RSI Statistics [Honestcowboy]⯁ Overview
Research tool for analysing price behaviour based on RSI, find out how your favorite trading pair / timeframe combinations react to RSI. 5 Different projections based on 5 different value zones of RSI:
RSI between 100-80 (very overbought)
RSI between 80-60 (overbought)
RSI between 60-40 (normal)
RSI between 40-20 (oversold)
RSI between 20-00 (very oversold)
The script simply show price projections of different RSI environments so you can get an idea of what price could do when RSI reaches this RSI value zone. Ofcourse past price performance does not guarantee future returns and this is just projections based on the past.
The script also projects RSI just like it does with price so you can get an idea of how long RSI might stay in overbought or very overbought etc
Script is mainly a research tool to use to get ideas to explore further and build upon. Here are some examples:
⯁ Settings
RSI Lenght: this is just normal RSI settings you find in standard RSI (bars used to calculate RSI)
Projection Length: Amount of bars to save for projections. The projections will also project this many bars in futre. Higher values here increase loading time drastically.
Price Action Boundaries: turn the highs / lows of projection zone on or off. I usually turn this off to look more closely at the averages themselves.
Maximum Stats history: Not on by default, in case you only want to show the average projection of last X amount of occurences RSI was in a specific RSI value zone
Selection of the different zones: in case you want to look at a specific zone alone or turn of some zones. It will no longer project for that zone both in the price projection and RSI projections.
⯁ How are these calculated?
To calculate the average price reaction script uses a very simple approach. On each bar it will save price action array up to projection length back in time. It will then check what the RSI value was there and store the array inside the right matrix.
It will use this matrix to calculate the averages, highs and lows of all these arrays for that specific RSI zone. It uses a simple arithmatic averaging method to get average value.
The script uses a similar approach for projecting the RSI itself into the future.
I include a visual showing it a bit better. This is from a different indicator of me using same approach:
The script will force you into a specific background, bar color and color template. Script is not meant to be used with other scripts and should be used as a standalone tool.
在脚本中搜索"zone"
Adaptive Market Wave TheoryAdaptive Market Wave Theory
🌊 CORE INNOVATION: PROBABILISTIC PHASE DETECTION WITH MULTI-AGENT CONSENSUS
Adaptive Market Wave Theory (AMWT) represents a fundamental paradigm shift in how traders approach market phase identification. Rather than counting waves subjectively or drawing static breakout levels, AMWT treats the market as a hidden state machine —using Hidden Markov Models, multi-agent consensus systems, and reinforcement learning algorithms to quantify what traditional methods leave to interpretation.
The Wave Analysis Problem:
Traditional wave counting methodologies (Elliott Wave, harmonic patterns, ABC corrections) share fatal weaknesses that AMWT directly addresses:
1. Non-Falsifiability : Invalid wave counts can always be "recounted" or "adjusted." If your Wave 3 fails, it becomes "Wave 3 of a larger degree" or "actually Wave C." There's no objective failure condition.
2. Observer Bias : Two expert wave analysts examining the same chart routinely reach different conclusions. This isn't a feature—it's a fundamental methodology flaw.
3. No Confidence Measure : Traditional analysis says "This IS Wave 3." But with what probability? 51%? 95%? The binary nature prevents proper position sizing and risk management.
4. Static Rules : Fixed Fibonacci ratios and wave guidelines cannot adapt to changing market regimes. What worked in 2019 may fail in 2024.
5. No Accountability : Wave methodologies rarely track their own performance. There's no feedback loop to improve.
The AMWT Solution:
AMWT addresses each limitation through rigorous mathematical frameworks borrowed from speech recognition, machine learning, and reinforcement learning:
• Non-Falsifiability → Hard Invalidation : Wave hypotheses die permanently when price violates calculated invalidation levels. No recounting allowed.
• Observer Bias → Multi-Agent Consensus : Three independent analytical agents must agree. Single-methodology bias is eliminated.
• No Confidence → Probabilistic States : Every market state has a calculated probability from Hidden Markov Model inference. "72% probability of impulse state" replaces "This is Wave 3."
• Static Rules → Adaptive Learning : Thompson Sampling multi-armed bandits learn which agents perform best in current conditions. The system adapts in real-time.
• No Accountability → Performance Tracking : Comprehensive statistics track every signal's outcome. The system knows its own performance.
The Core Insight:
"Traditional wave analysis asks 'What count is this?' AMWT asks 'What is the probability we are in an impulsive state, with what confidence, confirmed by how many independent methodologies, and anchored to what liquidity event?'"
🔬 THEORETICAL FOUNDATION: HIDDEN MARKOV MODELS
Why Hidden Markov Models?
Markets exist in hidden states that we cannot directly observe—only their effects on price are visible. When the market is in an "impulse up" state, we see rising prices, expanding volume, and trending indicators. But we don't observe the state itself—we infer it from observables.
This is precisely the problem Hidden Markov Models (HMMs) solve. Originally developed for speech recognition (inferring words from sound waves), HMMs excel at estimating hidden states from noisy observations.
HMM Components:
1. Hidden States (S) : The unobservable market conditions
2. Observations (O) : What we can measure (price, volume, indicators)
3. Transition Matrix (A) : Probability of moving between states
4. Emission Matrix (B) : Probability of observations given each state
5. Initial Distribution (π) : Starting state probabilities
AMWT's Six Market States:
State 0: IMPULSE_UP
• Definition: Strong bullish momentum with high participation
• Observable Signatures: Rising prices, expanding volume, RSI >60, price above upper Bollinger Band, MACD histogram positive and rising
• Typical Duration: 5-20 bars depending on timeframe
• What It Means: Institutional buying pressure, trend acceleration phase
State 1: IMPULSE_DN
• Definition: Strong bearish momentum with high participation
• Observable Signatures: Falling prices, expanding volume, RSI <40, price below lower Bollinger Band, MACD histogram negative and falling
• Typical Duration: 5-20 bars (often shorter than bullish impulses—markets fall faster)
• What It Means: Institutional selling pressure, panic or distribution acceleration
State 2: CORRECTION
• Definition: Counter-trend consolidation with declining momentum
• Observable Signatures: Sideways or mild counter-trend movement, contracting volume, RSI returning toward 50, Bollinger Bands narrowing
• Typical Duration: 8-30 bars
• What It Means: Profit-taking, digestion of prior move, potential accumulation for next leg
State 3: ACCUMULATION
• Definition: Base-building near lows where informed participants absorb supply
• Observable Signatures: Price near recent lows but not making new lows, volume spikes on up bars, RSI showing positive divergence, tight range
• Typical Duration: 15-50 bars
• What It Means: Smart money buying from weak hands, preparing for markup phase
State 4: DISTRIBUTION
• Definition: Top-forming near highs where informed participants distribute holdings
• Observable Signatures: Price near recent highs but struggling to advance, volume spikes on down bars, RSI showing negative divergence, widening range
• Typical Duration: 15-50 bars
• What It Means: Smart money selling to late buyers, preparing for markdown phase
State 5: TRANSITION
• Definition: Regime change period with mixed signals and elevated uncertainty
• Observable Signatures: Conflicting indicators, whipsaw price action, no clear momentum, high volatility without direction
• Typical Duration: 5-15 bars
• What It Means: Market deciding next direction, dangerous for directional trades
The Transition Matrix:
The transition matrix A captures the probability of moving from one state to another. AMWT initializes with empirically-derived values then updates online:
From/To IMP_UP IMP_DN CORR ACCUM DIST TRANS
IMP_UP 0.70 0.02 0.20 0.02 0.04 0.02
IMP_DN 0.02 0.70 0.20 0.04 0.02 0.02
CORR 0.15 0.15 0.50 0.10 0.10 0.00
ACCUM 0.30 0.05 0.15 0.40 0.05 0.05
DIST 0.05 0.30 0.15 0.05 0.40 0.05
TRANS 0.20 0.20 0.20 0.15 0.15 0.10
Key Insights from Transition Probabilities:
• Impulse states are sticky (70% self-transition): Once trending, markets tend to continue
• Corrections can transition to either impulse direction (15% each): The next move after correction is uncertain
• Accumulation strongly favors IMP_UP transition (30%): Base-building leads to rallies
• Distribution strongly favors IMP_DN transition (30%): Topping leads to declines
The Viterbi Algorithm:
Given a sequence of observations, how do we find the most likely state sequence? This is the Viterbi algorithm—dynamic programming to find the optimal path through the state space.
Mathematical Formulation:
δ_t(j) = max_i × B_j(O_t)
Where:
δ_t(j) = probability of most likely path ending in state j at time t
A_ij = transition probability from state i to state j
B_j(O_t) = emission probability of observation O_t given state j
AMWT Implementation:
AMWT runs Viterbi over a rolling window (default 50 bars), computing the most likely state sequence and extracting:
• Current state estimate
• State confidence (probability of current state vs alternatives)
• State sequence for pattern detection
Online Learning (Baum-Welch Adaptation):
Unlike static HMMs, AMWT continuously updates its transition and emission matrices based on observed market behavior:
f_onlineUpdateHMM(prev_state, curr_state, observation, decay) =>
// Update transition matrix
A *= decay
A += (1.0 - decay)
// Renormalize row
// Update emission matrix
B *= decay
B += (1.0 - decay)
// Renormalize row
The decay parameter (default 0.85) controls adaptation speed:
• Higher decay (0.95): Slower adaptation, more stable, better for consistent markets
• Lower decay (0.80): Faster adaptation, more reactive, better for regime changes
Why This Matters for Trading:
Traditional indicators give you a number (RSI = 72). AMWT gives you a probabilistic state assessment :
"There is a 78% probability we are in IMPULSE_UP state, with 15% probability of CORRECTION and 7% distributed among other states. The transition matrix suggests 70% chance of remaining in IMPULSE_UP next bar, 20% chance of transitioning to CORRECTION."
This enables:
• Position sizing by confidence : 90% confidence = full size; 60% confidence = half size
• Risk management by transition probability : High correction probability = tighten stops
• Strategy selection by state : IMPULSE = trend-follow; CORRECTION = wait; ACCUMULATION = scale in
🎰 THE 3-BANDIT CONSENSUS SYSTEM
The Multi-Agent Philosophy:
No single analytical methodology works in all market conditions. Trend-following excels in trending markets but gets chopped in ranges. Mean-reversion excels in ranges but gets crushed in trends. Structure-based analysis works when structure is clear but fails in chaotic markets.
AMWT's solution: employ three independent agents , each analyzing the market from a different perspective, then use Thompson Sampling to learn which agents perform best in current conditions.
Agent 1: TREND AGENT
Philosophy : Markets trend. Follow the trend until it ends.
Analytical Components:
• EMA Alignment: EMA8 > EMA21 > EMA50 (bullish) or inverse (bearish)
• MACD Histogram: Direction and rate of change
• Price Momentum: Close relative to ATR-normalized movement
• VWAP Position: Price above/below volume-weighted average price
Signal Generation:
Strong Bull: EMA aligned bull AND MACD histogram > 0 AND momentum > 0.3 AND close > VWAP
→ Signal: +1 (Long), Confidence: 0.75 + |momentum| × 0.4
Moderate Bull: EMA stack bull AND MACD rising AND momentum > 0.1
→ Signal: +1 (Long), Confidence: 0.65 + |momentum| × 0.3
Strong Bear: EMA aligned bear AND MACD histogram < 0 AND momentum < -0.3 AND close < VWAP
→ Signal: -1 (Short), Confidence: 0.75 + |momentum| × 0.4
Moderate Bear: EMA stack bear AND MACD falling AND momentum < -0.1
→ Signal: -1 (Short), Confidence: 0.65 + |momentum| × 0.3
When Trend Agent Excels:
• Trend days (IB extension >1.5x)
• Post-breakout continuation
• Institutional accumulation/distribution phases
When Trend Agent Fails:
• Range-bound markets (ADX <20)
• Chop zones after volatility spikes
• Reversal days at major levels
Agent 2: REVERSION AGENT
Philosophy: Markets revert to mean. Extreme readings reverse.
Analytical Components:
• Bollinger Band Position: Distance from bands, percent B
• RSI Extremes: Overbought (>70) and oversold (<30)
• Stochastic: %K/%D crossovers at extremes
• Band Squeeze: Bollinger Band width contraction
Signal Generation:
Oversold Bounce: BB %B < 0.20 AND RSI < 35 AND Stochastic < 25
→ Signal: +1 (Long), Confidence: 0.70 + (30 - RSI) × 0.01
Overbought Fade: BB %B > 0.80 AND RSI > 65 AND Stochastic > 75
→ Signal: -1 (Short), Confidence: 0.70 + (RSI - 70) × 0.01
Squeeze Fire Bull: Band squeeze ending AND close > upper band
→ Signal: +1 (Long), Confidence: 0.65
Squeeze Fire Bear: Band squeeze ending AND close < lower band
→ Signal: -1 (Short), Confidence: 0.65
When Reversion Agent Excels:
• Rotation days (price stays within IB)
• Range-bound consolidation
• After extended moves without pullback
When Reversion Agent Fails:
• Strong trend days (RSI can stay overbought for days)
• Breakout moves
• News-driven directional moves
Agent 3: STRUCTURE AGENT
Philosophy: Market structure reveals institutional intent. Follow the smart money.
Analytical Components:
• Break of Structure (BOS): Price breaks prior swing high/low
• Change of Character (CHOCH): First break against prevailing trend
• Higher Highs/Higher Lows: Bullish structure
• Lower Highs/Lower Lows: Bearish structure
• Liquidity Sweeps: Stop runs that reverse
Signal Generation:
BOS Bull: Price breaks above prior swing high with momentum
→ Signal: +1 (Long), Confidence: 0.70 + structure_strength × 0.2
CHOCH Bull: First higher low after downtrend, breaking structure
→ Signal: +1 (Long), Confidence: 0.75
BOS Bear: Price breaks below prior swing low with momentum
→ Signal: -1 (Short), Confidence: 0.70 + structure_strength × 0.2
CHOCH Bear: First lower high after uptrend, breaking structure
→ Signal: -1 (Short), Confidence: 0.75
Liquidity Sweep Long: Price sweeps below swing low then reverses strongly
→ Signal: +1 (Long), Confidence: 0.80
Liquidity Sweep Short: Price sweeps above swing high then reverses strongly
→ Signal: -1 (Short), Confidence: 0.80
When Structure Agent Excels:
• After liquidity grabs (stop runs)
• At major swing points
• During institutional accumulation/distribution
When Structure Agent Fails:
• Choppy, structureless markets
• During news events (structure becomes noise)
• Very low timeframes (noise overwhelms structure)
Thompson Sampling: The Bandit Algorithm
With three agents giving potentially different signals, how do we decide which to trust? This is the multi-armed bandit problem —balancing exploitation (using what works) with exploration (testing alternatives).
Thompson Sampling Solution:
Each agent maintains a Beta distribution representing its success/failure history:
Agent success rate modeled as Beta(α, β)
Where:
α = number of successful signals + 1
β = number of failed signals + 1
On Each Bar:
1. Sample from each agent's Beta distribution
2. Weight agent signals by sampled probabilities
3. Combine weighted signals into consensus
4. Update α/β based on trade outcomes
Mathematical Implementation:
// Beta sampling via Gamma ratio method
f_beta_sample(alpha, beta) =>
g1 = f_gamma_sample(alpha)
g2 = f_gamma_sample(beta)
g1 / (g1 + g2)
// Thompson Sampling selection
for each agent:
sampled_prob = f_beta_sample(agent.alpha, agent.beta)
weight = sampled_prob / sum(all_sampled_probs)
consensus += agent.signal × agent.confidence × weight
Why Thompson Sampling?
• Automatic Exploration : Agents with few samples get occasional chances (high variance in Beta distribution)
• Bayesian Optimal : Mathematically proven optimal solution to exploration-exploitation tradeoff
• Uncertainty-Aware : Small sample size = more exploration; large sample size = more exploitation
• Self-Correcting : Poor performers naturally get lower weights over time
Example Evolution:
Day 1 (Initial):
Trend Agent: Beta(1,1) → samples ~0.50 (high uncertainty)
Reversion Agent: Beta(1,1) → samples ~0.50 (high uncertainty)
Structure Agent: Beta(1,1) → samples ~0.50 (high uncertainty)
After 50 Signals:
Trend Agent: Beta(28,23) → samples ~0.55 (moderate confidence)
Reversion Agent: Beta(18,33) → samples ~0.35 (underperforming)
Structure Agent: Beta(32,19) → samples ~0.63 (outperforming)
Result: Structure Agent now receives highest weight in consensus
Consensus Requirements by Mode:
Aggressive Mode:
• Minimum 1/3 agents agreeing
• Consensus threshold: 45%
• Use case: More signals, higher risk tolerance
Balanced Mode:
• Minimum 2/3 agents agreeing
• Consensus threshold: 55%
• Use case: Standard trading
Conservative Mode:
• Minimum 2/3 agents agreeing
• Consensus threshold: 65%
• Use case: Higher quality, fewer signals
Institutional Mode:
• Minimum 2/3 agents agreeing
• Consensus threshold: 75%
• Additional: Session quality >0.65, mode adjustment +0.10
• Use case: Highest quality signals only
🌀 INTELLIGENT CHOP DETECTION ENGINE
The Chop Problem:
Most trading losses occur not from being wrong about direction, but from trading in conditions where direction doesn't exist . Choppy, range-bound markets generate false signals from every methodology—trend-following, mean-reversion, and structure-based alike.
AMWT's chop detection engine identifies these low-probability environments before signals fire, preventing the most damaging trades.
Five-Factor Chop Analysis:
Factor 1: ADX Component (25% weight)
ADX (Average Directional Index) measures trend strength regardless of direction.
ADX < 15: Very weak trend (high chop score)
ADX 15-20: Weak trend (moderate chop score)
ADX 20-25: Developing trend (low chop score)
ADX > 25: Strong trend (minimal chop score)
adx_chop = (i_adxThreshold - adx_val) / i_adxThreshold × 100
Why ADX Works: ADX synthesizes +DI and -DI movements. Low ADX means price is moving but not directionally—the definition of chop.
Factor 2: Choppiness Index (25% weight)
The Choppiness Index measures price efficiency using the ratio of ATR sum to price range:
CI = 100 × LOG10(SUM(ATR, n) / (Highest - Lowest)) / LOG10(n)
CI > 61.8: Choppy (range-bound, inefficient movement)
CI < 38.2: Trending (directional, efficient movement)
CI 38.2-61.8: Transitional
chop_idx_score = (ci_val - 38.2) / (61.8 - 38.2) × 100
Why Choppiness Index Works: In trending markets, price covers distance efficiently (low ATR sum relative to range). In choppy markets, price oscillates wildly but goes nowhere (high ATR sum relative to range).
Factor 3: Range Compression (20% weight)
Compares recent range to longer-term range, detecting volatility squeezes:
recent_range = Highest(20) - Lowest(20)
longer_range = Highest(50) - Lowest(50)
compression = 1 - (recent_range / longer_range)
compression > 0.5: Strong squeeze (potential breakout imminent)
compression < 0.2: No compression (normal volatility)
range_compression_score = compression × 100
Why Range Compression Matters: Compression precedes expansion. High compression = market coiling, preparing for move. Signals during compression often fail because the breakout hasn't occurred yet.
Factor 4: Channel Position (15% weight)
Tracks price position within the macro channel:
channel_position = (close - channel_low) / (channel_high - channel_low)
position 0.4-0.6: Center of channel (indecision zone)
position <0.2 or >0.8: Near extremes (potential reversal or breakout)
channel_chop = abs(0.5 - channel_position) < 0.15 ? high_score : low_score
Why Channel Position Matters: Price in the middle of a range is in "no man's land"—equally likely to go either direction. Signals in the channel center have lower probability.
Factor 5: Volume Quality (15% weight)
Assesses volume relative to average:
vol_ratio = volume / SMA(volume, 20)
vol_ratio < 0.7: Low volume (lack of conviction)
vol_ratio 0.7-1.3: Normal volume
vol_ratio > 1.3: High volume (conviction present)
volume_chop = vol_ratio < 0.8 ? (1 - vol_ratio) × 100 : 0
Why Volume Quality Matters: Low volume moves lack institutional participation. These moves are more likely to reverse or stall.
Combined Chop Intensity:
chopIntensity = (adx_chop × 0.25) + (chop_idx_score × 0.25) +
(range_compression_score × 0.20) + (channel_chop × 0.15) +
(volume_chop × i_volumeChopWeight × 0.15)
Regime Classifications:
Based on chop intensity and component analysis:
• Strong Trend (0-20%): ADX >30, clear directional momentum, trade aggressively
• Trending (20-35%): ADX >20, moderate directional bias, trade normally
• Transitioning (35-50%): Mixed signals, regime change possible, reduce size
• Mid-Range (50-60%): Price trapped in channel center, avoid new positions
• Ranging (60-70%): Low ADX, price oscillating within bounds, fade extremes only
• Compression (70-80%): Volatility squeeze, expansion imminent, wait for breakout
• Strong Chop (80-100%): Multiple chop factors aligned, avoid trading entirely
Signal Suppression:
When chop intensity exceeds the configurable threshold (default 80%), signals are suppressed entirely. The dashboard displays "⚠️ CHOP ZONE" with the current regime classification.
Chop Box Visualization:
When chop is detected, AMWT draws a semi-transparent box on the chart showing the chop zone. This visual reminder helps traders avoid entering positions during unfavorable conditions.
💧 LIQUIDITY ANCHORING SYSTEM
The Liquidity Concept:
Markets move from liquidity pool to liquidity pool. Stop losses cluster at predictable locations—below swing lows (buy stops become sell orders when triggered) and above swing highs (sell stops become buy orders when triggered). Institutions know where these clusters are and often engineer moves to trigger them before reversing.
AMWT identifies and tracks these liquidity events, using them as anchors for signal confidence.
Liquidity Event Types:
Type 1: Volume Spikes
Definition: Volume > SMA(volume, 20) × i_volThreshold (default 2.8x)
Interpretation: Sudden volume surge indicates institutional activity
• Near swing low + reversal: Likely accumulation
• Near swing high + reversal: Likely distribution
• With continuation: Institutional conviction in direction
Type 2: Stop Runs (Liquidity Sweeps)
Definition: Price briefly exceeds swing high/low then reverses within N bars
Detection:
• Price breaks above recent swing high (triggering buy stops)
• Then closes back below that high within 3 bars
• Signal: Bullish stop run complete, reversal likely
Or inverse for bearish:
• Price breaks below recent swing low (triggering sell stops)
• Then closes back above that low within 3 bars
• Signal: Bearish stop run complete, reversal likely
Type 3: Absorption Events
Definition: High volume with small candle body
Detection:
• Volume > 2x average
• Candle body < 30% of candle range
• Interpretation: Large orders being filled without moving price
• Implication: Accumulation (at lows) or distribution (at highs)
Type 4: BSL/SSL Pools (Buy-Side/Sell-Side Liquidity)
BSL (Buy-Side Liquidity):
• Cluster of swing highs within ATR proximity
• Stop losses from shorts sit above these highs
• Breaking BSL triggers short covering (fuel for rally)
SSL (Sell-Side Liquidity):
• Cluster of swing lows within ATR proximity
• Stop losses from longs sit below these lows
• Breaking SSL triggers long liquidation (fuel for decline)
Liquidity Pool Mapping:
AMWT continuously scans for and maps liquidity pools:
// Detect swing highs/lows using pivot function
swing_high = ta.pivothigh(high, 5, 5)
swing_low = ta.pivotlow(low, 5, 5)
// Track recent swing points
if not na(swing_high)
bsl_levels.push(swing_high)
if not na(swing_low)
ssl_levels.push(swing_low)
// Display on chart with labels
Confluence Scoring Integration:
When signals fire near identified liquidity events, confluence scoring increases:
• Signal near volume spike: +10% confidence
• Signal after liquidity sweep: +15% confidence
• Signal at BSL/SSL pool: +10% confidence
• Signal aligned with absorption zone: +10% confidence
Why Liquidity Anchoring Matters:
Signals "in a vacuum" have lower probability than signals anchored to institutional activity. A long signal after a liquidity sweep below swing lows has trapped shorts providing fuel. A long signal in the middle of nowhere has no such catalyst.
📊 SIGNAL GRADING SYSTEM
The Quality Problem:
Not all signals are created equal. A signal with 6/6 factors aligned is fundamentally different from a signal with 3/6 factors aligned. Traditional indicators treat them the same. AMWT grades every signal based on confluence.
Confluence Components (100 points total):
1. Bandit Consensus Strength (25 points)
consensus_str = weighted average of agent confidences
score = consensus_str × 25
Example:
Trend Agent: +1 signal, 0.80 confidence, 0.35 weight
Reversion Agent: 0 signal, 0.50 confidence, 0.25 weight
Structure Agent: +1 signal, 0.75 confidence, 0.40 weight
Weighted consensus = (0.80×0.35 + 0×0.25 + 0.75×0.40) / (0.35 + 0.40) = 0.77
Score = 0.77 × 25 = 19.25 points
2. HMM State Confidence (15 points)
score = hmm_confidence × 15
Example:
HMM reports 82% probability of IMPULSE_UP
Score = 0.82 × 15 = 12.3 points
3. Session Quality (15 points)
Session quality varies by time:
• London/NY Overlap: 1.0 (15 points)
• New York Session: 0.95 (14.25 points)
• London Session: 0.70 (10.5 points)
• Asian Session: 0.40 (6 points)
• Off-Hours: 0.30 (4.5 points)
• Weekend: 0.10 (1.5 points)
4. Energy/Participation (10 points)
energy = (realized_vol / avg_vol) × 0.4 + (range / ATR) × 0.35 + (volume / avg_volume) × 0.25
score = min(energy, 1.0) × 10
5. Volume Confirmation (10 points)
if volume > SMA(volume, 20) × 1.5:
score = 10
else if volume > SMA(volume, 20):
score = 5
else:
score = 0
6. Structure Alignment (10 points)
For long signals:
• Bullish structure (HH + HL): 10 points
• Higher low only: 6 points
• Neutral structure: 3 points
• Bearish structure: 0 points
Inverse for short signals
7. Trend Alignment (10 points)
For long signals:
• Price > EMA21 > EMA50: 10 points
• Price > EMA21: 6 points
• Neutral: 3 points
• Against trend: 0 points
8. Entry Trigger Quality (5 points)
• Strong trigger (multiple confirmations): 5 points
• Moderate trigger (single confirmation): 3 points
• Weak trigger (marginal): 1 point
Grade Scale:
Total Score → Grade
85-100 → A+ (Exceptional—all factors aligned)
70-84 → A (Strong—high probability)
55-69 → B (Acceptable—proceed with caution)
Below 55 → C (Marginal—filtered by default)
Grade-Based Signal Brightness:
Signal arrows on the chart have transparency based on grade:
• A+: Full brightness (alpha = 0)
• A: Slight fade (alpha = 15)
• B: Moderate fade (alpha = 35)
• C: Significant fade (alpha = 55)
This visual hierarchy helps traders instantly identify signal quality.
Minimum Grade Filter:
Configurable filter (default: C) sets the minimum grade for signal display:
• Set to "A" for only highest-quality signals
• Set to "B" for moderate selectivity
• Set to "C" for all signals (maximum quantity)
🕐 SESSION INTELLIGENCE
Why Sessions Matter:
Markets behave differently at different times. The London open is fundamentally different from the Asian lunch hour. AMWT incorporates session-aware logic to optimize signal quality.
Session Definitions:
Asian Session (18:00-03:00 ET)
• Characteristics: Lower volatility, range-bound tendency, fewer institutional participants
• Quality Score: 0.40 (40% of peak quality)
• Strategy Implications: Fade extremes, expect ranges, smaller position sizes
• Best For: Mean-reversion setups, accumulation/distribution identification
London Session (03:00-12:00 ET)
• Characteristics: European institutional activity, volatility pickup, trend initiation
• Quality Score: 0.70 (70% of peak quality)
• Strategy Implications: Watch for trend development, breakouts more reliable
• Best For: Initial trend identification, structure breaks
New York Session (08:00-17:00 ET)
• Characteristics: Highest liquidity, US institutional activity, major moves
• Quality Score: 0.95 (95% of peak quality)
• Strategy Implications: Best environment for directional trades
• Best For: Trend continuation, momentum plays
London/NY Overlap (08:00-12:00 ET)
• Characteristics: Peak liquidity, both European and US participants active
• Quality Score: 1.0 (100%—maximum quality)
• Strategy Implications: Highest probability for successful breakouts and trends
• Best For: All signal types—this is prime time
Off-Hours
• Characteristics: Thin liquidity, erratic price action, gaps possible
• Quality Score: 0.30 (30% of peak quality)
• Strategy Implications: Avoid new positions, wider stops if holding
• Best For: Waiting
Smart Weekend Detection:
AMWT properly handles the Sunday evening futures open:
// Traditional (broken):
isWeekend = dayofweek == saturday OR dayofweek == sunday
// AMWT (correct):
anySessionActive = not na(asianTime) or not na(londonTime) or not na(nyTime)
isWeekend = calendarWeekend AND NOT anySessionActive
This ensures Sunday 6pm ET (when futures open) correctly shows "Asian Session" rather than "Weekend."
Session Transition Boosts:
Certain session transitions create trading opportunities:
• Asian → London transition: +15% confidence boost (volatility expansion likely)
• London → Overlap transition: +20% confidence boost (peak liquidity approaching)
• Overlap → NY-only transition: -10% confidence adjustment (liquidity declining)
• Any → Off-Hours transition: Signal suppression recommended
📈 TRADE MANAGEMENT SYSTEM
The Signal Spam Problem:
Many indicators generate signal after signal, creating confusion and overtrading. AMWT implements a complete trade lifecycle management system that prevents signal spam and tracks performance.
Trade Lock Mechanism:
Once a signal fires, the system enters a "trade lock" state:
Trade Lock Duration: Configurable (default 30 bars)
Early Exit Conditions:
• TP3 hit (full target reached)
• Stop Loss hit (trade failed)
• Lock expiration (time-based exit)
During lock:
• No new signals of same type displayed
• Opposite signals can override (reversal)
• Trade status tracked in dashboard
Target Levels:
Each signal generates three profit targets based on ATR:
TP1 (Conservative Target)
• Default: 1.0 × ATR
• Purpose: Quick partial profit, reduce risk
• Action: Take 30-40% off position, move stop to breakeven
TP2 (Standard Target)
• Default: 2.5 × ATR
• Purpose: Main profit target
• Action: Take 40-50% off position, trail stop
TP3 (Extended Target)
• Default: 5.0 × ATR
• Purpose: Runner target for trend days
• Action: Close remaining position or continue trailing
Stop Loss:
• Default: 1.9 × ATR from entry
• Purpose: Define maximum risk
• Placement: Below recent swing low (longs) or above recent swing high (shorts)
Invalidation Level:
Beyond stop loss, AMWT calculates an "invalidation" level where the wave hypothesis dies:
invalidation = entry - (ATR × INVALIDATION_MULT × 1.5)
If price reaches invalidation, the current market interpretation is wrong—not just the trade.
Visual Trade Management:
During active trades, AMWT displays:
• Entry arrow with grade label (▲A+, ▼B, etc.)
• TP1, TP2, TP3 horizontal lines in green
• Stop Loss line in red
• Invalidation line in orange (dashed)
• Progress indicator in dashboard
Persistent Execution Markers:
When targets or stops are hit, permanent markers appear:
• TP hit: Green dot with "TP1"/"TP2"/"TP3" label
• SL hit: Red dot with "SL" label
These persist on the chart for review and statistics.
💰 PERFORMANCE TRACKING & STATISTICS
Tracked Metrics:
• Total Trades: Count of all signals that entered trade lock
• Winning Trades: Signals where at least TP1 was reached before SL
• Losing Trades: Signals where SL was hit before any TP
• Win Rate: Winning / Total × 100%
• Total R Profit: Sum of R-multiples from winning trades
• Total R Loss: Sum of R-multiples from losing trades
• Net R: Total R Profit - Total R Loss
Currency Conversion System:
AMWT can display P&L in multiple formats:
R-Multiple (Default)
• Shows risk-normalized returns
• "Net P&L: +4.2R | 78 trades" means 4.2 times initial risk gained over 78 trades
• Best for comparing across different position sizes
Currency Conversion (USD/EUR/GBP/JPY/INR)
• Converts R-multiples to currency based on:
- Dollar Risk Per Trade (user input)
- Tick Value (user input)
- Selected currency
Example Configuration:
Dollar Risk Per Trade: $100
Display Currency: USD
If Net R = +4.2R
Display: Net P&L: +$420.00 | 78 trades
Ticks
• For futures traders who think in ticks
• Converts based on tick value input
Statistics Reset:
Two reset methods:
1. Toggle Reset
• Turn "Reset Statistics" toggle ON then OFF
• Clears all statistics immediately
2. Date-Based Reset
• Set "Reset After Date" (YYYY-MM-DD format)
• Only trades after this date are counted
• Useful for isolating recent performance
🎨 VISUAL FEATURES
Macro Channel:
Dynamic regression-based channel showing market boundaries:
• Upper/lower bounds calculated from swing pivot linear regression
• Adapts to current market structure
• Shows overall trend direction and potential reversal zones
Chop Boxes:
Semi-transparent overlay during high-chop periods:
• Purple/orange coloring indicates dangerous conditions
• Visual reminder to avoid new positions
Confluence Heat Zones:
Background shading indicating setup quality:
• Darker shading = higher confluence
• Lighter shading = lower confluence
• Helps identify optimal entry timing
EMA Ribbon:
Trend visualization via moving average fill:
• EMA 8/21/50 with gradient fill between
• Green fill when bullish aligned
• Red fill when bearish aligned
• Gray when neutral
Absorption Zone Boxes:
Marks potential accumulation/distribution areas:
• High volume + small body = absorption
• Boxes drawn at these levels
• Often act as support/resistance
Liquidity Pool Lines:
BSL/SSL levels with labels:
• Dashed lines at liquidity clusters
• "BSL" label above swing high clusters
• "SSL" label below swing low clusters
Six Professional Themes:
• Quantum: Deep purples and cyans (default)
• Cyberpunk: Neon pinks and blues
• Professional: Muted grays and greens
• Ocean: Blues and teals
• Matrix: Greens and blacks
• Ember: Oranges and reds
🎓 PROFESSIONAL USAGE PROTOCOL
Phase 1: Learning the System (Week 1)
Goal: Understand AMWT concepts and dashboard interpretation
Setup:
• Signal Mode: Balanced
• Display: All features enabled
• Grade Filter: C (see all signals)
Actions:
• Paper trade ONLY—no real money
• Observe HMM state transitions throughout the day
• Note when agents agree vs disagree
• Watch chop detection engage and disengage
• Track which grades produce winners vs losers
Key Learning Questions:
• How often do A+ signals win vs B signals? (Should see clear difference)
• Which agent tends to be right in current market? (Check dashboard)
• When does chop detection save you from bad trades?
• How do signals near liquidity events perform vs signals in vacuum?
Phase 2: Parameter Optimization (Week 2)
Goal: Tune system to your instrument and timeframe
Signal Mode Testing:
• Run 5 days on Aggressive mode (more signals)
• Run 5 days on Conservative mode (fewer signals)
• Compare: Which produces better risk-adjusted returns?
Grade Filter Testing:
• Track A+ only for 20 signals
• Track A and above for 20 signals
• Track B and above for 20 signals
• Compare win rates and expectancy
Chop Threshold Testing:
• Default (80%): Standard filtering
• Try 70%: More aggressive filtering
• Try 90%: Less filtering
• Which produces best results for your instrument?
Phase 3: Strategy Development (Weeks 3-4)
Goal: Develop personal trading rules based on system signals
Position Sizing by Grade:
• A+ grade: 100% position size
• A grade: 75% position size
• B grade: 50% position size
• C grade: 25% position size (or skip)
Session-Based Rules:
• London/NY Overlap: Take all A/A+ signals
• NY Session: Take all A+ signals, selective on A
• Asian Session: Only A+ signals with extra confirmation
• Off-Hours: No new positions
Chop Zone Rules:
• Chop >70%: Reduce position size 50%
• Chop >80%: No new positions
• Chop <50%: Full position size allowed
Phase 4: Live Micro-Sizing (Month 2)
Goal: Validate paper trading results with minimal risk
Setup:
• 10-20% of intended full position size
• Take ONLY A+ signals initially
• Follow trade management religiously
Tracking:
• Log every trade: Entry, Exit, Grade, HMM State, Chop Level, Agent Consensus
• Calculate: Win rate by grade, by session, by chop level
• Compare to paper trading (should be within 15%)
Red Flags:
• Win rate diverges significantly from paper trading: Execution issues
• Consistent losses during certain sessions: Adjust session rules
• Losses cluster when specific agent dominates: Review that agent's logic
Phase 5: Scaling Up (Months 3-6)
Goal: Gradually increase to full position size
Progression:
• Month 3: 25-40% size (if micro-sizing profitable)
• Month 4: 40-60% size
• Month 5: 60-80% size
• Month 6: 80-100% size
Scale-Up Requirements:
• Minimum 30 trades at current size
• Win rate ≥50%
• Net R positive
• No revenge trading incidents
• Emotional control maintained
💡 DEVELOPMENT INSIGHTS
Why HMM Over Simple Indicators:
Early versions used standard indicators (RSI >70 = overbought, etc.). Win rates hovered at 52-55%. The problem: indicators don't capture state. RSI can stay "overbought" for weeks in a strong trend.
The insight: markets exist in states, and state persistence matters more than indicator levels. Implementing HMM with state transition probabilities increased signal quality significantly. The system now knows not just "RSI is high" but "we're in IMPULSE_UP state with 70% probability of staying in IMPULSE_UP."
The Multi-Agent Evolution:
Original version used a single analytical methodology—trend-following. Performance was inconsistent: great in trends, destroyed in ranges. Added mean-reversion agent: now it was inconsistent the other way.
The breakthrough: use multiple agents and let the system learn which works . Thompson Sampling wasn't the first attempt—tried simple averaging, voting, even hard-coded regime switching. Thompson Sampling won because it's mathematically optimal and automatically adapts without manual regime detection.
Chop Detection Revelation:
Chop detection was added almost as an afterthought. "Let's filter out obviously bad conditions." Testing revealed it was the most impactful single feature. Filtering chop zones reduced losing trades by 35% while only reducing total signals by 20%. The insight: avoiding bad trades matters more than finding good ones.
Liquidity Anchoring Discovery:
Watched hundreds of trades. Noticed pattern: signals that fired after liquidity events (stop runs, volume spikes) had significantly higher win rates than signals in quiet markets. Implemented liquidity detection and anchoring. Win rate on liquidity-anchored signals: 68% vs 52% on non-anchored signals.
The Grade System Impact:
Early system had binary signals (fire or don't fire). Adding grading transformed it. Traders could finally match position size to signal quality. A+ signals deserved full size; C signals deserved caution. Just implementing grade-based sizing improved portfolio Sharpe ratio by 0.3.
🚨 LIMITATIONS & CRITICAL ASSUMPTIONS
What AMWT Is NOT:
• NOT a Holy Grail : No system wins every trade. AMWT improves probability, not certainty.
• NOT Fully Automated : AMWT provides signals and analysis; execution requires human judgment.
• NOT News-Proof : Exogenous shocks (FOMC surprises, geopolitical events) invalidate all technical analysis.
• NOT for Scalping : HMM state estimation needs time to develop. Sub-minute timeframes are not appropriate.
Core Assumptions:
1. Markets Have States : Assumes markets transition between identifiable regimes. Violation: Random walk markets with no regime structure.
2. States Are Inferable : Assumes observable indicators reveal hidden states. Violation: Market manipulation creating false signals.
3. History Informs Future : Assumes past agent performance predicts future performance. Violation: Regime changes that invalidate historical patterns.
4. Liquidity Events Matter : Assumes institutional activity creates predictable patterns. Violation: Markets with no institutional participation.
Performs Best On:
• Liquid Futures : ES, NQ, MNQ, MES, CL, GC
• Major Forex Pairs : EUR/USD, GBP/USD, USD/JPY
• Large-Cap Stocks : AAPL, MSFT, TSLA, NVDA (>$5B market cap)
• Liquid Crypto : BTC, ETH on major exchanges
Performs Poorly On:
• Illiquid Instruments : Low volume stocks, exotic pairs
• Very Low Timeframes : Sub-5-minute charts (noise overwhelms signal)
• Binary Event Days : Earnings, FDA approvals, court rulings
• Manipulated Markets : Penny stocks, low-cap altcoins
Known Weaknesses:
• Warmup Period : HMM needs ~50 bars to initialize properly. Early signals may be unreliable.
• Regime Change Lag : Thompson Sampling adapts over time, not instantly. Sudden regime changes may cause short-term underperformance.
• Complexity : More parameters than simple indicators. Requires understanding to use effectively.
⚠️ RISK DISCLOSURE
Trading futures, stocks, options, forex, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Adaptive Market Wave Theory, while based on rigorous mathematical frameworks including Hidden Markov Models and multi-armed bandit algorithms, does not guarantee profits and can result in significant losses.
AMWT's methodologies—HMM state estimation, Thompson Sampling agent selection, and confluence-based grading—have theoretical foundations but past performance is not indicative of future results.
Hidden Markov Model assumptions may not hold during:
• Major news events disrupting normal market behavior
• Flash crashes or circuit breaker events
• Low liquidity periods with erratic price action
• Algorithmic manipulation or spoofing
Multi-agent consensus assumes independent analytical perspectives provide edge. Market conditions change. Edges that existed historically can diminish or disappear.
Users must independently validate system performance on their specific instruments, timeframes, and broker execution environment. Paper trade extensively before risking capital. Start with micro position sizing.
Never risk more than you can afford to lose completely. Use proper position sizing. Implement stop losses without exception.
By using this indicator, you acknowledge these risks and accept full responsibility for all trading decisions and outcomes.
"Elliott Wave was a first-order approximation of market phase behavior. AMWT is the second—probabilistic, adaptive, and accountable."
Initial Public Release
Core Engine:
• True Hidden Markov Model with online Baum-Welch learning
• Viterbi algorithm for optimal state sequence decoding
• 6-state market regime classification
Agent System:
• 3-Bandit consensus (Trend, Reversion, Structure)
• Thompson Sampling with true Beta distribution sampling
• Adaptive weight learning based on performance
Signal Generation:
• Quality-based confluence grading (A+/A/B/C)
• Four signal modes (Aggressive/Balanced/Conservative/Institutional)
• Grade-based visual brightness
Chop Detection:
• 5-factor analysis (ADX, Choppiness Index, Range Compression, Channel Position, Volume)
• 7 regime classifications
• Configurable signal suppression threshold
Liquidity:
• Volume spike detection
• Stop run (liquidity sweep) identification
• BSL/SSL pool mapping
• Absorption zone detection
Trade Management:
• Trade lock with configurable duration
• TP1/TP2/TP3 targets
• ATR-based stop loss
• Persistent execution markers
Session Intelligence:
• Asian/London/NY/Overlap detection
• Smart weekend handling (Sunday futures open)
• Session quality scoring
Performance:
• Statistics tracking with reset functionality
• 7 currency display modes
• Win rate and Net R calculation
Visuals:
• Macro channel with linear regression
• Chop boxes
• EMA ribbon
• Liquidity pool lines
• 6 professional themes
Dashboards:
• Main Dashboard: Market State, Consensus, Trade Status, Statistics
📋 AMWT vs AMWT-PRO:
This version includes all core AMWT functionality:
✓ Full Hidden Markov Model state estimation
✓ 3-Bandit Thompson Sampling consensus system
✓ Complete 5-factor chop detection engine
✓ All four signal modes
✓ Full trade management with TP/SL tracking
✓ Main dashboard with complete statistics
✓ All visual features (channels, zones, pools)
✓ Identical signal generation to PRO
✓ Six professional themes
✓ Full alert system
The PRO version adds the AMWT Advisor panel—a secondary dashboard providing:
• Real-time Market Pulse situation assessment
• Agent Matrix visualization (individual agent votes)
• Structure analysis breakdown
• "Watch For" upcoming setups
• Action Command coaching
Both versions generate identical signals . The Advisor provides additional guidance for interpreting those signals.
Taking you to school. - Dskyz, Trade with probability. Trade with consensus. Trade with AMWT.
FVG MTF Consensus OscillatorFVG MTF Consensus Oscillator
A multi-timeframe, multi-component oscillator that combines momentum, deviation, and slope analysis across multiple timeframes using Zeiierman's Chebyshev-filtered trend calculation. This indicator identifies potential turning points with zone-based signal classification and timeframe consensus filtering.
Backed by ML/Deep Learning evaluation on ES Futures data from 2015-2024.
🎯 Concept
Traditional oscillators suffer from two major weaknesses:
Single measurement - relying on one metric makes them susceptible to noise
Single timeframe - missing the bigger picture leads to fighting the trend
The FVG MTF Consensus Oscillator addresses both issues by combining three independent measurements across three timeframes into a weighted consensus signal.
The Three Components
Momentum - How fast is the trend moving?
Deviation - How far has price stretched from the trend?
Slope - What is the short-term directional bias?
The Three Timeframes
TF1 (Chart) - Your current chart timeframe (lowest weight)
TF2 (Medium) - Typically 1H or 4H (medium weight)
TF3 (High) - Typically 4H or Daily (highest weight)
By requiring agreement across multiple components AND multiple timeframes, the oscillator filters out noise while capturing meaningful, high-probability market movements.
🔧 How It Works
The Core: Chebyshev Type 1 Filter
At its heart, this indicator uses a Chebyshev Type 1 low-pass filter (inspired by Zeiierman's FVG Trend) to extract a clean trend line from price action. Unlike simple moving averages, the Chebyshev filter offers:
Sharper cutoff between trend and noise
Minimal lag for a given smoothness level
Controlled overshoot via the ripple parameter
Three Oscillator Components
1. Momentum Component
Momentum = Current Trend Value - Previous Trend Value
Measures the velocity of the trend. High positive values indicate strong upward acceleration, while high negative values show downward acceleration.
2. Deviation Component
Deviation = Close Price - Trend Value
Measures how far price has stretched away from the trend line. Useful for identifying overextended conditions and mean reversion opportunities.
3. Slope Component
Slope = Change in Trend over 3 bars
Captures the short-term directional bias of the trend itself, helping confirm trend changes.
Normalization & Component Consensus
Each component is individually normalized to a -100 to +100 scale using adaptive scaling. The oscillator output is a weighted average of all three components, allowing you to emphasize different aspects based on your trading style.
Multi-Timeframe Weighting
The final oscillator value combines all three timeframes using configurable weights:
Combined = (TF1 × Weight1 + TF2 × Weight2 + TF3 × Weight3) / Total Weight
Default weights (1, 2, 3) ensure higher timeframes have more influence, keeping you aligned with the dominant trend while timing entries on lower timeframes.
📊 Zone System
The oscillator uses a fuzzy zone system to classify market conditions:
ZoneRangeInterpretationSignal ColorNeutral-5 to +5No clear bias, avoid tradingGrayContinuation±5 to ±25Trend pullback, continuation setupsAquaDeep Swing±25 to ±50Extended move, stronger setupsGreenReversalBeyond ±50Extreme extension, reversal potentialOrange
When "Show Zone Background" is enabled, the background shading darkens as the oscillator moves into more extreme zones, providing instant visual feedback.
📈 Signal Interpretation
Turn Signals
The indicator plots triangular markers when the oscillator changes direction:
▲ Triangle Up (bottom): Oscillator turning up from a low
▼ Triangle Down (top): Oscillator turning down from a high
Signal Quality by Zone
Not all signals are equal. The signal color indicates which zone the turn occurred in:
ColorZoneProbabilityBest UseGrayNeutralLowAvoid or use very tight stopsAquaContinuationModerateTrend continuation entriesGreenDeep SwingHigherSwing trade entriesOrangeReversalHighestCounter-trend with caution
Timeframe Consensus Filter
Signals only fire when the required number of timeframes agree on direction. With default settings (TF Consensus = 2), at least 2 of 3 timeframes must be moving in the same direction for a signal to trigger.
This prevents:
Taking longs when higher timeframes are bearish
Taking shorts when higher timeframes are bullish
Whipsaws during timeframe disagreement
Trend Coloring
The combined oscillator line changes color based on trend direction:
Light purple (RGB 240, 174, 252): Majority of timeframes trending up
Dark purple (RGB 84, 19, 95): Majority of timeframes trending down
Info Table
When MTF is enabled, a table in the top-right corner displays:
Current oscillator values for each timeframe (TF1, TF2, TF3)
Combined value (CMB)
Color coding: Green = rising, Red = falling
⚙️ Settings Guide
Timeframe Settings
SettingDefaultDescriptionEnable Multi-TimeframeOnMaster switch for MTF functionalityTF1 (Chart)"" (current)First timeframe, typically your chart TFTF2 (Medium)60Second timeframe, typically 1HTF3 (High)240Third timeframe, typically 4HTF1/TF2/TF3 Weight1 / 2 / 3Influence of each TF on combined signal
Timeframe Tips:
Keep TF1 ≤ TF2 ≤ TF3 (ascending order)
For day trading: 5m / 15m / 1H
For swing trading: 1H / 4H / Daily
For position trading: 4H / Daily / Weekly
Display Settings
SettingDefaultDescriptionShow All TimeframesOffDisplay individual TF oscillator linesShow Combined LineOnDisplay the weighted combined oscillatorShow Zone BackgroundOffShade background based on current zone
Trend Filter Settings
SettingDefaultDescriptionTrend Ripple4.0Filter responsiveness (1-10). Higher = faster but more overshootTrend Cutoff0.1Cutoff frequency (0.01-0.5). Lower = smoother trendNormalization Length50Lookback for scaling. Longer = more stable
Component Weights
SettingDefaultDescriptionMomentum Weight1.0Emphasis on trend speedDeviation Weight1.0Emphasis on price stretch from trendSlope Weight1.0Emphasis on short-term trend direction
Component Tips:
For trend-following: Increase Momentum and Slope weights
For mean reversion: Increase Deviation weight
Set any weight to 0 to disable that component
Zone Thresholds
SettingDefaultDescriptionNeutral Zone5Inner boundary (±5 = neutral)Continuation Zone25Middle boundary for continuation setupsDeep Swing Zone50Outer boundary for reversal zone
Adjust based on instrument volatility. More volatile instruments may need wider zones.
Signal Filters
SettingDefaultDescriptionSignal Cooldown3Minimum bars between signalsMin Turn Size2.0Minimum oscillator change for valid turnTF Consensus Required2Minimum TFs agreeing for signal (1-3)
💡 Usage Examples
Example 1: Trend Continuation (Dip Buying)
Setup: Uptrend confirmed by higher timeframes
Check the info table - TF2 and TF3 should show green (rising)
Wait for TF1 to pull back, oscillator enters Continuation zone
Enter on Aqua ▲ signal (turn up with TF consensus)
Stop below recent swing low
Target: Previous high or next resistance
Why it works: You're buying a dip in an established uptrend with multi-timeframe confirmation.
Example 2: Deep Swing Entry
Setup: Extended move showing exhaustion
Oscillator reaches Deep Swing zone (±25 to ±50)
At least 2 TFs start showing the same direction
Enter on Green signal indicating momentum exhaustion
Use tighter stop as the move is already extended
Target: Return to Continuation zone or trend line
Why it works: Extended moves tend to mean-revert. The zone system identifies these opportunities.
Example 3: Reversal Setup (Advanced)
Setup: Extreme extension with diverging timeframes
Oscillator reaches Reversal zone (beyond ±50)
Watch for TF1 to turn while TF3 is still extended
Enter on Orange signal - this is counter-trend!
Use smaller position size and wider stops
Target: Return to Deep Swing or Continuation zone
Why it works: Extreme extensions eventually correct. The orange signal marks high-probability reversal points.
Example 4: Avoiding Bad Trades
What to avoid:
Gray signals in Neutral zone - No edge, random noise
Signals against TF3 direction - Fighting the dominant trend
Signals without TF consensus - Timeframe disagreement = choppy market
Multiple signals in quick succession - Let cooldown filter work
🔬 Multi-Timeframe Analysis Tips
Reading the Info Table
The info table shows real-time oscillator values:
| TF1 | TF2 | TF3 | CMB |
| 23.5 | 45.2 | 67.8 | 52.1 |
All green: Strong uptrend across all timeframes
All red: Strong downtrend across all timeframes
Mixed colors: Potential transition or consolidation
Timeframe Alignment States
TF1TF2TF3Interpretation↑↑↑Strong bull - look for long entries↓↓↓Strong bear - look for short entries↑↑↓Pullback in downtrend - caution on longs↓↓↑Pullback in uptrend - caution on shorts↑↓↑Choppy - reduce position size↓↑↓Choppy - reduce position size
The Power of Consensus
With TF Consensus = 2, signals only fire when 2+ timeframes agree. This single filter eliminates most whipsaws and keeps you aligned with the dominant trend.
For more conservative trading, set TF Consensus = 3 (all timeframes must agree).
⚠️ Important Notes
This indicator does not predict the future. It measures current market conditions and momentum across multiple timeframes.
Always use proper risk management. No indicator is 100% accurate.
Combine with price action. The oscillator works best when confirmed by support/resistance, candlestick patterns, or other confluence factors.
Respect the higher timeframe. When TF3 disagrees, trade smaller or sit out.
Zone signals are probabilistic. Orange (reversal) signals have higher probability but aren't guaranteed reversals.
Adjust settings per instrument. Default settings are optimized for ES Futures but may need tuning for other markets.
🧪 ML/Deep Learning Background
The default parameters and zone thresholds were evaluated using machine learning techniques on ES Futures data spanning 2015-2024. This included:
Optimization of component weights
Zone threshold calibration
Timeframe weight balancing
Signal filter tuning
While past performance doesn't guarantee future results, the parameters represent a data-driven starting point rather than arbitrary defaults.
🙏 Credits
This indicator is inspired by Zeiierman's Multitimeframe Fair Value Gap (FVG) indicator, specifically utilizing concepts from his Chebyshev Type 1 filter implementation for trend calculation.
Original indicator: Multitimeframe Fair Value Gap – FVG (Zeiierman)
📝 Changelog
v1.0
Initial release
Three-component consensus oscillator (Momentum, Deviation, Slope)
Multi-timeframe support with weighted combination
Fuzzy zone classification system
Configurable component and timeframe weights
TF consensus filter for signal quality
Signal cooldown and minimum turn size filters
Real-time info table with TF values
Optional zone background shading
Inside SwingsOverview
The Inside Swings indicator identifies and visualizes "inside swing" patterns in price action. These patterns occur when price creates a series of pivots that form overlapping ranges, indicating potential consolidation or reversal zones.
What are Inside Swings?
Inside swings are specific pivot patterns where:
- HLHL Pattern: High-Low-High-Low sequence where the first high is higher than the second high, and the first low is lower than the second low
- LHLH Pattern: Low-High-Low-High sequence where the first low is lower than the second low, and the first high is higher than the second high
Here an Example
These patterns create overlapping price ranges that often act as:
- Support/Resistance zones
- Consolidation areas
- Potential reversal points
- Breakout levels
Levels From the Created Range
Input Parameters
Core Settings
- Pivot Lookback Length (default: 5): Number of bars on each side to confirm a pivot high/low
- Max Boxes (default: 100): Maximum number of patterns to display on chart
Extension Settings
- Extend Lines: Enable/disable line extensions - this extends the Extremes of the Swings to where a new Swing Started or Extended Right for the Latest Inside Swings
- Show High 1 Line: Display first high/low extension line
- Show High 2 Line: Display second high/low extension line
- Show Low 1 Line: Display first low/high extension line
- Show Low 2 Line: Display second low/high extension line
Visual Customization
Box Colors
- HLHL Box Color: Color for HLHL pattern boxes (default: green)
- HLHL Border Color: Border color for HLHL boxes
- LHLH Box Color: Color for LHLH pattern boxes (default: red)
- LHLH Border Color: Border color for LHLH boxes
Line Colors
- HLHL Line Color: Extension line color for HLHL patterns
- LHLH Line Color: Extension line color for LHLH patterns
- Line Width: Thickness of extension lines (1-5)
Pattern Detection Logic
HLHL Pattern (Bullish Inside Swing)
Condition: High1 > High2 AND Low1 < Low2
Sequence: High → Low → High → Low
Visual: Two overlapping boxes with first range encompassing second
Detection Criteria:
1. Last 4 pivots form High-Low-High-Low sequence
2. Fourth pivot (first high) > Second pivot (second high)
3. Third pivot (first low) < Last pivot (second low)
LHLH Pattern (Bearish Inside Swing)
Condition: Low1 < Low2 AND High1 > High2
Sequence: Low → High → Low → High
Visual: Two overlapping boxes with first range encompassing second
Detection Criteria:
1. Last 4 pivots form Low-High-Low-High sequence
2. Fourth pivot (first low) < Second pivot (second low)
3. Third pivot (first high) > Last pivot (second high)
Visual Elements
Boxes
- Box 1: Spans from first pivot to last pivot (larger range)
- Box 2: Spans from third pivot to last pivot (smaller range)
- Overlap: The intersection of both boxes represents the inside swing zone
Extension Lines
- High 1 Line: Horizontal line at first high/low level
- High 2 Line: Horizontal line at second high/low level
- Low 1 Line: Horizontal line at first low/high level
- Low 2 Line: Horizontal line at second low/high level
Line Extension Behavior
- Historical Patterns: Lines extend until the next pattern starts
- Latest Pattern: Lines extend to the right edge of chart
- Dynamic Updates: All lines are redrawn on each bar for accuracy
Trading Applications
Support/Resistance Levels
Inside swing levels often act as:
- Dynamic support/resistance
- Breakout confirmation levels
- Reversal entry points
Pattern Interpretation
- HLHL Patterns: Potential bullish continuation or reversal
- LHLH Patterns: Potential bearish continuation or reversal
- Overlap Zone: Key area for price interaction
Entry Strategies
1. Breakout Strategy: Enter on break above/below inside swing levels
2. Reversal Strategy: Enter on bounce from inside swing levels
3. Range Trading: Trade between inside swing levels
Technical Implementation
Data Structures
type InsideSwing
int startBar // First pivot bar
int endBar // Last pivot bar
string patternType // "HLHL" or "LHLH"
float high1 // First high/low
float low1 // First low/high
float high2 // Second high/low
float low2 // Second low/high
box box1 // First box
box box2 // Second box
line high1Line // High 1 extension line
line high2Line // High 2 extension line
line low1Line // Low 1 extension line
line low2Line // Low 2 extension line
bool isLatest // Latest pattern flag
Memory Management
- Pattern Storage: Array-based storage with automatic cleanup
- Pivot Tracking: Maintains last 4 pivots for pattern detection
- Resource Cleanup: Automatically removes oldest patterns when limit exceeded
Performance Optimization
- Duplicate Prevention: Checks for existing patterns before creation
- Efficient Redraw: Only redraws lines when necessary
- Memory Limits: Configurable maximum pattern count
Usage Tips
Best Practices
1. Combine with Volume: Use volume confirmation for breakouts
2. Multiple Timeframes: Check higher timeframes for context
3. Risk Management: Set stops beyond inside swing levels
4. Pattern Validation: Wait for confirmation before entering
Common Scenarios
- Consolidation Breakouts: Inside swings often precede significant moves
- Reversal Zones: Failed breakouts at inside swing levels
- Trend Continuation: Inside swings in trending markets
Limitations
- Lagging Indicator: Patterns form after completion
- False Signals: Not all inside swings lead to significant moves
- Market Dependent: Effectiveness varies by market conditions
Customization Options
Visual Adjustments
- Modify colors for different market conditions
- Adjust line widths for visibility
- Enable/disable specific elements
Detection Sensitivity
- Increase pivot length for smoother patterns
- Decrease for more sensitive detection
- Balance between noise and signal
Display Management
- Control maximum pattern count
- Adjust cleanup frequency
- Manage memory usage
Conclusion
The Inside Swings indicator provides a systematic approach to identifying consolidation and potential reversal zones in price action. By visualizing overlapping pivot ranges
The indicator's strength lies in its ability to:
- Identify key price levels automatically
- Provide visual context for market structure
- Offer flexible customization options
- Maintain performance through efficient memory management
Aladin Pair Trading System v1Aladin Pair Trading System v1
What is This Indicator?
The Aladin Pair Trading System is a sophisticated tool designed to help traders identify profitable opportunities by comparing two related stocks that historically move together. Think of it as finding when one twin is running ahead or lagging behind the other - these moments often present trading opportunities as they tend to return to moving together.
Who Should Use This?
Beginners: Learn about statistical arbitrage and pair trading
Intermediate Traders: Execute mean-reversion strategies with confidence
Advanced Traders: Fine-tune parameters for optimal pair relationships
Portfolio Managers: Implement market-neutral strategies
💡 What is Pair Trading?
Imagine two ice cream shops next to each other. They usually have similar customer traffic because they're in the same area. If one day Shop A is packed while Shop B is empty, you might expect this imbalance to correct itself soon.
Pair trading works the same way:
You find two stocks that normally move together (like TCS and Infosys)
When one stock moves too far from the other, you trade expecting them to realign
You buy the lagging stock and sell the leading stock
When they come back together, you profit from both sides
Key Features
1. Z-Score Analysis
What it is: A statistical measure showing how far the price relationship has deviated from normal
What it means:
Z-Score near 0 = Normal relationship
Z-Score at +2 = Stock A is expensive relative to Stock B (Sell A, Buy B)
Z-Score at -2 = Stock A is cheap relative to Stock B (Buy A, Sell B)
2. Multiple Timeframe Analysis
Long-term Z-Score (300 bars): Shows the big picture trend
Short-term Z-Score (100 bars): Shows recent movements
Signal Z-Score (20 bars): Generates quick trading signals
3. Statistical Validation
The indicator checks if the pair is suitable for trading:
Correlation (must be > 0.7): Confirms the stocks move together
1.0 = Perfect positive correlation
0.7 = Strong correlation
Below 0.7 = Warning: pair may not be reliable
ADF P-Value (should be < 0.05): Tests if the relationship is stable
Low value = Good for pair trading
High value = Relationship may be random
Cointegration: Confirms long-term equilibrium relationship
YES = Pair tends to revert to mean
NO = Pair may drift apart permanently
Visual Elements Explained
Chart Zones (Color-Coded Areas)
Yellow Zone (-1.5 to +1.5)
Normal Zone: Relationship is stable
Action: Wait for better opportunities
Blue Zone (±1.5 to ±2.0)
Entry Zone: Deviation is significant
Action: Prepare for potential trades
Green/Red Zone (±2.0 to ±3.0)
Opportunity Zone: Strong deviation
Action: High-probability trade setups
Beyond ±3.0
Risk Limit: Extreme deviation
Action: Either maximum opportunity or structural break
Signal Arrows
Green Arrow Up (Buy A + Sell B):
Stock A is undervalued relative to B
Buy Stock A, Short Stock B
Red Arrow Down (Sell A + Buy B):
Stock A is overvalued relative to B
Sell Stock A, Buy Stock B
Settings Guide
Symbol Inputs
Pair Symbol (Symbol B): Choose the second stock to compare
Default: NSE:INFY (Infosys)
Example pairs: TCS/INFY, HDFCBANK/ICICIBANK, RELIANCE/ONGC
Z-Score Parameters
Long Z-Score Period (300): Historical context
Short Z-Score Period (100): Recent trend
Signal Period (20): Trading signals
Z-Score Threshold (2.0): Entry trigger level
Higher = Fewer but stronger signals
Lower = More frequent signals
Statistical Parameters
Correlation Period (240): How many bars to check correlation
Hurst Exponent Period (50): Measures mean-reversion tendency
Probability Lookback (100): Historical probability calculations
Trading Parameters
Entry Threshold (0.0): Minimum Z-score for entry
Risk Threshold (1.5): Warning level
Risk Limit (3.0): Maximum deviation to trade
How to Use (Step-by-Step)
Step 1: Choose Your Pair
Add the indicator to your chart (this becomes Stock A)
In settings, select Stock B (the comparison stock)
Choose stocks from the same sector for best results
Step 2: Verify Pair Quality
Check the Statistics Table (top-right corner):
✅ Correlation > 0.70 (Green = Good)
✅ ADF P-value < 0.05 (Green = Good)
✅ Cointegrated = YES (Green = Good)
If all three are green, the pair is suitable for trading!
Step 3: Wait for Signals
BUY SIGNAL (Green Arrow Up)
Z-Score crosses above -2.0
Action: Buy Stock A, Sell Stock B
Exit: When Z-Score returns to 0
SELL SIGNAL (Red Arrow Down)
Z-Score crosses below +2.0
Action: Sell Stock A, Buy Stock B
Exit: When Z-Score returns to 0
Step 4: Risk Management
Yellow Zone: Monitor only
Blue Zone: Prepare for entry
Green/Red Zone: Active trading zone
Beyond ±3.0: Maximum risk - use caution
⚠️ Important Warnings
Not All Pairs Work: Always check the statistics table first
Market Conditions Matter: Correlation can break during market stress
Use Stop Losses: Set stops at Z-Score ±3.5 or beyond
Position Sizing: Trade both legs with appropriate hedge ratios
Transaction Costs: Factor in brokerage and slippage for both stocks
Example Trade
Scenario: TCS vs INFOSYS
Correlation: 0.85 ✅
Z-Score: -2.3 (TCS is cheap vs INFY)
Action to be taken:
Buy 1lot of TCS Future
Sell 1lot of INFOSYS Future
Expected Outcome:
As Z-Score moves toward 0, TCS outperforms INFOSYS
Close both positions when Z-Score crosses 0
Profit from the convergence
Best Practices
Test Before Trading: Use paper trading first
Sector Focus: Choose pairs from the same industry
Monitor Statistics: Check correlation daily
Avoid News Events: Don't trade pairs during earnings/major news
Size Appropriately: Start small, scale with experience
Be Patient: Wait for high-quality setups (±2.0 or beyond)
What Makes This Indicator Unique?
Multi-timeframe Z-Score analysis: Three different perspectives
Statistical validation: Built-in correlation and cointegration tests
Visual risk zones: Easy-to-understand color-coded areas
Real-time statistics: Live pair quality monitoring
Beginner-friendly: Clear signals with educational zones
Technical Background
The indicator uses:
Engle-Granger Cointegration Test: Validates pair relationship
ADF (Augmented Dickey-Fuller) Test: Tests stationarity
Pearson Correlation: Measures linear relationship
Z-Score Normalization: Standardizes deviations
Log Returns: Handles price differences properly
Support & Community
For questions, suggestions, or to share your pair trading experiences:
Comment below the indicator
Share your successful pair combinations
Report any issues for quick fixes
Disclaimer
This indicator is for educational and informational purposes only. It does not constitute financial advice. Pair trading involves risk, including the risk of loss.
Always:
Do your own research
Understand the risks
Trade with money you can afford to lose
Consider consulting a financial advisor
📌 Quick Reference Card
Z-ScoreInterpretationAction-3.0 to -2.0A very cheap vs BStrong Buy A, Sell B-2.0 to -1.5A cheap vs BBuy A, Sell B-1.5 to +1.5Normal rangeHold/Wait+1.5 to +2.0A expensive vs BSell A, Buy B+2.0 to +3.0A very expensive vs BStrong Sell A, Buy B
Good Pair Statistics:
Correlation: > 0.70
ADF P-value: < 0.05
Cointegration: YES
Version: 1.0
Last Updated: 10th October 2025
Compatible: TradingView Pine Script v6
Happy Trading!
[blackcat] L2 Trend LinearityOVERVIEW
The L2 Trend Linearity indicator is a sophisticated market analysis tool designed to help traders identify and visualize market trend linearity by analyzing price action relative to dynamic support and resistance zones. This powerful Pine Script indicator utilizes the Arnaud Legoux Moving Average (ALMA) algorithm to calculate weighted price calculations and generate dynamic support/resistance zones that adapt to changing market conditions. By visualizing market zones through colored candles and histograms, the indicator provides clear visual cues about market momentum and potential trading opportunities. The script generates buy/sell signals based on zone crossovers, making it an invaluable tool for both technical analysis and automated trading strategies. Whether you're a day trader, swing trader, or algorithmic trader, this indicator can help you identify market regimes, support/resistance levels, and potential entry/exit points with greater precision.
FEATURES
Dynamic Support/Resistance Zones: Calculates dynamic support (bear market zone) and resistance (bull market zone) using weighted price calculations and ALMA smoothing
Visual Market Representation: Color-coded candles and histograms provide immediate visual feedback about market conditions
Smart Signal Generation: Automatic buy/sell signals generated from zone crossovers with clear visual indicators
Customizable Parameters: Four different ALMA smoothing parameters for various timeframes and trading styles
Multi-Timeframe Compatibility: Works across different timeframes from 1-minute to weekly charts
Real-time Analysis: Provides instant feedback on market momentum and trend direction
Clear Visual Cues: Green candles indicate bullish momentum, red candles indicate bearish momentum, and white candles indicate neutral conditions
Histogram Visualization: Blue histogram shows bear market zone (below support), aqua histogram shows bull market zone (above resistance)
Signal Labels: "B" labels mark buy signals (price crosses above resistance), "S" labels mark sell signals (price crosses below support)
Overlay Functionality: Works as an overlay indicator without cluttering the chart with unnecessary elements
Highly Customizable: All parameters can be adjusted to suit different trading strategies and market conditions
HOW TO USE
Add the Indicator to Your Chart
Open TradingView and navigate to your desired trading instrument
Click on "Indicators" in the top menu and select "New"
Search for "L2 Trend Linearity" or paste the Pine Script code
Click "Add to Chart" to apply the indicator
Configure the Parameters
ALMA Length Short: Set the short-term smoothing parameter (default: 3). Lower values provide more responsive signals but may generate more false signals
ALMA Length Medium: Set the medium-term smoothing parameter (default: 5). This provides a balance between responsiveness and stability
ALMA Length Long: Set the long-term smoothing parameter (default: 13). Higher values provide more stable signals but with less responsiveness
ALMA Length Very Long: Set the very long-term smoothing parameter (default: 21). This provides the most stable support/resistance levels
Understand the Visual Elements
Green Candles: Indicate bullish momentum when price is above the bear market zone (support)
Red Candles: Indicate bearish momentum when price is below the bull market zone (resistance)
White Candles: Indicate neutral market conditions when price is between support and resistance zones
Blue Histogram: Shows bear market zone when price is below support level
Aqua Histogram: Shows bull market zone when price is above resistance level
"B" Labels: Mark buy signals when price crosses above resistance
"S" Labels: Mark sell signals when price crosses below support
Identify Market Regimes
Bullish Regime: Price consistently above resistance zone with green candles and aqua histogram
Bearish Regime: Price consistently below support zone with red candles and blue histogram
Neutral Regime: Price oscillating between support and resistance zones with white candles
Generate Trading Signals
Buy Signals: Look for price crossing above the bull market zone (resistance) with confirmation from green candles
Sell Signals: Look for price crossing below the bear market zone (support) with confirmation from red candles
Confirmation: Always wait for confirmation from candle color changes before entering trades
Optimize for Different Timeframes
Scalping: Use shorter ALMA lengths (3-5) for 1-5 minute charts
Day Trading: Use medium ALMA lengths (5-13) for 15-60 minute charts
Swing Trading: Use longer ALMA lengths (13-21) for 1-4 hour charts
Position Trading: Use very long ALMA lengths (21+) for daily and weekly charts
LIMITATIONS
Whipsaw Markets: The indicator may generate false signals in choppy, sideways markets where price oscillates rapidly between support and resistance
Lagging Nature: Like all moving average-based indicators, there is inherent lag in the calculations, which may result in delayed signals
Not a Standalone Tool: This indicator should be used in conjunction with other technical analysis tools and risk management strategies
Market Structure Dependency: Performance may vary depending on market structure and volatility conditions
Parameter Sensitivity: Different markets may require different parameter settings for optimal performance
No Volume Integration: The indicator does not incorporate volume data, which could provide additional confirmation signals
Limited Backtesting: Pine Script limitations may restrict comprehensive backtesting capabilities
Not Suitable for All Instruments: May perform differently on stocks, forex, crypto, and futures markets
Requires Confirmation: Signals should always be confirmed with other indicators or price action analysis
Not Predictive: The indicator identifies current market conditions but does not predict future price movements
NOTES
ALMA Algorithm: The indicator uses the Arnaud Legoux Moving Average (ALMA) algorithm, which is known for its excellent smoothing capabilities and reduced lag compared to traditional moving averages
Weighted Price Calculations: The bear market zone uses (2low + close) / 3, while the bull market zone uses (high + 2close) / 3, providing more weight to recent price action
Dynamic Zones: The support and resistance zones are dynamic and adapt to changing market conditions, making them more responsive than static levels
Color Psychology: The color scheme follows traditional trading psychology - green for bullish, red for bearish, and white for neutral
Signal Timing: The signals are generated on the close of each bar, ensuring they are based on complete price action
Label Positioning: Buy signals appear below the bar (red "B" label), while sell signals appear above the bar (green "S" label)
Multiple Timeframes: The indicator can be applied to multiple timeframes simultaneously for comprehensive analysis
Risk Management: Always use proper risk management techniques when trading based on indicator signals
Market Context: Consider the overall market context and trend direction when interpreting signals
Confirmation: Look for confirmation from other indicators or price action patterns before entering trades
Practice: Test the indicator on historical data before using it in live trading
Customization: Feel free to experiment with different parameter combinations to find what works best for your trading style
THANKS
Special thanks to the TradingView community and the Pine Script developers for creating such a powerful and flexible platform for technical analysis. This indicator builds upon the foundation of the ALMA algorithm and various moving average techniques developed by technical analysis pioneers. The concept of dynamic support and resistance zones has been refined over decades of market analysis, and this script represents a modern implementation of these timeless principles. We acknowledge the contributions of all traders and developers who have contributed to the evolution of technical analysis and continue to push the boundaries of what's possible with algorithmic trading tools.
TOTAL3ES/ETH Mean ReversionTOTAL3ES/ETH Mean Reversion Indicator
Overview
The TOTAL3ES/ETH Mean Reversion indicator is a specialized tool designed exclusively for analyzing the ratio between TOTAL3 excluding stablecoins (TOTAL3ES) and Ethereum's market capitalization. This ratio provides crucial insights into the relative performance and valuation cycles between altcoins and ETH, making it an essential tool for cryptocurrency portfolio allocation and market timing decisions.
What This Indicator Measures
This indicator tracks the market cap ratio of all altcoins (excluding ETH and stablecoins) to Ethereum's market cap. When the ratio is:
Above 1.0 (Parity): Altcoins have a larger combined market cap than ETH
Below 1.0 (Parity): ETH's market cap exceeds the combined altcoin market cap
Key Features
Historical Context
Historical Range: 0.64 (July 2017 low) to 3.49 (all-time high)
Midpoint: 2.065 - the mathematical center of the historical range
Parity Line: 1.0 - the psychological level where altcoins = ETH market cap
Mean Reversion Zones
The indicator identifies extreme valuation zones based on historical data:
Upper Extreme Zone (~2.92 at 80% threshold): Suggests altcoins may be overvalued relative to ETH
Lower Extreme Zone (~1.21 at 80% threshold): Suggests altcoins may be undervalued relative to ETH
Visual Elements
Color-coded zones: Red shading for bearish reversion areas, green for bullish reversion areas
Multiple reference lines: Parity, midpoint, and historical extremes
Information table: Real-time metrics including current ratio, range position, and reversion pressure
Customizable display: Toggle zones, lines, and adjust transparency
How to Use This Indicator
Market Cycle Analysis
Extreme High Zone (Red): When ratio enters this zone, consider potential ETH outperformance
Extreme Low Zone (Green): When ratio enters this zone, consider potential altcoin season
Parity Crossovers: Monitor when ratio crosses above/below 1.0 for sentiment shifts
Portfolio Allocation Signals
High Ratio Values: May indicate overextended altcoin valuations relative to ETH
Low Ratio Values: May suggest undervalued altcoins relative to ETH
Midpoint Reversions: Historical tendency to revert toward the 2.065 midpoint
Alert Conditions
The indicator includes built-in alerts for:
Entering extreme high/low zones
Parity crossovers (above/below 1.0)
Mean reversion signals
Input Parameters
Display Settings
Show Reversion Zones: Toggle colored extreme zones on/off
Show Midpoint: Display the historical midpoint line
Show Parity Line: Show the 1.0 parity reference line
Zone Transparency: Adjust shaded area opacity (70-95%)
Calculation Settings
Reversion Strength Period: Moving average period for reversion calculations (10-50)
Extreme Threshold: Percentage of historical range defining extreme zones (0.5-1.0)
Information Table Metrics
The bottom-right table displays:
Current Ratio: Live TOTAL3ES/ETH value
Range Position: Current position within historical range (%)
From Parity: Distance from 1.0 parity level (%)
Reversion Pressure: Intensity of mean reversion forces (%)
Zone: Current market zone classification
Historical Range: Reference boundaries (0.64 - 3.49)
Midpoint: Historical center value
Important Notes
Chart Compatibility
Exclusively designed for CRYPTOCAP:TOTAL3ES/CRYPTOCAP:ETH
Built-in validation ensures proper chart usage
Will display error message if applied to incorrect charts
Trading Considerations
This is an analytical tool, not trading advice
Mean reversion is a tendency, not a guarantee
Consider multiple timeframes and confirmations
Factor in overall market conditions and trends
Risk Disclaimer
Past performance does not guarantee future results. Cryptocurrency markets are highly volatile and unpredictable. Always conduct your own research and consider your risk tolerance before making investment decisions.
Ideal Use Cases
Portfolio rebalancing between ETH and altcoins
Market cycle timing for position adjustments
Sentiment analysis of crypto market phases
Long-term allocation strategies based on historical patterns
Risk management through extreme zone identification
This indicator serves as a quantitative framework for understanding the cyclical relationship between Ethereum and the broader altcoin market, helping traders and investors make more informed allocation decisions based on historical valuation patterns.ons
- Factor in overall market conditions and trends
### Risk Disclaimer
Past performance does not guarantee future results. Cryptocurrency markets are highly volatile and unpredictable. Always conduct your own research and consider your risk tolerance before making investment decisions.
New York Midnight Indicator█ OVERVIEW
This script provides a visual tool for traders to track the New York Midnight (NY Midnight), a significant time marker for those who rely on New York’s financial markets. The script calculates the exact moment of midnight in New York and places a vertical line on the chart at this time, helping traders identify when a new trading day begins according to the New York time zone. The indicator also marks the midnight point with a lime-colored downward triangle to enhance visibility on the chart. It is specifically useful for traders who want to synchronize their strategies with New York’s trading hours, especially in global markets.
The script is flexible, allowing traders to adjust the UTC offset to accommodate different time zones. This is critical for those trading in different regions but still using New York as the main time reference.
█ CONCEPTS
New York Midnight: For many traders, especially those following the Forex and US stock markets, midnight in New York signifies the start of a new trading day. This point is essential for technical analysis as it often aligns with daily opening ranges, trend shifts, and volume spikes.
UTC Offset: The script includes a user-input parameter (utcOffset) to adjust the calculated time for New York midnight, ensuring that it accounts for time zone differences. This allows it to be used effectively regardless of the user’s local time zone, offering flexibility to global traders.
█ METHODOLOGY
UTC Offset Adjustment: The script starts by asking the trader to input their UTC offset (e.g., UTC -5 for New York without daylight saving time). This offset is added to the current chart time to align it with New York’s local time.
Current Hour Calculation: Once the UTC offset is applied, the script calculates the New York Hour by taking the chart’s current hour and adjusting it with the offset. This ensures that the displayed hour matches New York’s local time, regardless of the trader's location.
Vertical Line at Midnight: When the current New York hour equals 00:00 (midnight), the script plots a black vertical line on the chart. This line serves as a visual reference for the exact moment when New York's trading day begins, allowing traders to align their strategies accordingly.
Downward Triangle Plot: In addition to the vertical line, the script also adds a lime-colored downward triangle at the same bar location to further highlight the midnight point. This is useful for traders who prefer shape markers to visualize significant time events.
█ HOW TO USE
Identifying Daily Resets: The script makes it easy for traders to track when New York’s trading day resets. This is especially useful in Forex markets, where daily cycles and time zone-based volatility play an important role in price movement and volume spikes.
Time Zone Flexibility: By adjusting the UTC offset parameter, traders across the globe can synchronize their charts with New York time. This is critical for international traders who want to execute trades based on New York market patterns but reside in different time zones.
Strategic Time Marking: The vertical line and shape markers at midnight allow traders to quickly see when a new trading day starts, helping them identify patterns like the daily range, key support/resistance levels, or even potential reversals around this time.
Session-Based Analysis: Traders who work with session-based strategies (e.g., trading the Asian, European, or US sessions) can use this marker to better time their entries or exits relative to the start of the New York session.
█ METHOD VARIANTS
This script can be modified or extended in various ways to better suit specific trading strategies:
Highlighting Other Session Starts: It could be adapted to plot lines for other key session starts (e.g., London open, Tokyo open).
Multiple Time Zones: For traders who monitor several markets, the script could be extended to display midnight markers for multiple time zones.
Custom Line Styles: Users could modify the line color, thickness, or style to better match their chart aesthetic or preferences.
Wave Consolidation [LuxAlgo]The Wave Consolidation indicator uses market profiles to highlight consolidation zones based on upward and downward moves determined when a Higher-High or Lower-Low is created.
Users can control the amount of consolidation zones to display and the sensitivity of the swing point detection used to return those zones.
🔶 USAGE
These zones are intended as areas of interest to traders where price has seen historical interactions, which can be interpreted as support and resistance. By identifying these areas of interest before the price returns to them, traders are able to anticipate and prepare for various scenarios and respond dynamically to the behavior of the market, as seen below.
Rejection: A quick move away from the zone may indicate that the area is either overvalued or undervalued, leading to a fast movement in the opposite direction.
Breakthrough: Moving beyond a zone could indicate acceptance at that specific price, potentially signaling a shift in momentum or the start of a new trend. In a strong major trend, zones created from smaller trends could be used as price targets for taking profit and managing risk.
Consolidation: Holding these zones might suggest a market in balance at these levels, this could lead to opportunities for range-bound trading.
Below is an example of the Rejection and Consolidation scenarios described above.
Note: By analyzing the tests and retests of these zones, traders can also gain further insight into where participants are interacting in the market.
🔶 DETAILS
The full process for acquiring and managing these zones is described in the sub-sections below.
🔹 Creation
By only considering market movements creating a higher-high or lower-low, we can identify meaningful, directional, moves which can then be used to calculate zones.
Once a move is identified, the script calculates a volume profile spanning the length of the given move.
The width of the zones is determined starting from the POC of the profile and expanding outwards until the value of the profile's row falls below the profile's average.
Note: By increasing the "Multiplier" Input, Users can increase the threshold the script uses to determine zone width in multiples of Standard Deviations above the Average.
While this area is similar to a VP Value Area, it is not intended to replicate a value zone. The calculation is not concerned with capturing any % of the total profile's volume within the zone and only analyzes based on a fixed inclusion threshold.
🔹 Management
To keep clutter to a minimum, If a new zone overlaps a recently created zone, the zones are grouped as one. This is especially helpful in areas where prices are ranging, creating multiple zones in a very similar area.
Zones before management:
Zones after management:
🔹 Deletion
Just because a zone is crossed, does not make it immediately unimportant!
Once a Zone is mitigated (crossed in the opposite direction of its bias) it is reduced to a single dotted line representing the outer threshold for the zone. These lines are important to watch, as the price will often retest a break. For this reason, they will stay on the chart until the next swing point is detected when they will finally be deleted for good.
Below is an example of activity around a broken zone before it is deleted.
Below is the same example 2bBars later , once the new swing is confirmed, the dotted lines are deleted and new zones are created.
Notice how the newly formed resistance zone is in the same area where we noticed sellers previously.
🔶 SETTINGS
🔹 Structure
Display Structure: Determines if swing structures are displayed.
Structure Length: Sets Length for structure identification.
🔹 Zones
Volume-Based Calculations: Opt to use a "Volume" based Profile Calculation instead of the default "Price Action" based Calculation.
Display Count: Sets the specific number of bullish and bearish zones to display on the chart.
Multiplier: Sets the multiplier to use for the value cut-off for determining zone boundaries.
🔹 Style
Display Average Lines: Toggles on/off the average (mid) lines for the zones.
Grospector DCA V.4This is system for DCA with strategy and can trade on trend technique "CDC Action Zone".
We upgrade Grospector DCA V.3 by minimizing unnecessary components and it is not error price predictions.
This has 5 zone Extreme high , high , normal , low , Extreme low. You can dynamic set min - max percent every zone.
Extreme zone is derivative short and long which It change Extreme zone to Normal zone all position will be closed.
Every Zone is splitted 10 channel. and this strategy calculate contribution.
and now can predict price in future.
Idea : Everything has average in its life. For bitcoin use 4 years for halving. I think it will be interesting price.
Default : I set MA is 365*4 days and average it again with 365 days.
Input :
len: This input represents the length of the moving average.
strongLen: This input represents the length of the moving average used to calculate the strong buy and strong sell zone.
shortMulti: This input represents the multiplier * moveing average used to calculate the short zone.
strongSellMulti: This input represents the multiplier used to calculate the strong sell signal.
sellMulti: This input represents the multiplier * moveing average used to calculate the sell zone.
strongBuyMulti: This input represents the multiplier used to calculate the strong sell signal.
longMulti: This input represents the multiplier * moveing average used to calculate the long zone.
*Diff sellMulti and strongBuyMulti which is normal zone.
useDerivative: This input is a boolean flag that determines whether to use the derivative display zone. If set to true, the derivative display zone will be used, otherwise it will be hidden.
zoneSwitch: This input determines where to display the channel signals. A value of 1 will display the signals in all zones, a value of 2 will display the signals in the chart pane, a value of 3 will display the signals in the data window, and a value of 4 will hide the signals.
price: Defines the price source used for the indicator calculations. The user can select from various options, with the default being the closing price.
labelSwitch: Defines whether to display assistive text on the chart. The user can select a boolean value (true/false), with the default being true.
zoneSwitch: Defines which areas of the chart to display assistive zones. The user can select from four options: 1 = all, 2 = chart only, 3 = data only, 4 = none. The default value is 2.
predictFuturePrice: Defines whether to display predicted future prices on the chart. The user can select a boolean value (true/false), with the default being true.
DCA: Defines the dollar amount to use for dollar-cost averaging (DCA) trades. The user can input an integer value, with a default value of 5.
WaitingDCA: Defines the amount of time to wait before executing a DCA trade. The user can input a float value, with a default value of 0.
Invested: Defines the amount of money invested in the asset. The user can input an integer value, with a default value of 0.
strategySwitch: Defines whether to turn on the trading strategy. The user can select a boolean value (true/false), with the default being true.
seperateDayOfMonth: Defines a specific day of the month on which to execute trades. The user can input an integer value from 1-31, with the default being 28.
useReserve: Defines whether to use a reserve amount for trading. The user can select a boolean value (true/false), with the default being true.
useDerivative: Defines whether to use derivative data for the indicator calculations. The user can select a boolean value (true/false), with the default being true.
useHalving: Defines whether to use halving data for the indicator calculations. The user can select a boolean value (true/false), with the default being true.
extendHalfOfHalving: Defines the amount of time to extend the halving date. The user can input an integer value, with the default being 200.
Every Zone: It calculate percent from top to bottom which every zone will be splited 10 step.
To effectively make the DCA plan, I recommend adopting a comprehensive strategy that takes into consideration your mindset as the best indicator of the optimal approach. By leveraging your mindset, the task can be made more manageable and adaptable to any market
Dollar-cost averaging (DCA) is a suitable investment strategy for sound money and growth assets which It is Bitcoin, as it allows for consistent and disciplined investment over time, minimizing the impact of market volatility and potential risks associated with market timing
AI Momentum [YinYang]Overview:
AI Momentum is a kernel function based momentum Indicator. It uses Rational Quadratics to help smooth out the Moving Averages, this may give them a more accurate result. This Indicator has 2 main uses, first it displays ‘Zones’ that help you visualize the potential movement areas and when the price is out of bounds (Overvalued or Undervalued). Secondly it creates signals that display the momentum of the current trend.
The Zones are composed of the Highest Highs and Lowest lows turned into a Rational Quadratic over varying lengths. These create our Rational High and Low zones. There is however a second zone. The second zone is composed of the avg of the Inner High and Inner Low zones (yellow line) and the Rational Quadratic of the current Close. This helps to create a second zone that is within the High and Low bounds that may represent momentum changes within these zones. When the Rationalized Close crosses above the High and Low Zone Average it may signify a bullish momentum change and vice versa when it crosses below.
There are 3 different signals created to display momentum:
Bullish and Bearish Momentum. These signals display when there is current bullish or bearish momentum happening within the trend. When the momentum changes there will likely be a lull where there are neither Bullish or Bearish momentum signals. These signals may be useful to help visualize when the momentum has started and stopped for both the bulls and the bears. Bullish Momentum is calculated by checking if the Rational Quadratic Close > Rational Quadratic of the Highest OHLC4 smoothed over a VWMA. The Bearish Momentum is calculated by checking the opposite.
Overly Bullish and Bearish Momentum. These signals occur when the bar has Bullish or Bearish Momentum and also has an Rationalized RSI greater or less than a certain level. Bullish is >= 57 and Bearish is <= 43. There is also the option to ‘Factor Volume’ into these signals. This means, the Overly Bullish and Bearish Signals will only occur when the Rationalized Volume > VWMA Rationalized Volume as well as the previously mentioned factors above. This can be useful for removing ‘clutter’ as volume may dictate when these momentum changes will occur, but it can also remove some of the useful signals and you may miss the swing too if the volume just was low. Overly Bullish and Bearish Momentum may dictate when a momentum change will occur. Remember, they are OVERLY Bullish and Bearish, meaning there is a chance a correction may occur around these signals.
Bull and Bear Crosses. These signals occur when the Rationalized Close crosses the Gaussian Close that is 2 bars back. These signals may show when there is a strong change in momentum, but be careful as more often than not they’re predicting that the momentum may change in the opposite direction.
Tutorial:
As we can see in the example above, generally what happens is we get the regular Bullish or Bearish momentum, followed by the Rationalized Close crossing the Zone average and finally the Overly Bullish or Bearish signals. This is normally the order of operations but isn’t always how it happens as sometimes momentum changes don’t make it that far; also the Rationalized Close and Zone Average don’t follow any of the same math as the Signals which can result in differing appearances. The Bull and Bear Crosses are also quite sporadic in appearance and don’t generally follow any sort of order of operations. However, they may occur as a Predictor between Bullish and Bearish momentum, signifying the beginning of the momentum change.
The Bull and Bear crosses may be a Predictor of momentum change. They generally happen when there is no Bullish or Bearish momentum happening; and this helps to add strength to their prediction. When they occur during momentum (orange circle) there is a less likely chance that it will happen, and may instead signify the exact opposite; it may help predict a large spike in momentum in the direction of the Bullish or Bearish momentum. In the case of the orange circle, there is currently Bearish Momentum and therefore the Bull Cross may help predict a large momentum movement is about to occur in favor of the Bears.
We have disabled signals here to properly display and talk about the zones. As you can see, Rationalizing the Highest Highs and Lowest Lows over 2 different lengths creates inner and outer bounds that help to predict where parabolic movement and momentum may move to. Our Inner and Outer zones are great for seeing potential Support and Resistance locations.
The secondary zone, which can cross over and change from Green to Red is also a very important zone. Let's zoom in and talk about it specifically.
The Middle Zone Crosses may help deduce where parabolic movement and strong momentum changes may occur. Generally what may happen is when the cross occurs, you will see parabolic movement to the High / Low zones. This may be the Inner zone but can sometimes be the outer zone too. The hard part is sometimes it can be a Fakeout, like displayed with the Blue Circle. The Cross doesn’t mean it may move to the opposing side, sometimes it may just be predicting Parabolic movement in a general sense.
When we turn the Momentum Signals back on, we can see where the Fakeout occurred that it not only almost hit the Inner Low Zone but it also exhibited 2 Overly Bearish Signals. Remember, Overly bearish signals mean a momentum change in favor of the Bulls may occur soon and overly Bullish signals mean a momentum change in favor of the Bears may occur soon.
You may be wondering, well what does “may occur soon” mean and how do we tell?
The purpose of the momentum signals is not only to let you know when Momentum has occurred and when it is still prevalent. It also matters A LOT when it has STOPPED!
In this example above, we look at when the Overly Bullish and Bearish Momentum has STOPPED. As you can see, when the Overly Bullish or Bearish Momentum stopped may be a strong predictor of potential momentum change in the opposing direction.
We will conclude our Tutorial here, hopefully this Indicator has been helpful for showing you where momentum is occurring and help predict how far it may move. We have been dabbling with and are planning on releasing a Strategy based on this Indicator shortly.
Settings:
1. Momentum:
Show Signals: Sometimes it can be difficult to visualize the zones with signals enabled.
Factor Volume: Factor Volume only applies to Overly Bullish and Bearish Signals. It's when the Volume is > VWMA Volume over the Smoothing Length.
Zone Inside Length: The Zone Inside is the Inner zone of the High and Low. This is the length used to create it.
Zone Outside Length: The Zone Outside is the Outer zone of the High and Low. This is the length used to create it.
Smoothing length: Smoothing length is the length used to smooth out our Bullish and Bearish signals, along with our Overly Bullish and Overly Bearish Signals.
2. Kernel Settings:
Lookback Window: The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars. Recommended range: 3-50.
Relative Weighting: Relative weighting of time frames. As this value approaches zero, the longer time frames will exert more influence on the estimation. As this value approaches infinity, the behavior of the Rational Quadratic Kernel will become identical to the Gaussian kernel. Recommended range: 0.25-25.
Start Regression at Bar: Bar index on which to start regression. The first bars of a chart are often highly volatile, and omission of these initial bars often leads to a better overall fit. Recommended range: 5-25.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
YinYang Bar ForecastOverview:
YinYang Bar Forecast is a prediction indicator. It predicts the movement for High, Low, Open and Close for up to 13 bars into the future. We created this Indicator as we felt the TradingView community could benefit from a bar forecast as there wasn’t any currently available.
Our YinYang Bar Forecast is something we plan on continuously working on to better improve it, but at its current state it is still very useful and decently accurate. It features many calculations to derive what it thinks the future bars will hold. Let’s discuss some of the logic behind it:
Each bar has its High, Low, Open and Close calculated individually for highest accuracy. Within these calculations we first check which bar it is we are calculating and base our span back length that we are getting our data from based on the bar index we are generating. This helps us get a Moving Average for this bar index.
We take this MA and we apply our Custom Volume Filter calculation on it, which is essentially us dividing the current bars volume over the average volume in the last ‘Filtered Length’ (Setting) length. We take this decimal and multiply it on our MA and smooth it out with a VWMA.
We take the new Volume Filtered MA and apply a RSI Filter calculation on it. RSI Filter is where we take the difference between the high and low of this bar and we multiply it with an RSI calculation using our Volume Filtered MA. We take the result of that multiplication and either add or subtract it from the Volume Filtered MA based on if close > open. This makes our RSI Filtered MA.
Next, we do an EMA Strength Calculation which is where we check if close > ema(close, ‘EMA Averaged Length’) (Setting). Based on this condition we assign a multiplier that is applied to our RSI Filtered MA. We divide by how many bars we are predicting and add a bit to each predictive bar so that the further we go into the future the stronger the strength is.
Next we check RSI and RSI MA levels and apply multiplications based on its RSI levels and if it is greater than or less than the MA. Also it is affected by if the RSI is <= 30 and >= 70.
Finally we check the MFI and MFI MA levels and like RSI we apply multiplications based on its MFI levels and if it is greater than or less than the MA. It is also affected by if the MFI is <= 30 and >= 70.
Please note the way we calculate this may change in the future, this is just currently what we deemed works best for forecasting the future bars. Also note this script uses MA calculations out of scope for efficiency but there is potential for inconsistencies.
Innately it’s main use is the projection it provides. It only draws the bars for realtime bars and not historical ones, so the best way to backtest it is with TradingView’s Replay Tool.
Well, enough of the logic behind it, let's get to understanding how to use it:
Tutorial:
So unfortunately we aren’t able to plot legit bars/candles into the future so we’ve had to do a bit of a work around using lines and fills. As you can see here we have 4 Lines and 3 Zones:
Lines:
Green: Represents the High
Orange: Represents the Open
Teal: Represents the Close
Red: Represents the Low
Zones:
High Zone: This zone is from either Open or Close to the High and is ALWAYS filled with Green.
Open/Close Zone: This zone is from the Open to the Close and is filled with either Green or Red based on if it's greater than the previous bar (real or forecasted).
Low Zone: This zone is from either Open or Close to the Low and is ALWAYS filled with Red.
As you can see generally the Forecasted bars are generally within strong pivot locations and are a good estimation of what will likely go on. Please note, the WHOLE structure of the prediction can change based on the current bars movements and the way it affects the calculations.
Let's look 1 bar back from the current bar just so we can see what it used to Forecast:
As you can see it has changed quite a bit from the previous bar, but if you look close, we drew horizontal lines around where its projecting the next bar to be (our current realtime bar), if we go back to the live chart:
Its projections were pretty close for the high and low. Generally, right now at least, it does a much better job at predicting the high and low than it does the open and close, however we will do our best to fine tune that in future updates.
Remember, this indicator is not meant to base your trades on, but rather give you a Forecast towards the general direction of the next few bars. Somewhat like weather, the farther the bar (or day for weather), the harder it is to predict. For this reason we recommend you focusing on the first few bars as they are more accurate, but review the further ones as they may help show the trend and the way that pair will move.
We will conclude this tutorial here, hopefully this Predictive Indicator can be of some help and use to you. If you have any questions, comments, ideas or concerns please let us know.
Settings:
Forecast Length: How many bars should we predict into the Future? Max 13
Each Bar Length Multiplier: For each new Forecast bar, how many more bars are averaged? Min 2
VWMA Averaged Length: All Forecast bars are put into a VWMA, what length should we use?
EMA Averaged Length: All Forecast bars are put into a EMA, what length should we use?
Filtered Length: What length should we use for Filtered Volume and RSI?
EMA Strength Length: What length should we use for the EMA Strength
HAPPY TRADING!
Multicolor Bollinger Bands - Market PhasesHi everyone
Hope you're all doing well 😘
Today I feel gracious and decided to give to the community. And giving not only an indicator but also a trading method
This trading method shows how a convergence based on moving averages is tremendous
Multicolour Bollinger Bands indicator that indicates market phases.
It plots on the price chart, thanks to different color zones between the bands, a breakdown of the different phases that the price operates during a trend.
The different zones are identified as follows:
- red color zone: trend is bearish, price is below the 200 periods moving average
- orange color zone: price operate a technical rebound below the 200 periods moving average
- yellow color zone: (phase 1 which indicate a new bearish cycle)
- light green zone: (phase 2 which indicate a new bullish cycle)
- dark green zone: trend is bullish, price is above the 200 periods moving average
- grey color zone: calm phase of price
- dark blue color zone: price is consolidating in either bullish or bearish trend
- light blue zones: price will revert to a new opposite trend (either long or short new trend)
By identifying clearly the different market phases with the multicolor Bollinger bands, the market entries by either a the beginning of a new trend or just after a rebound or a consolidating phase is easier to spot on.
Trade well and trade safe
Dave
Scalp Precision Matrix [BullByte]SCALP PRECISION MATRIX (SPM)
OVERVIEW
Scalp Precision Matrix (SPM) is a comprehensive decision-support framework designed specifically for scalpers and short-term traders. This indicator synthesizes five distinct analytical layers into a unified system that helps identify high-quality setups while avoiding common pitfalls that trap traders.
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THE CORE PROBLEM THIS INDICATOR ADDRESSES
Scalping demands rapid decision-making while simultaneously processing multiple data points. Traders constantly ask themselves: Is momentum still alive? Am I entering near a potential reversal zone? Is this the right session to trade? What is my actual risk-to-reward? Most traders either overwhelm themselves with too many separate indicators (creating analysis paralysis) or use too few (missing crucial context).
SPM was developed to consolidate these essential checks into one cohesive framework. Rather than overlaying disconnected indicators, each component in SPM directly informs and adjusts the others, creating an integrated analytical system.
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WHY THESE SPECIFIC COMPONENTS AND HOW THEY WORK TOGETHER
The five analytical layers in SPM are not arbitrarily combined. Each addresses a specific question in the scalping decision process, and together they form a logical workflow:
LAYER 1: MOMENTUM FUEL GAUGE
This answers the question: "Does the current move still have energy?"
After any impulse move (a significant directional price movement), momentum naturally decays over time. The Fuel Gauge estimates remaining momentum by analyzing four factors:
Body Strength (30% weight): Compares recent candle body sizes against the historical average. Strong momentum produces candles with large bodies relative to their wicks. The calculation takes the 3-bar average body size divided by the 20-bar average body size, then scales it to a 0-100 range.
Wick Rejection (25% weight): Measures the wick-to-body ratio. When wicks are large relative to bodies, it suggests rejection and weakening momentum. A ratio of 2.0 or higher (wicks twice the body size) scores low; smaller ratios score higher.
Volume Consistency (20% weight): Compares recent 3-bar average volume against the lookback period average. Sustained moves require consistent volume support. Volume dropping off suggests the move may be losing participation.
Time Decay (25% weight): Tracks how many bars have passed since the last detected impulse. Momentum naturally fades over time. The typical impulse duration is adjusted based on the current volatility regime.
These components are weighted and combined, then smoothed with a 3-period EMA to reduce noise. The result is a 0-100% gauge where:
- Above 70% = Strong momentum (green)
- 40-70% = Moderate momentum (amber)
- Below 40% = Weak momentum (red)
- Below 20% = Exhausted (triggers EXIT warning)
The Fuel Gauge also estimates how many bars of momentum remain based on the current burn rate.
IMPORTANT DISCLAIMER : The Fuel Gauge is NOT order flow, volume profile, or depth of market data. It is a technical proxy calculated entirely from standard OHLCV (Open, High, Low, Close, Volume) data. The term "Fuel" is used metaphorically to represent estimated remaining momentum energy.
LAYER 2: TRAP ZONE DETECTION
This answers the question: "Am I walking into a potential reversal area?"
Price tends to reverse at levels where it has reversed before. SPM identifies these zones by detecting clusters of historical swing points:
How it works:
1. The indicator detects swing highs and swing lows using the Swing Detection Length setting (default 5 bars on each side required to confirm a pivot).
2. Recent swing points are stored (up to 10 of each type).
3. For each potential zone, the algorithm counts how many swing points cluster within a tolerance of 0.5 ATR.
4. Zones with 2 or more clustered swing points, positioned between 0.3 and 4.0 ATR from current price, are marked as Trap Zones.
5. A Confluence Score is calculated based on cluster density and proximity to current price.
The percentage displayed (e.g., "TRAP 85%") is a CONFLUENCE SCORE, not a probability. Higher percentages mean more swing points cluster at that level and price is closer to it. This indicates stronger historical significance, not a prediction of future reversal.
CRITICAL DISCLAIMER : Trap Zones are NOT institutional order flow, liquidity pools, smart money footprints, or any proprietary data feed. They are calculated purely from historical swing point clustering using standard technical analysis. The term "trap" describes how price action has historically reversed at these levels, potentially trapping traders who enter prematurely. This is pattern recognition, not market structure data.
LAYER 3: VELOCITY ANALYSIS
This answers the question: "Is price moving favorably right now?"
Velocity measures how fast price is currently moving compared to its recent average:
Calculation:
- Current velocity = Absolute price change from previous bar divided by ATR
- Average velocity = Simple moving average of velocity over the lookback period
- Velocity ratio = Current velocity divided by average velocity
Classification:
- FAST (ratio above 1.5 ): Price is moving significantly faster than normal. Good for momentum continuation plays.
- NORMAL (ratio 0.5 to 1.5) : Typical price movement speed.
- SLOW (ratio below 0.5 ): Price is moving sluggishly. Often indicates ranging or choppy conditions where scalping becomes difficult.
The velocity score contributes 18% to the overall quality score calculation.
LAYER 4: SESSION AWARENESS
This answers the question: "Is this a good time to trade?"
Different trading sessions have different characteristics. SPM automatically detects which major session is active and adjusts its quality assessment:
Session Times (all in UTC):
- A sia Session : 00:00 - 08:00 UTC
- London Session : 08:00 - 16:00 UTC
- New York Session : 13:00 - 21:00 UTC
- London/NY Overlap : 13:00 - 16:00 UTC
- Off-Peak : Outside major sessions
Session Quality Weighting:
- Overlap : 100 points (highest liquidity, best movement)
- London : 85 points
- New York : 80 points
- Asia : 50 points (tends to range more)
- Off-Peak : 30 points (lower liquidity, more false signals)
The session score contributes 17% to the overall quality calculation. Signals are also filtered to prevent firing during off-peak hours.
Note : These are fixed UTC times and may not perfectly match your broker's session boundaries. Use them as general guidance rather than precise timing.
LAYER 5: VOLATILITY REGIME ADAPTATION
This answers the question: "How should I adjust for current market conditions?"
SPM compares current volatility (14-period ATR) against historical volatility (50-period ATR) to categorize the market:
HIGH Volatility (ratio above 1.3): Current ATR is 30%+ above normal. SPM widens thresholds to filter noise and extends target projections.
NORMAL Volatility (ratio 0.7 to 1.3): Typical conditions. Standard parameters apply.
LOW Volatility (ratio below 0.7): Current ATR is 30%+ below normal. SPM tightens thresholds for sensitivity and reduces target expectations. The market state may show AVOID during prolonged low volatility.
This adaptation prevents false signals during erratic markets and missed signals during quiet markets.
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THE SYNERGY: WHY THIS COMBINATION MATTERS
These five layers are not independent indicators placed on one chart. They form an interconnected system:
- A signal only fires when momentum exists (Fuel above 40%), price is away from danger zones (Trap Zones factored into quality score), movement is favorable (Velocity contributes to score), timing is appropriate (Session is not off-peak), and volatility is accounted for (thresholds adapt to regime).
- The Trap Zones directly influence Entry Zone placement. Entry zones are positioned beyond trap zones to avoid getting caught in reversals.
- Target projections automatically adjust to avoid placing take-profit levels inside detected trap zones.
- The Fuel Gauge affects which signal tier fires. Insufficient fuel prevents all signals.
- Session quality is weighted into the overall score, reducing signal quality during less favorable trading hours.
This integration is the core originality of SPM. Each component makes the others more useful than they would be in isolation.
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HOW THE QUALITY SCORE IS CALCULATED
The Quality Score (0-100) synthesizes all layers into a single number for each direction (long and short):
For Long Quality Score:
- Fuel Component (28% weight) : Full fuel value if impulse direction is bullish; 60% of fuel value otherwise
- Trap Avoidance (22% weight) : 75 points if no trap zone below; otherwise 100 minus the trap confluence score (minimum 20)
- Velocity Component (18% weight) : Direct velocity score
- Session Component (17% weight) : Current session quality score
- Trend Alignment (15% bonus) : Adds 12 points if price is above the 20-period SMA
For Short Quality Score:
- Same structure but reversed (bearish impulse direction, trap zone above, price below SMA)
The direction with the higher score becomes the current Bias. A 12-point difference is required to switch bias, preventing flip-flopping in neutral conditions.
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SIGNAL TYPES AND WHAT THEY MEAN
SPM generates four types of signals, each with specific visual representation:
PRIME SIGNALS (Cyan Diamond)
These represent the highest quality confluence. Requirements:
- Quality score crosses above the Prime threshold (default 80)
- Bias aligns with signal direction
- Fuel is sufficient (above 40%)
- Session is active (not off-peak)
- Cooldown period has passed
Prime signals appear as cyan-colored diamond shapes. Long signals appear below the bar; short signals appear above.
STANDARD SIGNALS (Green Triangle Up / Red Triangle Down)
These represent good quality setups. Requirements:
- Quality score crosses above the Standard threshold (default 75) but below Prime
- Same bias, fuel, and cooldown requirements as Prime
Standard signals appear as small triangles in green (long) or red (short).
CAUTION SIGNALS (Small Faded Circle)
These represent minimum threshold setups. Requirements:
- Quality score crosses above the Caution threshold (default 65) but below Standard
- Same additional requirements
Caution signals appear as small, faded circles. These suggest the setup exists but with weaker confluence. Consider these only when broader market context supports them, or skip them entirely during uncertain conditions.
EXHAUSTION SIGNAL (Purple X with "EXIT" text)
This warning appears when the Fuel Gauge drops below 20% from above, indicating momentum has depleted. This is not a trade signal but a warning to:
- Consider exiting existing positions
- Avoid entering new trades in the current direction
- Wait for new momentum to develop
All signals use CONFIRMED bar data only (referencing the previous closed bar) to prevent repainting. Once a signal appears, it will never disappear or change position on historical bars.
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READING THE CHART ELEMENTS
TRAP ZONES (Red Dashed Box with "TRAP XX%" Label)
These mark price levels where multiple historical swing points cluster. The red dashed box shows the zone boundaries. The percentage is the confluence score indicating cluster strength and proximity.
How to use: When price approaches a trap zone, be cautious about entering in that direction. If your bias is LONG and there's a strong trap zone above, consider taking partial profits before price reaches it or adjusting your target below it.
ENTRY ZONES (Green Solid Box with "ENTRY" Label)
These show suggested entry areas based on the current bias direction. For LONG bias, the entry zone appears below the trap zone (buying the dip beyond support). For SHORT bias, it appears above the trap zone (selling the rally beyond resistance).
How to use: Rather than entering at current price, consider placing limit orders within the entry zone. This positions you beyond where typical trap reversals occur.
TARGET ZONES (Blue Dotted Box with "TARGET" Label)
These project potential take-profit areas based on ATR multiples, adjusted for:
- Current volatility regime (wider in high volatility, tighter in low)
- Impulse direction (larger targets when aligned with impulse)
- Nearby trap zones (targets adjust to avoid placing TP inside trap zones)
How to use: These are suggestions, not guarantees. Consider taking partial profits before the target or using trailing stops once price moves favorably.
STOP LEVEL (Orange Dashed Line with "STOP" Label)
This shows suggested stop-loss placement, calculated as 0.8 ATR beyond the trap zone (or 2.0 ATR from current price if no trap zone exists).
How to use: This provides a reference for risk calculation. The dashboard R:R ratio is calculated using this stop level.
Chart Example: Scalp Precision Matrix displays real-time market analysis through dynamic zones and quality scores. ENTRY/TARGET/STOP zones show potential price levels based on current market structure - they appear continuously as reference points, NOT as trade instructions. Actual trade signals (diamonds, triangles, circles) fire only when multiple conditions align: quality score thresholds are crossed, fuel gauge is sufficient, session is active, and cooldown period has passed. The zones help you understand market context; the signals tell you when to act.
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UNDERSTANDING THE DASHBOARD (Top Right Panel)
The main dashboard provides comprehensive market context:
Row 1 - Header:
- "SPM " : Indicator name
- Market State : Current overall condition
Market States Explained:
- PRIME : Excellent conditions. Quality score meets prime threshold, session is active. Best opportunities.
- READY : Good conditions. Quality score meets standard threshold. Solid setups available.
- WAIT : Mixed conditions. Some factors favorable, others not. Patience recommended.
- AVOID : Poor conditions. Off-peak session or very low volatility. High risk of false signals.
- EXIT : Fuel exhausted. Momentum depleted. Consider closing positions or waiting.
Row 2-3 - Quality Bars:
- " UP ########## " : Visual meter for long quality (each # = 10 points, . = empty)
- " DN ########## " : Visual meter for short quality
- The number on the right shows the exact quality score
Row 4 - Bias:
- Shows current directional lean: LONG, SHORT, or NEUTRAL
- Color-coded: Green for long, red for short, gray for neutral
Rows 5-7 (Full Mode Only) - Trade Levels:
- Entry : Suggested entry price for current bias direction
- Stop : Suggested stop-loss price
- Target : Projected take-profit price
Row 8 - Risk:Reward Ratio:
- Format : "1:X.X" where X.X is the reward multiple
- Color-coded : Green if 2:1 or better, amber if 1.5:1 to 2:1, red if below 1.5:1
Row 9 - Fuel:
- Shows percentage and estimated bars remaining in parentheses
- Example : "72% (8)" means 72% fuel with approximately 8 bars remaining
- Color-coded : Green above 70%, amber 40-70%, red below 40%
Row 10-11 (Full Mode Only) - Market Conditions:
- Vol : Current volatility regime (HIGH/NORMAL/LOW)
- Speed : Current velocity zone (FAST/NORMAL/SLOW)
Row 12 - Session:
- Shows active trading session
- Color-coded by session type
Row 13 (Full Mode Only) - Remaining:
- Time remaining in current session (hours and minutes)
Row 14 (Conditional) - Trap Warning:
- Appears when a significant trap zone exists in your bias direction
- Shows direction (ABOVE/BELOW) and confluence percentage
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UNDERSTANDING THE QUICK PANEL (Bottom Left)
The Quick Panel provides essential information at a glance without looking away from price action:
Row 1: Current Bias and Quality Score (large text for quick reading)
Row 2: Market State
Row 3: Fuel Percentage
Row 4: Estimated Bars Remaining
Row 5: Risk:Reward Ratio
Row 6: Current Session
Both panels can be repositioned using the settings, and each can be toggled on/off independently.
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SETTINGS EXPLAINED
CORE SETTINGS:
Analysis Lookback (Default: 20)
Number of bars used for statistical calculations including average volume and average body size. Higher values create smoother but slower-reacting analysis. Lower values are more responsive but may include more noise.
Swing Detection Length (Default: 5)
Bars required on each side to confirm a swing high or low. A setting of 5 means a swing high must have 5 lower highs on each side. Lower values detect more swings (more trap zones, more sensitivity). Higher values find only major pivots (fewer but more significant zones).
Impulse Sensitivity (Default: 1.5)
Multiplier for ATR when detecting impulse moves. Lower values (like 1.0) detect smaller price movements as impulses, refreshing the fuel gauge more frequently. Higher values (like 2.5) require larger moves, making impulse detection less frequent but more significant.
SIGNAL SETTINGS:
Prime/Standard/Caution Thresholds (Defaults: 80/75/65)
These control the quality score required for each signal tier. You can adjust these based on your preference:
- More conservative : Raise thresholds (e.g., 85/80/70) for fewer but higher-quality signals
- More aggressive : Lower thresholds (e.g., 75/70/60) for more signals with slightly lower quality
Signal Cooldown (Default: 8 bars)
Minimum bars between signals to prevent signal spam. After any signal fires, no new signals can appear until this many bars pass. Increase for fewer signals in choppy markets; decrease if you want faster signal refresh.
Show Prime/Standard/Caution/Exhaustion Signals
Toggle each signal type on or off based on your preference.
ZONE DISPLAY:
Show Trap Zones / Entry Zones / Target Zones / Stop Levels
Toggle each zone type on or off. Turning off zones you don't use reduces chart clutter.
Zone Transparency (Default: 88)
Controls how transparent zone boxes appear. Higher values (closer to 95) make zones barely visible; lower values (closer to 75) make them more prominent.
Zone History (Default: 25 bars)
How far back zone boxes extend on the chart. Purely visual preference.
BACKGROUND:
Background Mode (Options: Off, Subtle, Normal)
Controls whether and how intensely the chart background is colored. Subtle is barely noticeable; Normal is more visible; Off disables background coloring entirely.
Background Type (Options: Bias, Fuel)
- Bias : Colors background based on current directional lean (green for long, red for short)
- Fuel : Colors background based on momentum level (green for high fuel, amber for moderate, red for low)
DASHBOARD / QUICK PANEL:
Show Dashboard / Show Quick Panel
Toggle each panel on or off.
Compact Mode
When enabled, the main dashboard shows only essential rows (quality bars, bias, R:R, fuel, session) without entry/stop/target levels, volatility, velocity, or time remaining.
Position Settings
Choose where each panel appears on your chart from six options: Top Right, Top Left, Bottom Right, Bottom Left, Middle Right, Middle Left.
ALERTS:
Alert Prime Signals / Standard Signals / Fuel Exhaustion
Enable or disable TradingView alerts for each condition. When enabled, you can set up alerts in TradingView that will notify you when these conditions occur.
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RECOMMENDED TIMEFRAMES AND USAGE
OPTIMAL TIMEFRAMES:
- 1-minute to 5-minute : Best for active scalping with quick entries and exits
- 5-minute to 15-minute : Balanced scalping with slightly more confirmation
- 15-minute to 1-hour : Short-term swing entries, fewer but more significant signals
Zone visualizations only appear on intraday timeframes to prevent chart clutter on higher timeframes.
BEST PRACTICES:
1. Trade primarily during LONDON, NEW YORK, or OVERLAP sessions. The indicator weights these sessions higher for good reason - liquidity and movement are typically better.
2. Prioritize PRIME signals. These represent the highest confluence and have proven most reliable. Use STANDARD signals as secondary opportunities. Treat CAUTION signals with extra scrutiny.
3. Respect the Fuel Gauge. Avoid entering new positions when fuel is below 40%. When the EXIT signal appears, seriously consider closing or reducing positions.
4. Pay attention to TRAP warnings. When the dashboard shows a trap zone in your bias direction, be cautious about holding through that level.
5. Verify R:R before entry. The dashboard shows the risk-to-reward ratio. Ensure it meets your minimum requirements (many traders require at least 1.5:1 or 2:1).
6. When state shows AVOID or EXIT, step back. These conditions typically produce poor results.
7. Combine with your own analysis. SPM is a decision-support tool, not a standalone system. Use it alongside your understanding of market structure, news events, and overall context.
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PRACTICAL EXAMPLE
Scenario : You're watching a 5-minute chart during London session. A cyan diamond (Prime Long signal) appears below the bar.
Before entering, you check the dashboard:
- State shows "PRIME" - conditions are favorable
- Fuel shows "72% (8)" - plenty of momentum remaining (approximately 8 bars)
- R:R shows "1:2.3" - acceptable risk-to-reward ratio
- Session shows "LONDON" - active session with good liquidity
- No TRAP warning in dashboard - no immediate resistance cluster in your way
- Entry zone visible on chart at a lower price level
- Stop and Target zones clearly marked
With this confluence of factors, you have context for a more informed decision. The signal indicates quality, the fuel suggests momentum remains, the R:R is favorable, and no immediate trap threatens your trade.
However, you also notice the target zone sits just below where a trap zone would be if there were one. This is by design - SPM adjusts targets to avoid placing them inside reversal zones.
This multi-factor confirmation delivered in a single glance is what SPM provides.
Chart Example :This chart demonstrates how the Scalp Precision Matrix identifies key market transitions. After a strong bullish impulse (cyan PRIME signal at ~08:30), price reached a historical reversal cluster (TRAP ZONE at 92,300). The indicator detected momentum exhaustion (purple EXIT signal) as fuel dropped below 20%, warning traders to exit longs. Now showing a SHORT bias with entry/stop/target zones clearly marked. The 92% trap zone confluence indicates a strong cluster of previous swing highs where price historically reversed.
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DATA WINDOW VALUES
For detailed analysis and strategy development, SPM exports the following values to TradingView's Data Window (visible when you hover over the chart with the indicator selected):
- Long Quality Score (0-100)
- Short Quality Score (0-100)
- Fuel Gauge (0-100%)
- Risk:Reward Ratio
These values can be useful for understanding how the indicator behaves over time and for developing your own insights about when it works best for your trading style.
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NON-REPAINTING CONFIRMATION
All signals in SPM are generated using CONFIRMED bar data only. The signal logic references the previous closed bar's values ( and in Pine Script terms). This means:
- Signals appear at the OPEN of the new bar (after the previous bar closes)
- Signals will NEVER disappear once they appear
- Signals will NEVER change position on historical bars
- What you see in backtesting is what you would have seen in real-time
The dashboard and zones update in real-time to provide current market context, but the trading signals themselves are non-repainting.
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IMPORTANT DISCLAIMERS
TERMINOLOGY CLARIFICATION:
This indicator uses terms that might imply access to data it does not have. To be completely transparent:
- "Trap Zones" are calculated from historical swing point clustering. They are NOT institutional liquidity pools, order blocks, smart money footprints, or any form of order flow data. The term "trap" is metaphorical, describing how price has historically reversed at these levels.
- "Fuel Gauge" is a technical momentum proxy. It is NOT order flow, volume profile, depth of market, or bid/ask data. It estimates momentum remaining based entirely on standard OHLCV price and volume data.
- "Quality Scores" are weighted combinations of the technical factors described above. A high score indicates multiple conditions align favorably according to the indicator's logic. It does NOT predict or guarantee trade success.
- The percentages shown on trap zones are CONFLUENCE SCORES measuring cluster density and proximity. They are NOT probability predictions of reversal.
TRADING RISK WARNING:
Trading involves substantial risk of loss and is not suitable for all investors. This indicator is a technical analysis tool designed to assist with decision-making. It does not constitute financial advice, trading advice, or any other sort of advice. Past performance of any signal or pattern does not guarantee future results. Markets are inherently unpredictable.
Always use proper risk management. Define your risk before entering any trade. Never risk more than you can afford to lose. Consider consulting with a licensed financial advisor before making trading decisions.
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ORIGINALITY STATEMENT - NOT A MASHUP
Scalp Precision Matrix is an original work that combines several analytical concepts into a purpose-built scalping framework. While individual components like ATR calculations, pivot detection, session timing, and trend alignment exist in various forms elsewhere, the specific implementation here represents original synthesis:
- The Fuel Gauge decay model with its four-component weighted calculation
- The Trap Zone cluster detection with confluence scoring
- The multi-factor quality scoring system that integrates all layers
- The trap-aware entry and target zone placement logic
- The volatility regime adaptation across all components
- The session weighting is integrated into the quality assessment
The indicator does not simply overlay separate indicators on one chart. It creates interconnected layers where each component informs and adjusts the others. This integration is the core originality of SPM.
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For best results, combine SPM with your own market understanding and always practice proper risk management.
-BullByte
On Balance Volume [BrightSideTrading]
# On Balance Volume - Complete User Guide
## Overview
This enhanced OBV indicator provides clean, actionable volume analysis with intelligent signal filtering. It combines On-Balance Volume (OBV) with a smoothed signal line to identify shifts in buying and selling pressure without chart clutter.
**Key Features:**
- Real-time OBV and signal line visualization
- Smart crossover detection with confirmation filtering
- Z-Score momentum analysis
- Customizable signal alerts with V-shaped markers
- Window-normalized option for detrended analysis
---
## What is On-Balance Volume (OBV)?
OBV is a volume-based momentum indicator that accumulates volume on up days and subtracts volume on down days. It answers a fundamental question: **Is volume flowing in (buying) or out (selling)?**
**Formula:**
- If Close > Previous Close: OBV = Previous OBV + Volume
- If Close < Previous Close: OBV = Previous OBV - Volume
- If Close = Previous Close: OBV = Previous OBV (unchanged)
**What it tells you:**
- **Rising OBV** = Accumulation (smart money buying)
- **Falling OBV** = Distribution (smart money selling)
- **OBV above zero line** = Net positive buying pressure
- **OBV below zero line** = Net negative selling pressure
---
## Interface & Settings
### **MAIN VISUALIZATION**
**OBV Line (Green/Red Ribbon)**
- Green when OBV is above the signal line (bullish trend)
- Red when OBV is below the signal line (bearish trend)
- Toggles between window-normalized (detrended) and raw values
**Signal Line (Orange)**
- Smoothed average of OBV
- Crossovers with OBV generate buy/sell signals
- Default: 21-period SMA
**V-Shaped Markers**
- Green upward V = Bullish crossover (buy signal)
- Red downward V = Bearish crossover (sell signal)
- Appears at the OBV value when signal is triggered
**Zero Line (Yellow)**
- Center equilibrium point for volume balance
- Acts as support/resistance for OBV
- Separates buying pressure (above) from selling pressure (below)
---
### **SOURCE GROUP**
**Source**
- **Default:** Close
- **Options:** Open, High, Low, or any custom value
- Controls which price value triggers OBV direction changes
- Most traders use Close for standard OBV calculation
---
### **SIGNAL SMOOTHING GROUP**
**Show Signal?**
- **Default:** ON
- Toggle visibility of the signal line
- Disable if you prefer to see raw OBV only
**Smoothing Type**
- **SMA (Simple Moving Average)** - Default, standard smoothing
- **EMA (Exponential Moving Average)** - Faster response, weights recent bars more heavily
- **Choose SMA** for consistent, traditional OBV signals
- **Choose EMA** for faster trend identification (more whipsaws possible)
**Smoothing Length**
- **Default:** 21 bars
- **Range:** 1-200 bars
- **Lower values** (5-14): Faster signals, more noise
- **Higher values** (30-50): Slower signals, fewer false alarms
- **Recommendation:** Use 21-25 for most timeframes
---
### **SIGNAL FILTERING GROUP**
This is your primary control for signal quality and frequency.
**Show Signal Markers?**
- **Default:** ON
- Toggle the V-shaped buy/sell markers on/off
- Disable if markers distract from your analysis
**Signal Filter Type**
- **None** - Shows every single crossover (noisy, best for skilled traders)
- **Confirmation Bars** - Waits N bars before confirming signal (recommended)
- **Strength-Based** - Only signals during strong momentum (filters weakest moves)
#### **CONFIRMATION BARS MODE** (Recommended)
Best for reducing false signals while staying responsive to real moves.
**Confirmation Bars**
- **Default:** 2 bars
- **Range:** 1-10 bars
- Waits for the signal to hold for N consecutive bars after crossover
- **Setting 1:** Every crossover (same as "None")
- **Setting 2:** Wait 1 bar confirmation (good balance)
- **Setting 3:** Wait 2 bars confirmation (filters 50% of noise)
- **Setting 4+:** Very selective, misses quick reversals
**How it works:**
1. OBV crosses signal line → Confirmation counter starts
2. If OBV stays on correct side for 2 bars → V-marker appears
3. If OBV crosses back → Counter resets, no signal
#### **STRENGTH-BASED MODE**
Only signals when momentum is statistically significant.
**Min Z-Score Strength**
- **Default:** 0.3
- **Range:** 0.0-3.0
- Requires OBV deviation from its mean to reach this threshold
- **Setting 0.1-0.3:** More signals, lower quality
- **Setting 0.5-0.8:** Moderate signals, good quality
- **Setting 1.0+:** Only the strongest momentum shifts
**How it works:**
- Calculates how far OBV is from its 50-bar average (Z-score)
- Only shows signals when this distance is meaningful
- Automatically avoids weak, choppy market conditions
---
### **VISUALS & COLORS GROUP**
**Highlight Crossovers?**
- **Default:** ON
- Master toggle for all signal markers
- Turn OFF to see only the OBV/signal lines
**Apply Ribbon Filling?**
- **Default:** ON
- Colors the space between OBV and signal line
- Green fill = OBV above signal (bullish)
- Red fill = OBV below signal (bearish)
- Provides clear visual trend confirmation
- Turn OFF for minimal chart clutter
---
### **STATS & ZONES GROUP**
**Use Window-Normalized OBV (visual only)?**
- **Default:** ON
- Removes long-term trend from OBV for clearer short-term signals
- Detrends the indicator to highlight recent momentum changes
- **ON:** Better for swing trading and identifying reversals
- **OFF:** Better for trend-following strategies
- Note: Z-Score always uses raw OBV for statistical accuracy
**OBV Normalize Window**
- **Default:** 200 bars
- Lookback period for detrending calculation
- Larger values = more aggressive detrending
- Adjust if you want OBV to oscillate more/less around zero
**Show Z-Score (OBV)?**
- **Default:** ON
- Displays statistical momentum indicator below main chart
- Ranges from -3 to +3 (most data within -2 to +2)
- High Z-Score = Strong buying momentum
- Low Z-Score = Strong selling momentum
**Z-Score Lookback**
- **Default:** 50 bars
- Period for calculating Z-Score mean and standard deviation
- Larger = smoother Z-Score, slower response
- Smaller = noisier Z-Score, faster response
**Show ROC (OBV Momentum)?**
- **Default:** OFF
- Rate of Change indicator for OBV velocity
- Useful for identifying momentum turning points
- Enable if you want to see speed of volume changes
**ROC Lookback**
- **Default:** 14 bars
- Period for ROC calculation
**Show Z-Score StdDev Zones?**
- **Default:** ON
- Shaded regions around zero line showing statistical boundaries
- Inner Zone (±1 Z) = Normal variation
- Outer Zone (±2 Z) = Extreme moves, potential reversals
- Helps identify overbought/oversold volume conditions
**Inner Zone (±Z)**
- **Default:** 1.0
- First boundary for standard deviation zones
- Most normal trading occurs within ±1
**Outer Zone (±Z)**
- **Default:** 2.0
- Second boundary for extreme conditions
- Crossing these zones indicates significant momentum shift
---
## Trading Strategy Examples
### **Strategy 1: Signal Line Crossovers (Beginner)**
**Setup:**
- Signal Filter Type: **Confirmation Bars**
- Confirmation Bars: **2-3**
- Show Signal Markers: **ON**
**Rules:**
1. **BUY signal** (green V): When OBV crosses above signal line and holds for 2-3 bars
- Confirms buying pressure is building
- Look for price to follow within 1-3 bars
2. **SELL signal** (red V): When OBV crosses below signal line and holds for 2-3 bars
- Confirms selling pressure is increasing
- Expect price decline
3. **Exit:** Take profits at next signal or use price support/resistance
**Best For:** Swing trading, intraday reversals, timeframes 5m-1h
---
### **Strategy 2: Zero Line Bounce (Intermediate)**
**Setup:**
- Signal Filter Type: **Strength-Based**
- Min Z-Score Strength: **0.5**
- Show Z-Score StdDev Zones: **ON**
**Rules:**
1. **Watch OBV approach zero line** during established trends
- OBV bouncing repeatedly off zero = trend is healthy
- OBV breaking through zero = trend reversal imminent
2. **Enter on bounce:** Buy when OBV bounces from zero line in uptrend
3. **Exit on break:** Close position when OBV breaks below zero line
4. **Confirm with Z-Score:** Only take trades when Z-Score shows momentum (|Z| > 0.5)
**Best For:** Trend traders, identifying trend strength, medium timeframes 15m-4h
---
### **Strategy 3: Momentum Extremes (Advanced)**
**Setup:**
- Signal Filter Type: **None**
- Show Z-Score StdDev Zones: **ON**
- Outer Zone: **2.0**
**Rules:**
1. **Identify extremes:** When Z-Score breaks outer zone (±2.0)
- Indicator is in extreme territory
- Likely overextended
2. **Fade extremes:** Take opposite position when Z-Score hits extreme
- High Z (>2.0) = OBV overbought, expect pullback
- Low Z (<-2.0) = OBV oversold, expect bounce
3. **Confirm:** Wait for crossover signal to enter
4. **Target:** Outer zone of opposite side or zero line
**Best For:** Range trading, mean reversion, experienced traders only
---
## Reading the Indicator in Different Markets
### **Strong Uptrend**
- OBV consistently above signal line (green)
- OBV well above zero line, rising higher lows
- Z-Score positive, trending upward
- **Action:** Buy dips to signal line, sell at resistance
### **Strong Downtrend**
- OBV consistently below signal line (red)
- OBV well below zero line, making lower highs
- Z-Score negative, trending downward
- **Action:** Sell rallies to signal line, cover at support
### **Consolidation/Choppy Market**
- OBV whipsaws around signal line frequently
- Crossovers occur every few bars
- Z-Score oscillating between -1 and +1
- **Action:** Increase confirmation bars to 3-4, or switch to strength-based filter
### **Accumulation (Bottom Formation)**
- OBV rising while price is flat or falling
- Volume flowing in despite downtrend (bullish divergence)
- Z-Score climbing while price lows hold
- **Action:** Expect breakout up; prepare buy near support
### **Distribution (Top Formation)**
- OBV falling while price is flat or rising
- Volume flowing out despite uptrend (bearish divergence)
- Z-Score falling while price continues higher
- **Action:** Expect breakdown down; prepare short near resistance
---
## Parameter Tuning Guide
### **Aggressive Settings (More Signals)**
- Smoothing Length: 14
- Signal Filter: None or Confirmation Bars: 1
- Min Z-Score: 0.1
- Best for: Day trading, high volatility stocks
- Risk: More false signals
### **Balanced Settings (Recommended)**
- Smoothing Length: 21
- Signal Filter: Confirmation Bars: 2
- Min Z-Score: 0.3
- Best for: Swing trading, most market conditions
- Risk/Reward: Moderate
### **Conservative Settings (Fewer Signals)**
- Smoothing Length: 30-40
- Signal Filter: Confirmation Bars: 3-4 or Strength-Based: 0.7+
- Min Z-Score: 0.8
- Best for: Position trading, high-conviction trades only
- Risk: May miss some moves
---
## Common Questions & Troubleshooting
**Q: Why are there more sell signals than buy signals?**
A: This reflects the actual market action. Markets often decline faster than they rise (fear > greed). Confirm signals with price action and support/resistance.
**Q: The indicator keeps whipsawing, should I hide it?**
A: Increase Confirmation Bars to 3-4 or switch to Strength-Based filter. Market conditions matter—choppy markets require stricter filters.
**Q: What's the difference between normalized and raw OBV?**
A: Normalized (detrended) shows shorter-term momentum by removing long-term trends. Raw OBV shows absolute accumulation/distribution over the full period. Use normalized for swing signals, raw for trend confirmation.
**Q: My signals come too late. How do I get faster entry?**
A: Reduce Smoothing Length (try 14 instead of 21), use EMA instead of SMA, or set Confirmation Bars to 1. Trade-off: More false signals.
**Q: Can I use this for day trading?**
A: Yes, on 1m-5m charts with aggressive settings. Use Confirmation Bars: 1 and focus on Z-Score > 0.5 entries only.
**Q: Should I trade every signal?**
A: No. Filter signals using: price near support/resistance, multiple indicators confirming, and Z-Score showing momentum. Best signals occur at key levels.
---
## Best Practices
1. **Always confirm with price action:** OBV signals work best when price is near support, resistance, or moving average. Don't trade signals in a vacuum.
2. **Use volume context:** Check if volume is increasing or decreasing on the signal. Strong signals have volume confirmation (increasing volume on OBV spikes).
3. **Adjust settings per timeframe:**
- 1m-5m: Smoothing 12, Confirmation 1, Z-Score 0.2
- 15m-1h: Smoothing 20, Confirmation 2, Z-Score 0.3
- 4h-1d: Smoothing 25, Confirmation 3, Z-Score 0.5
4. **Watch the zero line:** It's your friend. OBV behavior at the zero line reveals trend strength. Bounces = healthy trend. Breaks = reversal.
5. **Risk management:** No indicator is perfect. Use proper position sizing and stop losses. OBV should confirm your thesis, not be the only reason to trade.
6. **Combine with other indicators:**
- Price moving averages for trend confirmation
- RSI or Stochastic for overbought/oversold levels
- Support/resistance for entry/exit zones
- MACD for momentum divergences
---
## Disclaimer
This indicator is for educational and informational purposes only. It is not financial advice. Past performance does not guarantee future results. Always conduct your own research and consult with a financial advisor before making trading decisions. Trading carries risk, including potential loss of principal.
---
## Version History
**Version 1.0** - Initial release with enhanced signal filtering, Z-Score analysis, and customizable parameters.
Elite S&D [By:CienF]Elite Supply & Demand
Description
Elite Supply & Demand is not just another zone indicator; it is a complete institutional trading system designed to identify high-probability imbalances in the market. Unlike standard indicators that flood the chart with weak zones, this script applies rigorous Price Action rules to filter, score, and validate only the most significant areas of interest.
The core philosophy of this tool is "Anormality". Institutional activity leaves a footprint in the form of explosive volatility relative to the recent context. This indicator detects these footprints, measures their intensity, and validates them against market structure.
Key Features
🔥 Dynamic Quality Scoring (The "Elite" Feature) The indicator doesn't just draw boxes; it rates them. It calculates a Volumetric Ratio comparing the explosive move against the historical average at the moment of creation.
Contextual Intelligence: It continues to track the initial move. If the momentum continues after a small pause, the score updates in real-time.
Visual Grades:
🔥 Fire: High Anormality (Institutional Imbalance).
⚡ Lightning: Moderate Anormality (Decent strength).
No Icon: Standard move.
🏗️ Advanced Structure Validation Includes a unique "Eventual Break" filter.
Latent Zones: You can choose to hide zones that haven't broken structure yet.
Auto-Validation: The zone remains invisible/transparent until price breaks a recent High/Low or Fractal Pivot. Once the break occurs, the zone "activates" on your chart.
🧠 Smart Mitigation Logic
No Zombie Zones: Once a zone is mitigated (touched), it is strictly processed. It can either turn gray (History Mode) or be removed instantly.
Priority Handling: Mitigated zones are never re-colored or re-validated, keeping your chart clean and accurate.
🚀 Performance Optimization
Date Lookback: Includes a "Days Back" filter to prevent the script from calculating thousands of historical candles, ensuring smooth performance even on lower timeframes (1m, 5m).
🔔 Integrated Alerts
Creation: Get notified immediately when a potential zone forms.
Validation: Get notified specifically when a latent zone breaks structure and becomes active.
How It Works ( The Logic)
Phase 1: The Base (Indecision): Identifies candles with small bodies (≤ 50% of range) representing equilibrium/accumulation.
Phase 2: The Explosion (Imbalance): Looks for a strong breakout candle (≥ 60% body) that moves away from the base.
Phase 3: The Follow-up: Verifies that the move continues. It allows for "Smart Pauses" (single indecision candles) within the trend but invalidates the zone if a reversal occurs immediately.
Phase 4: Structure Check: Verifies if the move broke the Recent Range (High/Low) or Fractal Pivots.
Settings & Configuration
1. Base & Exit Rules
Max % Body: Threshold to define an indecision candle (Default: 50%).
Explosive Min: Minimum strength required for the exit candle.
2. Structure Validation
Structure Type: Choose between Recent Range (more fluid) or Fractal Pivots (stricter).
Filter Eventual Break: Highly Recommended. If checked, zones appear only after they prove their strength by breaking structure.
3. Scoring (Quality)
High Quality Ratio: The multiplier required to earn the 🔥 icon (e.g., 2.0x larger than average).
Allow Pause: Allows the algorithm to capture larger moves even if there is a single small candle in the middle of the explosive leg.
4. Performance
Days Back: Limits how far back the indicator draws. Reduce this number on low timeframes to speed up loading.
Usage Recommendations
For Trend Trading: Look for "Follow-up" zones. If you see a 🔥 zone forming in the direction of the higher timeframe trend, it is a high-probability entry.
For Reversals: Use the "Filter Eventual Break" feature. Wait for the indicator to reveal a zone that has broken a major structure point.
Stop Loss Placement: The indicator draws the zone covering the entire "Base" (wicks included). A safe stop is typically just beyond the distal line (33% recommended) of the box.
🔔 How to Set Up Alerts
Since this indicator uses the dynamic alert() function to send detailed messages (Entry Price, Stop Zone, Type), you must configure it correctly:
Add the indicator to your chart and adjust the settings to your preference.
Click the "Create Alert" button (Clock Icon) on the right toolbar or press Alt + A.
Condition: Select "Elite S&D " from the dropdown menu.
Trigger (CRITICAL): You must select "Any alert() function call".
Note: Do not select "Crossing" or other standard conditions, or the alerts will not trigger.
Expiration: Select "Open-ended" (if you have a Premium plan) or set a future date.
Alert Actions: Choose where you want to receive the alert (Notify on App, Show Popup, Send Email, etc.).
Message: You can leave this default. The script automatically generates a detailed message with the Ticker, Timeframe, Zone Type, and Coordinates.
Click Create.
Disclaimer: This tool is designed to assist in technical analysis and does not constitute financial advice. Always use proper risk management.
Support Resistance with Order BlocksIndicator Description
Professional Price Level Detection for Smart Trading. Master the Markets with Precision Support/Resistance and Order Block Analysis . It provides traders with clear visual cues for potential reversal and breakout areas, combining both retail and institutional trading concepts into one powerful tool.
The Support & Resistance with Order Blocks indicator is a versatile Pine Script tool designed to empower traders with clear, actionable insights into key market levels. By combining advanced pivot-based support and resistance (S/R) detection with order block (OB) filtering, this indicator delivers clean, high-probability zones for entries, exits, and reversals. With customizable display options (boxes or lines) and intuitive settings, it’s perfect for traders of all styles—whether you’re scalping, swing trading, or investing long-term. Overlay it on your TradingView chart and elevate your trading strategy today!
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Key Features
✅ Dynamic Support/Resistance - Auto-adjusting levels based on price action
✅ Smart Order Block Detection - Identifies institutional buying/selling zones
✅ Dual Display Modes - Choose between Boxes or Clean Lines for different chart styles
✅ Customizable Sensitivity - Adjust detection parameters for different markets
✅ Broken Level Markers - Clearly shows when key levels are breached
✅ Timeframe-Adaptive - Automatically adjusts for daily/weekly charts
1. Dynamic Support & Resistance Detection
Identifies critical S/R zones using pivot high/low calculations with adjustable look back periods.
Visualizes active S/R zones with distinct colors and labels ("Support" or "Resistance" for boxes, lines for cleaner charts).
Marks broken S/R levels as "Br S" (broken support) or "Br R" (broken resistance) when historical display is enabled, aiding in breakout and reversal analysis.
2. Smart Order Block Identification
Detects bullish and bearish order blocks based on significant price movements (default: ±0.3% over 5 candles).
Highlights institutional buying/selling zones with customizable colors, displayed as boxes or lines.
Filters out overlapping OB zones to keep your chart clutter-free.
3. Dual Display Options
Boxes or Lines: Choose to display S/R and OB as boxes for detailed zones or lines for a minimalist view.
Line Width Customization: Adjust line widths for S/R and OB (1–5 pixels) for optimal visibility.
Color Customization: Tailor colors for active/broken S/R and bullish/bearish OB zones.
4. Advanced Overlap Filtering
Ensures S/R zones don’t overlap with OB zones or other S/R levels, providing only the most relevant levels.
Limits the number of active zones (default: 10) to maintain chart clarity.
5. Historical S/R Visualization
Optionally display broken S/R levels with distinct colors and labels ("Br S" or "Br R") to track historical price reactions.
Broken levels are dynamically updated and removed (or retained) based on user settings.
6. Timeframe Adaptability
Automatically adjusts pivot detection for daily/weekly timeframes (40-candle look back) versus shorter timeframes (20-candle look back).
Works seamlessly across all asset classes (stocks, forex, crypto, etc.) and timeframes.
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How It Works
• Support & Resistance:
Uses ta.pivothigh and ta.pivotlow to detect significant price pivots, with a user-defined look back (default: 5 candles post-pivot).
Plots S/R as boxes (with labels "Support" or "Resistance") or lines, extending to the current bar for real-time relevance.
Broken S/R levels are marked with adjusted colors and labels ("S" or "R" for boxes, "Br S" or "Br R" for lines when historical display is enabled).
• Order Blocks:
Identifies OB based on strong price movements over 4 candles, plotted as boxes or lines at the candle’s midpoint.
Validates OB to prevent overlap, ensuring only significant zones are displayed.
Removes OB zones when price breaks through, keeping the chart focused on active levels.
• Customization:
Toggle S/R and OB visibility, adjust detection sensitivity, and set maximum active zones (4–50).
Fine-tune line widths and colors for a personalized chart experience.
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Why Use This Indicator?
• Precision Trading: Pinpoint high-probability entry/exit zones with filtered S/R and OB levels.
• Clean Charts: Overlap filtering and zone limits reduce clutter, focusing on key levels.
• Versatile Display: Switch between boxes for detailed zones or lines for simplicity, with adjustable line widths.
• Institutional Edge: Leverage OB detection to align with institutional activity for smarter trades.
• User-Friendly: Intuitive settings and clear visuals make it accessible for beginners and pros alike.
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Settings Overview________________________________________
⚙ Input Parameters
Settings Overview
Display Options:
Display Type: Choose "Boxes" or "Lines" for S/R and OB visualization.
S/R Line Width: Set line thickness for S/R lines (1–5 pixels, default: 2).
OB Line Width: Set line thickness for OB lines (1–5 pixels, default: 2).
Order Block Options:
Show Order Block: Enable/disable OB display.
Bull/Bear OB Colors: Customise border and fill colors for bullish and bearish OB zones.
Support/Resistance Options:
Show S/R: Toggle active S/R zones.
Show Historical S/R: Display broken S/R levels, marked as "Br S" or "Br R" for lines.
Detection Period: Set candle lookback for pivot detection (4–50, default: 5).
Max Active Zones: Limit active S/R and OB zones (4–50, default: 10).
Colors: Customise active and broken S/R colors for clear differentiation.
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How to Use
1. Add to Chart: Apply the indicator to your TradingView chart.
2. Customize Settings:
o Select "Boxes" or "Lines" for your preferred display style.
o Adjust line widths, colors, and detection parameters to suit your trading style.
o Enable "Show Historical S/R" to track broken levels with "Br S" and "Br R" labels.
3. Analyze Levels:
o Use support zones (green) for buy entries and resistance zones (red) for sell entries.
o Monitor OB zones for institutional activity, signaling potential reversals or continuations.
o Watch for "Br S" or "Br R" labels to identify breakout opportunities.
4. Combine with Other Tools: Pair with trend indicators, volume analysis, or price action for a robust strategy.
5. Monitor Breakouts: Trade breakouts when price breaches S/R or OB zones, with historical labels providing context.
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Example Use Cases
• Swing Trading: Use S/R and OB zones to identify entry/exit points, with historical broken levels for context.
• Breakout Trading: Trade price breaks through S/R or OB, using "Br S" and "Br R" labels to confirm reversals.
• Scalping: Adjust detection period for faster S/R and OB identification on lower timeframes.
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• Performance: Optimized for all timeframes, with best results on 5M, 15M, 30M, 1H, 4H, or daily charts for swing trading.
• Compatibility: Works with any asset class and TradingView chart.
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Get Started
Transform your trading with Support & Resistance with Order Blocks! Add it to your chart, customize it to your style, and trade with confidence. For questions or feedback, drop a comment on TradingView or message the author. Happy trading! 🚀
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Disclaimer: This indicator is for educational and informational purposes only. Always conduct your own analysis and practice proper risk management before trading.
FVG LevelsFVG Levels Indicator Description
The FVG Levels indicator dynamically identifies and displays key price zones that may represent fair value gaps and order block areas, helping traders to visually pinpoint potential support and resistance levels directly on the chart.
Key Features
Order Block Identification:
The indicator detects bullish and bearish order blocks by analyzing specific candle patterns. For bullish zones, it checks if a candle two bars ago was bullish (close greater than open) coupled with a subsequent gap condition. Similarly, bearish zones are identified when bearish candle conditions are met with an appropriate gap.
Dynamic Zone Calculation:
It computes critical levels such as the highest highs, lowest lows, highest lows, and lowest highs over a series of recent bars. These levels define the boundaries of potential buy and sell zones and adjust dynamically as new price data comes in.
Visual Representation:
Buy zones are plotted in lime and sell zones in yellow, with the indicator filling the areas between the high and low lines to create clear, shaded bands. This visual aid helps in quickly recognizing zones of potential price reaction.
Chart Overlay:
Designed to work as an overlay, the indicator integrates directly onto your price chart, allowing for seamless correlation between price action and identified zones.
How It Works
Bullish Zones:
When a bullish candle (with the candle's close above its open) is detected along with a significant gap, the indicator marks the upper and lower boundaries of the bullish order block. It further refines these levels by tracking the lowest low and highest high over recent bars to enhance the zone's definition.
Bearish Zones:
In a similar manner, the indicator calculates bearish order blocks by confirming bearish candle conditions and corresponding gap criteria. It then updates the bearish zone levels and computes the highest high and lowest low to establish clear sell zone boundaries.
Usage
Traders can use the FVG Levels indicator to:
Identify potential entry and exit points by observing where price may reverse or consolidate.
Recognize fair value gaps or imbalances that often act as magnet points for price action.
Enhance risk management by using the dynamically calculated zones to set stop-losses or take-profits.
Immediate Rebalance ICT [TradingFinder] No Imbalances - MTF Gaps🔵 Introduction
The concept of "Immediate Rebalance" in technical analysis is a powerful and advanced strategy within the ICT (Inner Circle Trader) framework, widely used to identify key market levels.
Unlike the "Fair Value Gap," which leaves a price gap requiring a retracement for a fill, an Immediate Rebalance fills the gap immediately, representing an instant balance that strengthens the prevailing market trend. This structure allows traders to quickly spot critical price zones, capitalizing on strong trend continuations without the need for price retracement.
The "Immediate Rebalance ICT" indicator leverages this concept, providing traders with automated identification of critical supply and demand zones, order blocks, liquidity voids, and key buy-side and sell-side liquidity levels.
Through features like crucial liquidity points and immediate rebalancing areas, this tool enables traders to perform precise real-time market analysis and seize profitable opportunities.
🔵 How to Use
The Immediate Rebalance indicator assists traders in identifying reliable trading signals by detecting and analyzing Immediate Rebalance zones. By focusing on supply and demand areas, the indicator pinpoints optimal entry and exit positions.
Here’s how to use the indicator in both bearish (Supply Immediate Rebalance) and bullish (Demand Immediate Rebalance) structures :
🟣 Bullish Structure (Demand Immediate Rebalance)
In a bullish scenario, the indicator detects a Demand Immediate Rebalance formed by two consecutive bullish candles with overlapping wicks. This structure signifies an immediate demand zone, where price instantly balances within the zone, reducing the likelihood of a revisit and indicating potential upside momentum.
Zone Identification : Look for two consecutive bullish candles with overlapping wicks, forming a demand zone. This structure, due to its rapid balance, usually does not require a revisit and supports further upward movement.
Entry and Exit Levels : If price revisits this zone, percentage markers, particularly 50% and 75%, act as supportive levels, creating ideal entry points for long positions.
Example : In the second image, an example of a Demand Immediate Rebalance is shown, where overlapping bullish candle shadows indicate immediate balance, supporting the continuation of the bullish trend.
🟣 Bearish Structure (Supply Immediate Rebalance)
In a bearish setup, the indicator identifies a Supply Immediate Rebalance when two consecutive bearish candles with overlapping wicks appear. This formation signals an immediate supply zone, suggesting a high probability of trend continuation to the downside, with minimal expectation for price to retrace back to this area.
Zone Identificatio n: Look for two consecutive bearish candles with overlapping shadows. This structure forms a supply area where price is expected to continue its downtrend without revisiting the zone.
Entry and Exit Level s: Should price revisit this zone, percentage-based levels (e.g., 50% and 75%) serve as potential resistance points, optimizing entry for short positions, especially if the downtrend is expected to persist.
Example : The attached chart illustrates a Supply Immediate Rebalance, where overlapping candle shadows define this area, reassuring traders of a continued downward trend with a low likelihood of price returning to this zone.
🔵 Settings
ImmR Filter : This filter allows users to adjust the detection of Immediate Rebalance zones in four modes, from "Very Aggressive" to "Very Defensive," based on zone width. The chosen mode controls the sensitivity of Immediate Rebalance detection, allowing users to fine-tune the indicator to their trading style.
Multi Time Frame : Enabling this option allows users to set the indicator to a specific timeframe (1 minute, 5 minutes, 15 minutes, 30 minutes, 1 hour, 4 hours, daily, weekly, or monthly), broadening the perspective for identifying Immediate Rebalance zones across multiple timeframes.
🔵 Conclusion
The Immediate Rebalance indicator, based on rapid balancing zones within supply and demand areas, serves as a powerful tool for market analysis and improving trade decision-making.
By accurately identifying zones where price achieves instant balance without gaps, the indicator highlights areas likely to support strong trend continuations, exempt from common retracements.
The indicator’s use of percentage levels enables traders to pinpoint optimal entry and exit points more effectively, with levels like 50% and 75% acting as support within demand zones and resistance within supply zones. This empowers traders to ride strong trends without the worry of abrupt reversals.
Overall, the Immediate Rebalance is a reliable tool for both professional and beginner traders seeking precise methods to recognize supply and demand zones, capitalizing on consistent trends.
By choosing appropriate settings and focusing on the zones highlighted by this indicator, traders can enter trades with greater confidence and improve their risk management.
BTC - Power Law OscillatorDescription:
The BTC - Power Law Oscillator is a technical analysis tool designed to help traders and investors identify potential overbought and oversold conditions in the Bitcoin market. This oscillator is based on a power law model that approximates Bitcoin's historical price trajectory, providing a framework for understanding deviations from this trajectory over time.
Key Features:
Exponential Model: The oscillator uses an exponential model that represents Bitcoin's price growth over time since its inception on January 3, 2009. This model is mathematically expressed as:
price=exp(5.71×ln(days since inception)−38.16)
This captures the long-term growth trend of Bitcoin, allowing for the analysis of deviations from this model.
Deviation Analysis: The Power Law Oscillator measures the percentage deviation of Bitcoin's closing price from the model price. This deviation is expressed as a percentage to illustrate how far the current price is from the expected model trajectory.
Normalization: The oscillator values are normalized to a 0-100 range. A quadratic transformation is applied to enhance sensitivity to higher values, allowing for better visualization and interpretation of extreme conditions.
Bands and Zones:
Upper Band (50): Indicates the 20% threshold. Values above this band suggest overbought conditions, where Bitcoin's price may be significantly above the expected trajectory.
Lower Band (15): Indicates the 5% threshold. Values below this band suggest oversold conditions, where Bitcoin's price may be significantly below the expected trajectory.
Top Zone: The area above the upper band is shaded red, highlighting potential sell or caution areas.
Bottom Zone: The area below the lower band is shaded green, highlighting potential buy or accumulation areas.
Benefits:
Trend Analysis: Helps identify long-term trends and potential reversals by analyzing price deviations from a theoretical model based on historical growth.
Market Timing: Assists in market timing decisions by indicating overbought and oversold conditions with visual bands and zones.
Enhanced Sensitivity: The quadratic normalization enhances sensitivity to changes in the oscillator, providing clearer signals for traders.
Usage Tips:
Complementary Tool: Use this oscillator in conjunction with other technical indicators and fundamental analysis for more comprehensive market insights.
Risk Management: Always employ sound risk management strategies when trading, as no single indicator can guarantee accurate predictions.
Market Context: Consider the broader market context, as Bitcoin's volatility can lead to significant short-term fluctuations.
The BTC - Power Law Oscillator provides a unique perspective on Bitcoin's price movements by leveraging a mathematical model to understand historical growth trends and deviations. Use this tool to gain deeper insights into market dynamics and enhance your trading strategy.
ICT KillZones Hunt [TradingFinder] 4 Sessions + OB + FVG + Alert🔵 Introduction
🟣 ICT
The "ICT" style is a subset of "Price Action" technical analysis. The primary goal of the ICT trading strategy is to merge "Price Action" with the "Smart Money" concept to pinpoint optimal trade entry points.
However, this approach's strength extends beyond merely finding entry points. It also helps traders gain a deeper understanding of price behavior and adapt their trading strategies to the market structure.
The most important concepts of "ICT" :
Order Block
Fair Value Gap(FVG)
Liquidity
🟣 Session
Financial markets are divided into several time periods, each featuring distinct characteristics and levels of activity. These periods, known as sessions, are active at different times during the day.
The primary active sessions in financial markets include :
Asian Session
European Session
New York Session
Based on the UTC time zone, the schedule for these key sessions is :
Asian Session: 23:00 to 06:00
European Session: 07:00 to 16:30
New York Session: 13:00 to 22:00
Note
To avoid session overlap and minimize interference during kill zones, the session times have been modified as follows :
Asian Session: 23:00 to 06:00
European Session: 07:00 to 14:25
New York Session: 14:30 to 22:55
🟣 KillZone
Kill zones are periods within a session where trader activity spikes. During these times, trading volume surges, and price movements become more pronounced.
The major kill zones, according to the UTC time zone, are as follows :
Asian Kill Zone: 23:00 to 03:55
European Kill Zone: 07:00 to 09:55
New York Morning Kill Zone: 14:30 to 16:55
New York Evening Kill Zone: 19:30 to 20:55
🔵 How to Use
🟣 Order Block
Order blocks are a distinct category of "Supply and Demand" zones, formed when a series of orders are grouped together. These blocks are often created by banks or other significant market participants.
Banks typically execute large orders in blocks during their trading sessions. If they were to enter the market with small quantities, substantial price movements would occur before the orders were fully executed, reducing potential profit.
To mitigate this, they divide their orders into smaller, more manageable positions. Traders should seek "buy" opportunities in "demand order blocks" and "sell" opportunities in "supply order blocks."
🟣 Fair Value Gap (FVG)
To pinpoint the "Fair Value Gap" on the chart, meticulous candle-by-candle analysis is essential. Pay close attention to candles with significant bodies, examining each candle alongside the one preceding it.
The candles flanking this central candle should exhibit elongated shadows, with bodies that do not intersect the body of the central candle. The span between the shadows of the first and third candles is referred to as the FVG range.
Note :
The origin of all Order Blocks and FVGs starts from inside a kill zone and extends up to the end of the same session.
🟣 Kill Zone Hunt
Following this strategy, after the conclusion of the kill zone and the stabilization of its high and low lines, if the price touches either of these lines within the same session and encounters a robust rejection, it presents an opportunity to enter a trade.
🔵 Setting
🟣 Global Setting
Show All Order Block :
If it is turned off, only the last Order Block will be displayed.
Show All FVG :
If it is turned off, only the last FVG will be displayed.
Show More Info Session :
If it is turned on, more information about kill zones (Trade Volume, Time, Number of Candles) will be displayed.
🟣 Logic Parameter
Pivot Period of Order Blocks Detector :
Enter the desired pivot period to identify the Order Block.
Order Block Validity Period (Bar) :
You can specify the maximum time the Order Block remains valid based on the number of candles from the origin.
Mitigation Level Order Block :
Determining the basic level of a block order. When the price hits the basic level, the order block due to mitigation.
🟣 Order Blocks Display
Demand Order Block :
Show or not show and specify color.
Supply order Block :
Show or not show and specify color.
🟣 Order Block Refinement
Refine Demand OB :
Enable or disable the refinement feature. Mode selection.
Refine Supply OB :
Enable or disable the refinement feature. Mode selection.
🟣 FVG
FVG Validity Period (Bar) :
You can specify the maximum time the FVG remains valid based on the number of candles from the origin.
Mitigation Level FVG :
Determining the basic level of a FVG. When the price hits the basic level, the FVG due to mitigation.
Show Demand FVG :
Show or not show and specify color.
Show Supply FVG :
Show or not show and specify color.
FVG Filter :
Enable or disable filtering of FVGs. Select filter mode.
🟣 Session
Show More Info Session Color
Asia Session, London Sesseion, New York am Session & New York pm Session :
Show or not show session and kill zones. Change the display color.
🟣 Alert
Send Alert When Touched Session high & Low :
On / Off
Alert Demand OB Mitigation :
On / Off
Alert Supply OB Mitigation :
On / Off
Alert Demand FVG Mitigation :
On / Off
Alert Supply FVG Mitigation :
On / Off
Message Frequency :
This string parameter defines the announcement frequency. Choices include: "All" (activates the alert every time the function is called), "Once Per Bar" (activates the alert only on the first call within the bar), and "Once Per Bar Close" (the alert is activated only by a call at the last script execution of the real-time bar upon closing). The default setting is "Once per Bar".
Show Alert Time by Time Zone :
The date, hour, and minute you receive in alert messages can be based on any time zone you choose. For example, if you want New York time, you should enter "UTC-4". This input is set to the time zone "UTC" by default.
Display More Info :
Displays information about the price range of the order blocks (Zone Price) and the date, hour, and minute under "Display More Info". If you do not want this information to appear in the received message along with the alert, you should set it to "Off".
Supply & Demand (MTF) [Bearly Invested]Overview
This multi-timeframe supply and demand zone indicator identifies institutional price areas using a unique "Last 2 Opposite Candles" methodology. Unlike traditional support/resistance indicators, this script detects zones by analyzing momentum-based impulse moves and marking the base formed by the last two opposite-colored candles before the displacement.
How It Works
Zone Detection Logic
The indicator identifies supply and demand zones through a four-step process:
Momentum Detection: Monitors for consecutive candles with body sizes exceeding the 20-period average body size by a configurable multiplier (default 0.5x)
Impulse Confirmation: When the required number of momentum candles (default: 4 candles within 4-bar span) is detected, the script identifies a potential impulse move
Base Identification: Looks back through all consecutive momentum bars, then scans up to 50 bars to find the last two opposite-colored candles that formed before the impulse
Zone Creation: Creates a supply/demand zone using the combined high and low of those two opposite candles
Multi-Timeframe Analysis
The indicator supports up to three simultaneous timeframes, allowing you to identify higher timeframe zones while trading on lower timeframes. Each timeframe independently calculates zones using its own momentum criteria, providing confluence when multiple timeframe zones align.
Zone Combination Feature
When "Combine Zones" is enabled, overlapping zones from different timeframes or detection instances are automatically merged into single zones. Combined zones display all contributing timeframes in the label (e.g., "15 Min & 30 Min").
Zone Management
Invalidation Methods
Choose between two zone invalidation approaches:
Wick: Zone remains valid until price wicks through the boundary
Close: Zone remains valid until a candle closes through the boundary
Zone Filtering
The script includes built-in filters to reduce noise:
Minimum zone size requirement (10 bars on detection timeframe)
Maximum zone size limit (1.5x ATR)
Minimum 5-bar cooldown between new zone detections
Distance-based filtering (zones beyond max lookback are hidden)
Key Features
Retest & Break Detection
Retests: Automatically marks when price retests an active zone with "R" labels
Breaks: Optionally displays "B" labels when zones are invalidated
Built-in cooldown system prevents label spam (5-bar minimum between retests)
Alert Conditions
Four alert types are included:
Supply Zone Retest
Demand Zone Retest
Supply Zone Break
Demand Zone Break
Configuration Guide
General Settings
Zone Count: High (30 zones), Medium (5), Low (3), or One (single most recent zone per type)
Momentum Count: Number of consecutive momentum candles required (default: 4)
Momentum Span: Maximum bars to scan for momentum confirmation (default: 4)
Max Lookback For Opposite Candles: How far back to search for base candles (default: 50)
Max Distance To Last Bar: Controls historical zone visibility (High: 1250 bars, Normal: 500, Low: 150)
Timeframe Configuration
Enable up to three timeframes simultaneously. When multiple timeframes show the same value (e.g., chart timeframe), duplicate detection automatically disables redundant calculations.
Visual Options
Customizable supply/demand colors with transparency
"Show Historic Zones" toggles visibility of broken/invalidated zones
Text color and label positioning controls
Combined zones display with increased opacity for emphasis
Best Practices
Timeframe Selection: Use higher timeframes (15m, 30m, 1H) for swing trades; lower timeframes work for scalping when combined with HTF confluence
Zone Invalidation: "Close" method reduces false breaks from wicks; "Wick" method is more conservative
Zone Count: Start with "Medium" or "Low" settings to avoid chart clutter, especially on lower timeframes
Momentum Parameters: Lower values (3-4) detect more zones; higher values (5-6) create stricter, higher-quality zones
Combine Zones: Enable this feature to merge overlapping multi-timeframe zones for cleaner charts and stronger confluence areas
Important Notes
Zones are calculated in real-time on the detection timeframe and displayed on your chart timeframe
The indicator looks back a maximum of 2000 bars for calculations
Maximum of 500 boxes/labels can be displayed simultaneously due to Pine Script limitations
Zones older than the "Max Distance" setting are automatically hidden but still tracked for break/retest detection
The "Last 2 Opposite Candles" method may produce zones of varying sizes depending on the range of those base candles
VIX Percentile OscillatorWhat is this script?
This is a trading tool that helps you decide when to buy or sell options based on market volatility. Think of it as a "fear meter" for the stock market.
What is VIX?
VIX = Volatility Index (also called the "fear index")
When VIX is HIGH → Market is scared/volatile → Options are EXPENSIVE
When VIX is LOW → Market is calm → Options are CHEAP
What does "Percentile" mean?
Instead of just showing VIX price, this script shows where VIX is compared to history.
Example: If VIX Percentile = 85%
This means VIX is higher than 85% of all past readings
Only 15% of the time was VIX higher than now
Translation: Volatility is unusually HIGH
The 5 Trading Zones
The script divides the market into 5 zones:
🔴 EXTREME SELLING ZONE (90-100%)
VIX is in the top 10% historically
Action: AGGRESSIVELY SELL OPTIONS (collect big premiums)
Market panic = expensive options = profit for sellers
🟠 SELLING ZONE (80-89%)
VIX is elevated but not extreme
Action: SELL OPTIONS (good premiums available)
⚪ NEUTRAL ZONE (20-79%)
VIX is normal
Action: WAIT or use other strategies
🟢 BUYING ZONE (10-19%)
VIX is low
Action: BUY OPTIONS (they're cheap)
🟢 EXTREME BUYING ZONE (0-9%)
VIX is in the bottom 10% historically
Action: AGGRESSIVELY BUY OPTIONS (bargain prices)
Market complacency = cheap options = opportunity
Understanding the Chart
Main Line (Blue/Red/Green):
Shows current VIX percentile
Color changes based on zone
Thick line = easy to see
Histogram (Background bars):
Red bars = above 50% (high volatility)
Green bars = below 50% (low volatility)
Purple Momentum Line:
Shows if VIX is rising or falling
Helps you catch trends early
Background Colors:
Light red/orange = Selling zones
Light green = Buying zones
Triangle Markers:
Appear when entering new zones
"EXTREME" label = strongest signals
The Statistics Table (Top Right)
VIX Price: Current VIX value (e.g., 16.50)
Percentile: Where VIX ranks (0-100%)
Z-Score: Statistical measure
Above +2 or below -2 = extreme
Red text = unusually high/low
Momentum: Rate of change
Red = rising (volatility increasing)
Green = falling (volatility decreasing)
Avg VIX: Average VIX over lookback period
Current Zone: Which zone you're in right now
Bars in Zone: How long you've been in this zone
Simple Trading Rules
FOR OPTION SELLERS (Premium Collectors):
✅ SELL when: Percentile > 80% (especially > 90%)
High premiums available
Examples: Sell covered calls, cash-secured puts, credit spreads
FOR OPTION BUYERS (Hedgers/Speculators):
✅ BUY when: Percentile < 20% (especially < 10%)
Cheap options available
Examples: Buy protective puts, long calls, debit spreads
Key Settings You Can Adjust
Lookback Period (default: 252)
How far back to compare (252 = 1 year of trading days)
Longer = smoother, more stable
Shorter = more sensitive to recent changes
Smoothing Period (default: 3)
Reduces noise/wiggling
Higher = smoother line
Lower = more responsive
Zone Thresholds:
Extreme Sell: 90%
Sell: 80%
Buy: 20%
Extreme Buy: 10%
You can customize these!
Real-World Example
Scenario: VIX Percentile jumps to 92%
What this means:
VIX is higher than 92% of all past readings
Market is in panic mode
Option premiums are INFLATED
Trading Action:
✅ Sell covered calls on stocks you own
✅ Sell cash-secured puts on stocks you want to buy
✅ Sell credit spreads
❌ DON'T buy expensive options right now
Why it works: When fear is extreme, it usually calms down eventually. You profit as premiums deflate.
Important Reminders
⚠️ This is a TIMING tool, not a crystal ball
It tells you WHEN premiums are expensive/cheap
It doesn't tell you WHICH options to trade
You still need proper risk management
⚠️ Works on ALL timeframes
Daily charts = swing trading
Weekly charts = position trading
Intraday charts = day trading volatility
⚠️ Best for:
Option sellers during high VIX (>80%)
Option buyers during low VIX (<20%)
Portfolio hedging decisions
Volatility trading strategies
Bottom Line: This script helps you buy options when they're cheap and sell options when they're expensive. It's like shopping for sales, but for volatility!
DISCLAIMER: This information is provided for educational purposes only and should not be considered financial, investment, or trading advice. Please do boost if you like it. Happy Trading.
