SMC BOS Strategy 1:1 RRThe SMC BOS Strategy 1:1 RR is a Smart Money Concepts–based trading strategy designed to capture high-probability market continuation moves after a Break of Structure (BOS). It focuses on trading in the direction of institutional momentum with clear risk control.
📌 Core Concept
Markets move in structure (higher highs & higher lows in an uptrend, lower highs & lower lows in a downtrend).
A Break of Structure (BOS) occurs when price closes beyond a previous swing high or swing low, signaling that smart money may be pushing price in a new or continued direction.
⚙️ Strategy Rules
1️⃣ Market Structure Identification
Swing highs and swing lows define key structure levels.
These levels act as institutional decision points.
2️⃣ Break of Structure (BOS)
Bullish BOS: Price closes above the previous structure high.
Bearish BOS: Price closes below the previous structure low.
3️⃣ Trade Entry
Buy after a bullish BOS.
Sell after a bearish BOS.
Entry is taken at the close of the BOS candle.
4️⃣ Risk Management (1:1 RR)
Stop Loss (SL):
Long trades → below previous structure low.
Short trades → above previous structure high.
Take Profit (TP):
Set equal to the stop-loss distance (1:1 risk–reward).
📊 Why 1:1 Risk–Reward?
Ensures high win-rate focus.
Suitable for scalping and intraday trading.
Protects capital with consistent, controlled risk.
✅ Key Advantages
✔ Clear and objective rules
✔ Institutional price-action logic (SMC)
✔ Automatic stop loss & take profit
✔ Works on Forex, Gold, Crypto, Indices
✔ Easy to backtest and optimize
带和通道
VWAP + Hull MA Scalping PRO//@version=6
indicator("VWAP + Hull MA Scalping PRO", overlay=true)
// ================= INPUTS =================
src = input.source(close, "Source")
// Hull MA lengths
len5 = input.int(5, "HMA 5")
len9 = input.int(9, "HMA 9")
len18 = input.int(18, "HMA 18")
len34 = input.int(34, "HMA 34")
// ================= FUNCTIONS =================
hma(src, length) =>
ta.wma(
2 * ta.wma(src, length / 2) - ta.wma(src, length),
math.round(math.sqrt(length))
)
// ================= CALCULATIONS =================
hma5 = hma(src, len5)
hma9 = hma(src, len9)
hma18 = hma(src, len18)
hma34 = hma(src, len34)
vwapVal = ta.vwap(close)
// ================= DYNAMIC COLORS =================
c5 = hma5 > hma5 ? color.lime : color.red
c9 = hma9 > hma9 ? color.green : color.maroon
c18 = hma18 > hma18 ? color.aqua : color.orange
c34 = hma34 > hma34 ? color.blue : color.purple
// ================= TREND LOGIC =================
bullTrend = hma5 > hma9 and hma9 > hma18 and hma18 > hma34 and close > vwapVal
bearTrend = hma5 < hma9 and hma9 < hma18 and hma18 < hma34 and close < vwapVal
// ================= ENTRY SIGNALS =================
buySignal = bullTrend and ta.crossover(hma5, hma9)
sellSignal = bearTrend and ta.crossunder(hma5, hma9)
// ================= PLOTS =================
plot(vwapVal, "VWAP", color=color.yellow, linewidth=2)
plot(hma5, "HMA 5", color=c5, linewidth=2)
plot(hma9, "HMA 9", color=c9, linewidth=2)
plot(hma18, "HMA 18", color=c18, linewidth=2)
plot(hma34, "HMA 34", color=c34, linewidth=2)
// ================= SIGNAL MARKERS =================
plotshape(buySignal, title="BUY", location=location.belowbar,
color=color.lime, style=shape.triangleup, size=size.small, text="BUY")
plotshape(sellSignal, title="SELL", location=location.abovebar,
color=color.red, style=shape.triangledown, size=size.small, text="SELL")
// ================= BACKGROUND TREND =================
bgcolor(bullTrend ? color.new(color.green, 92) :
bearTrend ? color.new(color.red, 92) : na)
// ================= ALERTS =================
alertcondition(buySignal, title="BUY Alert", message="{{ticker}} BUY | VWAP + HMA")
alertcondition(sellSignal, title="SELL Alert", message="{{ticker}} SELL | VWAP + HMA")
RSI Trendline Breakout BB Exit -by RiazMalikUse this strategy based on RSI and bolinger bands
When RSI trend line breaks take position when RSI touches bolinger bands exit
VWAP Institutional Trading Engine INDICATORVWAP Institutional Trading Engine
Adaptive Market Regime & Trading Model Indicator
🔍 Overview
The VWAP Institutional Trading Engine is an advanced, rule-based market analysis indicator designed to replicate institutional decision-making logic using VWAP, volatility, and session-based market behavior.
This indicator does not predict price.
Instead, it answers a more important question:
“What type of trading is appropriate right now – if any?”
The engine continuously evaluates:
Market regime (trend, range, dead market)
Volatility conditions
VWAP acceptance and deviation
Trading session (Asia / London / New York)
Based on this, it dynamically activates one of three trading models:
TREND
MEAN REVERSION
OFF (no trading)
This makes it ideal for:
Discretionary traders
Systematic traders
Risk-focused trading
Educational / portfolio-style trading approaches
🧠 Core Philosophy
Professional trading is not about finding more signals.
It is about knowing when not to trade.
This indicator is built around three institutional principles:
VWAP defines fair value
Volatility defines opportunity or danger
Different sessions require different behavior
⚙️ Indicator Components
1️⃣ VWAP & Statistical Deviation Bands
VWAP represents institutional fair price
±1σ bands indicate acceptance zones
±2σ bands represent statistical extremes
Used for:
Mean reversion zones
Trend acceptance confirmation
Go Score calculation
2️⃣ Volatility Engine
Volatility is measured using ATR relative to price
Compared against its own moving average
Classifications:
Low volatility → dead / untradable market
Normal volatility → structured behavior
High volatility → trend or liquidation events
3️⃣ Market Regime Detection
The engine classifies each moment into one regime:
Regime Meaning
TREND Price accepts above or below VWAP with volatility
RANGE Price rotates near VWAP
DEAD Low volatility, no opportunity
MIXED Unclear structure
4️⃣ Active Trading Model (Most Important)
Displayed in the dashboard as Model:
Model Interpretation
TREND Trade with momentum and continuation
MEAN_REVERT Trade extremes back to VWAP
OFF Do not trade
The Model tells you HOW you are allowed to trade right now.
5️⃣ Session Awareness (UTC)
The indicator adapts behavior based on session logic:
Session Preferred Behavior
Asia Mean Reversion
London Trend
New York Selective / adaptive
Trades are only allowed when model + session are aligned.
6️⃣ Go Score – Trade Quality Filter
Each potential setup receives a Go Score (0–100), based on:
Distance from VWAP
Market regime quality
Volatility penalties
Go Score Interpretation
≥ 80 High-quality (A+)
65–79 Acceptable
< 65 No trade
7️⃣ Risk Guidance (Informational)
The indicator outputs a Risk % suggestion, based on:
Go Score
Simulated drawdown logic
⚠️ This is guidance only, not position sizing.
📈 Visual Signals
The indicator plots contextual signals, not blind entries:
Mean Reversion Signals
▲ Long below −2σ
▼ Short above +2σ
Trend Signals
↑ Long after acceptance above +1σ
↓ Short after acceptance below −1σ
Signals appear only when trading is allowed by:
Model
Session
Go Score
🧩 Dashboard Explanation
The top-right dashboard displays real-time engine state:
Field Description
Session Current UTC session
Regime Detected market condition
Go Score Trade quality score
Risk % Suggested relative risk
Drawdown % Virtual defensive metric
Model Active trading model
If Model = OFF → do nothing.
🧭 Practical Trading Manual (Step-by-Step)
Step 1 – Check the Model
TREND → look for continuation
MEAN_REVERT → look for extremes
OFF → do not trade
Step 2 – Confirm Session Alignment
Asia + Mean Reversion ✔
London + Trend ✔
Misalignment = caution
Step 3 – Check Go Score
Below 65 → skip
65+ → proceed
Step 4 – Use Chart Structure
VWAP = anchor
σ bands = context
Signal = permission, not obligation
Step 5 – Manage Risk Manually
Use your own SL/TP rules
Follow the Risk % as guidance, not law
❌ What This Indicator Is NOT
Not a signal spam tool
Not a prediction system
Not a “holy grail”
It is a decision framework.
✅ Best Use Cases
Futures
Indices
Forex
Crypto
Intraday & swing trading
Recommended timeframes:
5m – 1H (intraday)
4H (contextual swing)
🏁 Final Notes
This indicator is intentionally transparent and rule-based.
It is designed to help traders:
Think in regimes
Trade with structure
Avoid overtrading
Protect capital
If you trade with the Model, not against it,
you will already be ahead of most market participants.
Session Anchored OIWAP [Arjo]The Session Anchored OIWAP (Open Interest Weighted Average Price) indicator shows you a weighted average price that uses Open Interest (OI) changes during different trading sessions . It divides the day into four clear sessions: Opening Hour , Morning Session , Mid-Day Session , and Closing Session .
For each session , it calculates a weighted average price using both market price and open interest data from futures . This line updates as the session progresses and resets when a new session starts .
You can also see optional deviation bands that you visually compare to how far the market price is moving away from the session’s weighted average. This indicator also helps you watch how Open Interest changes connect with price movements during specific market hours.
Concepts
This tool works on a few simple ideas:
Session anchoring
Each session starts fresh. The indicator resets and begins a new calculation when a new time block begins. This allows users to visually study each session independently.
Open-interest weighting
Instead of treating all price moves equally, price changes linked to higher open-interest activity have more influence on the OIWAP. This gives a weighted reflection of where the market has been trading during the session.
Averaging and smoothing
The OIWAP line blends many price data points into one smooth curve, making it easier to follow than raw price movement.
Volatility display with bands
The upper and lower bands are placed at ±0.5 standard deviation from the OIWAP line. These bands simply help you see when price stretches further away than usual from the session average.
Features
Four Independent Session Calculations: Shows separate OIWAP lines for Opening Hour (default: 09:15-10:15), Morning (10:15-11:30), Mid-Day (11:30-14:00), and Closing (14:00-15:30) sessions
Open Interest Weighting: Uses absolute OI change as the weight instead of traditional volume
Customizable Session Times: You can change the time ranges for each session to match your market or what you need
Optional Deviation Bands: You can turn ±0.5 standard deviation bands on or off around each OIWAP line
Color-Coded Sessions: Each session has its own color so you can tell them apart easily
Selective Display: You can turn individual sessions and bands on or off
Data Availability Check: Shows you a notification when Open Interest data isn't available for your symbol
Adjustable Position Timeframe: You can calculate OI changes on different timeframes (Chart, Daily, 15min, 30min, 60min, 120min)
How to use
Add this indicator to a chart of any symbol that has Open Interest data ( from futures or derivatives contracts). Once you add it, you'll see colored lines showing the OIWAP for each session you enable, along with optional deviation bands.
Adjusting Settings:
Turn individual sessions on or off using the checkboxes in the " Sessions " section
Change session colors to match your chart or what looks good to you
Turn deviation bands on or off using the " Show Bands " option in the Display settings
Change session time ranges in the " Session Times " section to match your market hours or what you want to analyze
Change the Position Timeframe if you want to see OI changes calculated on a different time period
Visual Interpretation:
Each OIWAP line shows you the OI-weighted average price for that session
The deviation bands show you how much prices spread out, weighted by OI changes
You can watch how price interacts with these levels to see where significant OI activity happened
Different sessions may show different OIWAP levels, showing you how the OI-price relationship changes throughout the trading day
Note:
This indicator needs Open Interest data to work. If OI data isn't available for your symbol, you'll see a message in the center of your chart. This indicator works only with derivatives markets like futures and options in the Indian Market where OI data is publicly available.
Conclusion
The Session Anchored OIWAP indicator is designed to support structured market observation by combining price, open interest, and session anchoring into a clear visual format. It helps users study market behavior during different parts of the day without generating trading instructions or outcomes.
Disclaimer
This indicator is for educational and visual-analysis purposes only. It does not provide trading signals , financial advice, or guaranteed outcomes . You should perform your own research and consult a licensed financial professional when needed. All trading decisions are solely the responsibility of the user.
Happy Trading
MADZ - Moving Average Deviation Z-ScoreMADZ - Moving Average Deviation Z-Score
MADZ is a powerful valuation oscillator that measures how far the current price has deviated from a user-selected moving average, expressed in statistical terms as a Z-Score. This normalization makes it easier to identify overvalued and undervalued conditions across different assets, timeframes, and market environments.
Overview
The indicator works by:
Calculating the percentage deviation of price from a customizable moving average (SMA, EMA, WMA, VWMA, HMA, or RMA).
Applying a Z-Score transformation to this deviation over a chosen lookback period — showing how many standard deviations the current deviation is from its historical average. Smoothing the result for a clean, responsive oscillator centered around zero.
Positive values indicate price is trading above the moving average (potentially overvalued), while negative values suggest price is below (potentially undervalued). The further from zero, the greater the relative valuation extreme.
Key Features
Customizable base moving average (type and length)
Z-Score normalization for statistically meaningful readings
Final smoothing for reduced noise
Static overbought/oversold levels (default ±1.5) — line changes color when crossed (red above, green below)
Dynamic extreme bands (±3σ) — optional display of bands calculated from the oscillator’s own volatility over a user-defined period
Extreme zone highlighting — background shading activates only during truly rare valuation events
Extreme Zone Highlighting Explained
The highlighted extreme zones (background shading) are not based on the fixed static levels. Instead, they signal statistically significant outliers using dynamic bands:
Overbought extreme zone (red background): Triggered when MADZ rises above the upper dynamic band (+3 standard deviations of the MADZ line itself over the dynamic length period).
Oversold extreme zone (green background): Triggered when MADZ falls below the lower dynamic band (-3 standard deviations).
These ±3σ bands adapt to the recent behavior of the oscillator. Because they represent three standard deviations from the mean of MADZ, crossings are rare and often precede major reversals or trend accelerations — making them valuable for spotting potential turning points in valuation extremes.
How to Use
Use zero-line crosses for trend changes or mean-reversion setups.
Watch static level crossings (±1.5 default) for early overbought/oversold warnings.
Pay special attention to extreme zone shading — these highlight high-conviction valuation dislocations that may offer superior risk/reward opportunities.
Designed on the BTC chart, but can be used on other assets.
Settings
Moving Average Settings: Type, length, source
Z-Score & Smoothing: Lookback period and smoothing length
Threshold Levels: Static overbought/oversold thresholds
Display Options: Toggle dynamic bands and extreme background highlighting
This is an educational tool designed to aid in valuation analysis. The information provided is not financial advice. Always conduct your own research and consider multiple factors before making trading decisions. Trade at your own risk.
Box BO signals v1Box Breakout Direction Flip Signals is a smart price‐action tool designed to identify clean directional shifts using consolidation boxes and breakout logic.
The indicator draws dynamic high–low range boxes and generates Buy (B) and Sell (S) signals only when direction flips, avoiding repeated noise signals during trending moves.
✔ First breakout after box marks direction (Buy or Sell)
✔ Signals alternate: S → B → S → B, never repeating
✔ No signals while price simply continues in same direction
✔ Labels are spaced away from candles for clean visibility
✔ Works best on lower timeframes (1m, 3m, 5m) for scalping / intraday
🎯 How It Works
1️⃣ A consolidation zone forms automatically using candle high–low
2️⃣ Breakout above the box → Buy label → new box begins
3️⃣ Breakout below the box → Sell label → new box begins
4️⃣ Signals print only on actual directional change (flip)
5️⃣ Boxes extend dynamically until breakout occurs
Ultimate Imbalance + RSI + Mean Reversion (v6)
FVG / Imbalance Logic:
🔵 Blue boxes (solid)
Bullish imbalances
These are areas where buying was so aggressive that price skipped levels.
What they represent
• Inefficient auction
• Buyers overwhelmed sellers
• Market left “unfinished business” below price
Types inside blue boxes
• Solid blue box = FVG or Opening Gap
• Blue dotted box = Volume Imbalance (VI)
__________________________________________________
🔴 Red boxes (solid)
Bearish imbalances
Opposite of blue: selling pressure skipped levels upward.
What they represent
• Aggressive sellers
• Liquidity vacuum above price
• Unfinished auction above
__________________________________________________
Gray boxes
Dead / resolved imbalances
These were once valid, but are now structurally irrelevant.
Boxes turn Gray when one of two things happened:
1. Filled
• Bullish → price traded down into the bottom of the box
• Bearish → price traded up into the top of the box
2. Invalidated
• Bullish → price closed below the box
• Bearish → price closed above the box
Gray = do not trade anymore // It’s historical context only.
They extend forward to:
• To visually show when they were resolved
• Help you see how long imbalances tend to survive on that market / timeframe
__________________________________________________
RSI Logic:
RSI filter (RSI 9, smoothed)
• Long bias: RSI ≤ 20 (oversold)
• Short bias: RSI ≥ 80 (overbought)
👉 RSI must already be extreme // We do NOT trade mid-range RSI.
__________________________________________________
Mean Reversion Channel (MRC) Logic:
What it measures:
• Distance from statistically “fair” price
• Uses volatility-adjusted bands (not fixed %)
Zones:
• Inner band = Normal mean oscillation
• Outer band = Exhaustion
• Beyond outer = Forced unwind / liquidation
Trade bias logic:
• Long allowed only if: price at or below lower outer band
• Short allowed only if: price at or above upper outer band
__________________________________________________
Final Signal from all 3 (prints a triangle):
✅ Long setup
1. Active bullish imbalance is touched
2. RSI ≤ oversold
3. Price is at MRC oversold zone
✅ Short setup
1. Active bearish imbalance is touched
2. RSI ≥ overbought
3. Price is at MRC overbought zone
This is why signals are intentionally rare.
Donchian FlowDonchain Flow is a breakout indicator inspired by Donchian channels, using a customizable block size to detect market swings. It generates buy/sell signals only on high-volume breakouts (RVOL > threshold) in strong trends (ADX > threshold), filtering out noisy/choppy periods. Visuals include channel lines, regime background coloring (green: bullish, red: bearish, gray: weak trend), and labeled signals for optimal entries. Ideal for trend-following strategies. Despite its simplicity, it performs surprisingly well. I recommend reviewing it for scalping.
Ping-Pong Fade (BB + Absorption Proxy)Ping-Pong Fade is a short-term mean-reversion indicator designed to capitalize on range-bound, low-catalyst market conditions. The setup targets price extremes where directional follow-through fails and liquidity absorption occurs, causing price to revert back toward equilibrium.
When price reaches a statistical extreme (±2 standard deviations) without acceptance, aggressive orders are absorbed rather than expanded. This imbalance frequently leads to a controlled reversal back toward the mean.
1. Bollinger Band Extreme
Upper Band (2 SD) → potential short fade
Lower Band (2 SD) → potential long fade
2. Absorption Proxy (Tape Substitute)
Absorption is inferred using:
Volume expansion relative to recent average
Small candle body (lack of continuation)
Rejection from the Bollinger Band extreme
Signals
FADE ↑ → Long setup at lower band with absorption
FADE ↓ → Short setup at upper band with absorption
Signals are plotted directly on the chart and can be used with alerts.
Ideal Market Conditions
Sideways or rotational markets
Midday consolidation
Low-volatility environments
Liquid ETFs and large-cap stocks
Conditions to Avoid
Opening range expansion
Strong trend days
High-impact news or macro events
RCAzussie_HAMA Candles Final HAMA Candles & Auto S/R System
* Overview
This indicator combines the trend-following power of HAMA (Heiken Ashi Moving Average) candles with an Automated Support & Resistance system. It is designed to filter out market noise and identify key reversal levels efficiently.
* Key Features
HAMA Candles (Trend)
Smoothed candles help visualize the true market trend.
Green: Bullish Trend
Red: Bearish Trend
Includes a central MA line with gradient colors to indicate trend strength.
Auto Support & Resistance (Levels)
Automatically plots dynamic S/R levels based on pivot points.
Level 1 (White): Short-term (Lookback 5) - For scalping.
Level 2 (Yellow): Mid-term (Lookback 10) - For swing trading.
Level 3 (Orange): Long-term (Lookback 20) - Strongest levels.
* Simplified Alerts
MA Cross (Any): Triggers when price crosses the main MA line (Trend entry/exit).
Major S/R Touch: Triggers ONLY when price touches the strongest Level 3 lines (Reversal check).
* Recommended Chart Setup (Important)
Use Range Bars: This system is optimized for Range Charts, not standard time-based candles (e.g., 1m, 5m).
Focus on Price: Range bars ignore the time axis completely and generate new bars only when the price moves a specific amount. This eliminates time-based noise.
How to Set:
Click the timeframe menu in the top bar.
Select "Range".
Choose a value based on volatility (e.g., 40R for scalping, 100R for crypto/indices).
HAMA 캔들 & 자동 지지저항 시스템
* 개요:
이 지표는 HAMA (Heiken Ashi Moving Average) 캔들의 추세 추종 기능과 자동 지지/저항(S/R) 시스템을 결합한 도구임. 시장의 노이즈를 제거하고 핵심 반전 구간을 찾는 데 최적화됨.
* 핵심 기능
HAMA 캔들 (추세)
노이즈가 제거된 부드러운 캔들로 진짜 추세를 보여줌.
초록색: 상승 추세
빨간색: 하락 추세
중앙 MA 라인의 그라디언트 색상으로 추세 강도를 시각적으로 확인 가능.
자동 지지 & 저항 (레벨)
피봇 포인트 기반으로 지지/저항선을 자동 작도함.
Level 1 (흰색): 단기 (Lookback 5) - 스캘핑용
Level 2 (노란색): 중기 (Lookback 10) - 스윙용
Level 3 (주황색): 장기 (Lookback 20) - 가장 강력한 지지/저항 구간
간편 알람 (Alerts)
MA Cross (Any): 가격이 중앙 MA 라인을 돌파할 때 울림 (진입/청산 신호).
Major S/R Touch: 가장 강력한 Level 3 라인을 터치할 때만 울림 (반전 확인용).
* 추천 차트 설정 (필독)
레인지(Range) 차트 사용: 이 지표는 일반적인 시간 봉(분봉, 시봉)이 아니라 레인지 바에 최적화되어 있음.
가격 집중: 시간의 흐름(X축)을 무시하고, 오직 '가격'이 움직일 때만 캔들이 생성됨. 이렇게 하면 횡보 구간의 노이즈가 사라짐.
설정 방법:
트레이딩뷰 상단 시간 메뉴 클릭.
'Range' 선택.
자산 변동성에 맞춰 값 설정 (예: 스캘핑은 40R, 비트코인/지수는 100R 추천).
알씨아저씨
BLOG: blog.naver.com
Nifty OI Support Resistance This study is designed for educational purposes to assist traders in analyzing price structure on the Nifty 50 index. It creates visual reference zones based on standard mathematical intervals used in the derivatives market.
Purpose of the Tool: In the Nifty 50 index, price action is often analyzed relative to "Round Numbers" or standard strike intervals (e.g., multiples of 50). This script automatically plots these mathematical reference levels relative to the current price to help users observe price behavior.
How It Works: This indicator uses a mathematical formula to identify the nearest standard strike price intervals based on the current close price.
Strike Logic: It projects levels at standard 50-point intervals (Nifty's standard strike distance).
Volatility Buffers: It adds a user-defined buffer (default: 30 points) around these levels to visualize a "zone" rather than a specific price point.
Major Levels: It visually distinguishes major round numbers (multiples of 500) which are often significant for technical analysis.
Features:
Automated Plotting: Adjusts dynamically as price moves to show relevant upper and lower reference bands.
Zone Visualization: Helps in identifying potential areas of support or resistance based on technical structure.
Customizable: Users can adjust the strike distance and buffer range to suit different volatility conditions.
Usage: This tool is intended to be used as a visual aid for Technical Analysis. It allows users to see where the price is located relative to standard Nifty intervals.
⚠️ STANDARD DISCLAIMER & DISCLOSURE:
Nature of Content: This script and description are for educational and informational purposes only.
No Financial Advice: This tool does not constitute investment advice, buy/sell recommendations, or trading tips.
Not SEBI Registered: The author is not a SEBI registered Research Analyst (RA) or Investment Advisor (IA).
Methodology: The levels displayed are generated purely via mathematical calculation based on price inputs and do not represent real-time exchange Open Interest data.
Risk Warning: Trading in securities market is subject to market risks. Read all the related documents carefully before investing. User discretion is advised.
laoto Simple Moving Averages (SMA)Five Simple Moving Averages (SMA)
Customizable colors and periods (lengths).
Key Price Levels + Zones"Support and resistance are rarely exact lines; hey are zones where price reacts."
This indicator upgrades standard horizontal levels by visualizing Liquidity Zones around the most critical intraday reference points: Pre-Market, Previous Day, and Previous Week Highs/Lows.
Unlike basic scripts that just draw thin lines, this tool combines the precision of exact price levels with the reality of market volatility. It offers deep customization, allowing you to separate line colors from zone colors, perfect for keeping your charts clean and professional.
Key Features
1. Dual Zone Logic (Dynamic Sizing)
• Price Tier Mode (Default): Zones are sized based on the asset price (e.g., higher-priced stocks get wider zones automatically). This mimics "psychological" levels.
• ATR Volatility Mode: Switches calculation to use the Average True Range (ATR). Zones expand during high volatility and contract during chop, adapting to the market conditions in real-time.
2. Ultimate Customization
• Separate Colors: You can finally set your Line Color (e.g., Bright Green) independently from your Zone Fill (e.g., Faint Grey).
• Individual Toggles: Turn the Line, Zone, or Label on/off individually for every single level.
• Line Styles: Differentiate daily levels (Solid) from weekly levels (Dashed) instantly.
3. The "Smart" Levels
• PM High/Low: Real-time Pre-Market tracking that freezes at the open.
• PD High/Low: Previous Day’s range.
• PW High/Low: Previous Week’s range (Critical for swing points).
---
Settings Guide
• Extension Style:
- Individual: Keeps history of levels for backtesting.
- Most Recent: Keeps the chart minimal by extending only today's levels.
• Zone Thickness Mode: Switch between "Price Tier" and "ATR Volatility".
• ATR Settings: Fully adjustable Length and Multiplier (when in ATR mode).
• Transparency: Global slider to control how subtle or bold the zones appear.
How to Trade This
• The "Trap": If price breaks a Line but fails to close outside the Zone, it is often a liquidity grab (fakeout).
• The Retest: Watch for price to break a level and use the Zone as a cushion for a bounce/retest entry.
Price-Time Confluence Engine
Price-Time Confluence Engine is a dual-layer market analysis indicator designed to synchronize price-based targets with time-based momentum projections, helping traders anticipate potential reaction points, reversals, and momentum shifts.
The indicator combines adaptive ATR price targets with deviation context on the chart, alongside a forward-projected Stochastic RSI structure in a dedicated pane.
🔹 Core Components
1️⃣ Adaptive Price Targets (Chart Overlay)
On every new candle, a new ATR-based price target is generated automatically.
The target updates dynamically with live price movement until the candle closes.
Targets are directionally aligned with the current candle’s momentum.
A HIT label is displayed when price reaches the active target during the candle.
Behavioral Insight
If a target fails to be hit and remains red after the next candle forms, this behavior has shown a tendency to correlate with short-term swing reversals, signaling potential exhaustion or loss of momentum.
2️⃣ Mean & Deviation Framework
A configurable mean (moving average) is plotted with up to four deviation bands.
Deviation bands provide contextual boundaries for price targets and help visually frame volatility expansion or compression.
An optional filter allows HIT labels to require alignment with the first deviation band.
3️⃣ Stochastic RSI Projection (Indicator Pane)
The lower pane displays live Stochastic RSI %K and %D values.
A historical Stoch RSI pattern is cloned and projected forward in time, creating a time-based momentum forecast.
The projection highlights anticipated crossing points between %K and %D before they occur.
A single dynamic “Projected Cross” label marks the next expected crossing location.
Vertical reference lines and directional arrows help visualize projected momentum shifts.
Important Note on Timeframes
The projection logic is optimized for the Daily timeframe.
Other timeframes may require different lookback settings for meaningful alignment.
Price-based targets and deviation logic function on any timeframe.
🔧 User Controls
ATR length and multiplier
Mean length and deviation depth
Number of deviation bands displayed
Label visibility and history limits
Projection visibility and forward shift
Optional normalization of projected momentum
Visual toggles for arrows, vertical lines, and labels
📈 How to Use
Observe the active price target forming with each new candle.
Watch whether price hits or fails to hit the target before the next candle.
Use deviation bands to contextualize where targets sit within volatility structure.
Reference the Projected Cross in the lower pane to anticipate potential momentum transitions.
Look for confluence between unhit targets and projected momentum shifts as potential inflection zones.
⚠️ Disclaimer
This indicator is a visual analysis and decision-support tool.
It does not generate trade signals and should be used in conjunction with proper risk management and additional market context.
MAs + Bollinger Bands by @ETERNYWORLDMAs + Bollinger Bands by @ETERNYWORLD is the core trend and volatility layer inside the Trend Mastery Pro ecosystem, engineered by EternityWorld to deliver a clean, structured, and highly customizable market bias reading directly on the chart.
What’s Inside the Indicator
5 independent Moving Averages (EMA or SMA) with individual enable/disable toggles, lengths, colors, and widths.
Bollinger Bands with professional basis options: SMA, EMA, RMA/SMMA, WMA, VWMA, plus adjustable deviation multiplier and visual band fill.
Chart overlay compatibility, making trend and volatility easy to interpret for fast decisions.
Fully configurable alerts, enabling traders to stay proactive without missing high-probability expansion triggers.
Enhanced by Trend Mastery Pro Workflow
This indicator complements the 3-step methodology of Trend Mastery Pro:
Bias → defines the dominant trend direction.
Trigger → identifies breakout or momentum expansion zones using confluence with volatility.
Management → supports consistent risk execution when combined with external strategy rules and trade plans.
Key Strengths
✔ Unified trend + volatility envelope on chart
✔ Individual component control (no clutter, no guesswork)
✔ Noise reduction in consolidation environments
✔ Adaptable to crypto, forex, indices, commodities, and equities
✔ Reliable for intraday impulse plays and structured directional setups
How to Use It
Context: Align your analysis with the broader bias before execution.
Signal: Watch for volatility expansion and trend alignment for breakout scenarios.
Execution: Apply your risk plan (position size, partials, BE/trailing) based on your trading model.
Best Practices
🛡️ Tune sensitivity according to asset volatility and timeframe horizon
🛡️ Avoid trading against dominant bias during compression phases
🛡️ Always validate through backtesting and forward testing before scaling
🛡️ Log performance and refine parameters iteratively
Who It's For
Traders who want:
A repeatable and disciplined process
A professional visual structure
Less noise, more clarity, better bias alignment
A premium indicator suite that supports real decision-making
Compatibility
Seamlessly works with any asset and timeframe on TradingView supporting chart overlay indicators. Alerts are designed to help monitoring without being glued to the screen.
Disclaimer ⚠️
This product is not financial advice and does not guarantee results. Performance varies depending on market conditions, asset behavior, user configuration, and applied risk management. Always trade responsibly and follow your own risk plan.
Gridbot Ping Pong🏓 Gridbot Ping Pong is a dynamic grid bot indicator that generates buy and sell signals as price oscillates between automatically calculated support and resistance levels. The grid adapts to trending markets through adjustable tilt and anchor parameters, which control the grid slope and shift resistance respectively. Entry signals trigger when price touches grid levels, while take profit and stop signals manage position exits. Unlike traditional grid bots that require horizontal ranges, this indicator maintains its oscillation zone as price trends by tilting and shifting the grid structure to follow momentum. The grid bot approach aims to accumulate gains through frequent touches across multiple grid levels rather than seeking large directional moves. Like a ping pong ball in motion, price oscillates between grid levels — each touch generates a signal.
⚡ THEORY & CONCEPTS ⚡
Grid trading is a systematic approach that places buy and sell orders at predetermined price intervals, creating a grid of orders above and below a set price level. In ranging markets, this method capitalizes on natural price oscillations by buying at lower grid levels and selling at higher ones. Each completed round trip between levels represents a captured opportunity, and the frequency of these oscillations determines the grid's effectiveness. Traditional grid bots excel when price remains within the defined range, methodically accumulating gains as price bounces between levels.
However, traditional grid structures face significant challenges when markets begin to trend. Fixed horizontal levels that performed well during consolidation become liabilities during directional moves. An uptrend leaves buy orders unfilled while sell orders trigger prematurely, and a downtrend creates the opposite problem. Extended trends can result in accumulated positions at increasingly unfavorable prices, with no mechanism to adapt to the new market reality. The static nature of traditional grids assumes markets will return to the mean, yet sustained breakouts regularly invalidate this assumption.
Gridbot Ping Pong addresses these limitations through dynamic grid adaptation. The tilt parameter angles the grid in the direction of the prevailing trend, aligning support and resistance levels with market momentum rather than fighting against it. The anchor parameter creates buffer zones beyond the outer grid boundaries, requiring price to demonstrate conviction before triggering a grid shift. When price breaks through these buffers, the entire grid recenters to the new price level. This combination of tilting grids and controlled shifting allows the indicator to maintain grid trading mechanics while acknowledging that markets trend.
The grid adapts through a downtrend and early reversal. Entry signals (▲▼), take profit signals (△▽), and grid shifts demonstrate the ping pong sequence as price oscillates between levels.
The grid structure consists of five levels: two potential support levels below, a center base price, and two potential resistance levels above. These levels are calculated as percentage intervals from a dynamic base price, with the spacing parameter determining the distance between each level. Trend direction is derived from consecutive grid shifts, where multiple shifts in the same direction confirm momentum. The grid restricts entries to the trend direction — buy signals in uptrends, sell signals in downtrends — while counter-trend signals convert to exits when appropriate.
Full market cycle demonstrating grid adaptation through rally, reversal, decline, and recovery. Buy signals dominate during uptrends, sell signals during downtrends, with take profits at boundaries throughout. Two stop signals mark the trend reversals.
Tilt
The tilt mechanic introduces slope to the grid structure based on trend direction and momentum. When consecutive shifts occur in the same direction, the tilt increases, creating a steeper grid that tracks with the trend. As the trend progresses, support levels rise with it — buy signals trigger on pullbacks to these rising levels rather than static levels abandoned by price. Similarly, resistance levels fall during downtrends, keeping sell signals relevant to current price action. If the trend reverses and shifts occur in the opposite direction, the tilt resets and begins building in the new direction. The tilt strength parameter controls how aggressively the grid slopes, with higher values producing steeper angles. Negative tilt values invert this relationship, angling the grid against the prevailing momentum rather than with it. This counter-trend configuration positions support levels lower during uptrends and resistance levels higher during downtrends, favoring mean reversion entries that anticipate pullbacks rather than continuation.
Negative tilt applied during an uptrend. Despite the bullish price action from late November through December, the grids slope downward, positioning buy signals at deeper support levels. Take profit signals appear at resistance as price reaches the upper grid boundaries before pulling back. The counter-trend configuration captures oscillations within the rising market rather than chasing momentum.
Anchor
The anchor mechanic provides resistance to grid shifting. Buffer zones extend beyond the outer grid boundaries, requiring price to demonstrate conviction before triggering a shift. Higher anchor values create larger buffers, requiring more significant price movement. As consecutive shifts confirm a trend, the pro-trend buffer shrinks, allowing the grid to follow momentum with increasing ease. This lets the indicator commit to established trends while resisting premature shifts during consolidations. Tilt and anchor work in complementary tension: tilt rewards momentum by angling the grid, while anchor resists excessive shifting by requiring price conviction to recenter. When price breaks through these buffers, the entire grid recenters to the new price level and play continues on a fresh table.
Steady uptrend with minimal tilt. The flat grid segments demonstrate that shifting alone keeps the grid aligned with price action. Buy signals (▲) and take profit signals (▽) alternate as price bounces between levels, accumulating gains through repetition across the entire move.
Sustained uptrend from June through September. The grid follows the trend with increasing ease as consecutive shifts reduce the pro-trend buffer. The October consolidation eventually triggers a downward shift and stop signal, but the system adapts to the renewed uptrend in November with fresh entry signals.
Signal Generation
The indicator generates three signal types. Entry signals (▲▼) trigger when price reaches a grid level in the direction of the trend, initiating a new position. Take profit signals (△▽) trigger when price reaches a grid level against the trend direction while a position is held, capturing gains as the rally continues. Stop signals (⦿) trigger when a grid shift occurs while holding a position adverse to the new shift direction. The ball goes off the table.
Trend reversal from bearish to bullish. The grid follows the downtrend through November with consecutive sell signals. A stop signal (⦿) triggers at the bottom as the grid shifts adversely against the held position. The system resets and adapts to the emerging uptrend in December, generating fresh buy signals as the new direction establishes.
Trigger Options
The signal trigger determines what price data the indicator uses to detect grid touches, balancing responsiveness against confirmation.
Auto : The default setting, using wick-based detection for pro-trend signals and close-based detection for counter-trend signals. This balances responsiveness when entering with the trend against confirmation when signaling against it.
Wick Touch : Generates signals in real-time when the high or low touches a grid level, providing the fastest response to price interaction.
Wick Reverse : Requires the wick to cross through the grid level from the previous bar, confirming the touch before signaling.
SWMA : Uses a Symmetrically Weighted Moving Average as the trigger source, generating signals only when the smoothed price crosses grid levels.
Close : Uses the bar's closing price as the trigger source, providing confirmed signals after each bar completes.
Symmetrically Weighted Moving Average (SWMA) trigger during a trend reversal. The smoothed price line filters intrabar noise, generating signals only when the SWMA crosses grid levels rather than reacting to wick touches. The grid follows the downtrend through November, resets at the bottom, and adapts to the emerging uptrend in December.
Signal Safeguards
The indicator includes built-in protections to reduce overtrading and mitigate risk, keeping the ball in play longer:
Boundary Protection : New entries are blocked at the outermost grid levels where breakout risk is highest. Exits remain permitted at these boundaries.
Signal Spacing : Signals maintain one-level separation from the most recent signal, preventing clusters of entries at similar prices.
Trend Alignment : When conflicting conditions arise, signals align with the prevailing trend direction rather than fighting momentum.
Automatic Profit Taking : Counter-trend interactions convert to take profit signals when a position is held, capturing gains rather than reversing exposure.
Adverse Shift Stops : When the grid shifts against a held position, a stop signal triggers to exit before further adverse movement.
Cautious Breakout Entries : On the first shift in a new direction, entries are restricted to favorable grid levels until the trend confirms through consecutive shifts.
Shift Resistance : Counter-trend shifts always require full buffer conviction, while pro-trend shifts become easier only after the trend is confirmed.
🛠️ CONFIGURATION & SETTINGS 🛠️
Core Parameters
SPACING (%) : Sets the percentage distance between grid levels. Higher values create wider grids with more room between signals, lower values create tighter grids with more frequent signal opportunities.
TRIGGER : Selects the price source for signal detection. See Trigger Options above.
TILT : Controls the grid slope factor in the trend direction.
ANCHOR : Controls resistance to grid shifting.
Visual Settings
GRIDS : Sets the colors for support (lower) and resistance (upper) grid levels.
FILL : Sets the gradient fill colors between the price line and outer grid boundaries.
SWMA : Sets the color of the Symmetrically Weighted Moving Average line.
🏓 PLAYING GRIDBOT PING PONG 🏓
⚪The objective is not to predict where price will go, but to be present at each level when it arrives.
⚪Each touch at a boundary counts. Gains accumulate through repetition, not single swings.
⚪The rally continues until it doesn't. When the ball goes off the table, the game resets.
⚪The grid creates boundaries where price bounces back and forth. The table is set — the ball does the work.
⚪Price oscillates between defined levels. The grid is the table. Everything else is just ping pong.
Tennis is a form of ping pong. In fact, tennis is ping pong played while standing on the table. In fact, all racquet games are nothing but derivatives of ping pong. — George Carlin
⚠️ DISCLAIMER ⚠️
The Gridbot Ping Pong indicator is a visual analysis tool designed to illustrate grid trading concepts and serve as a framework for understanding grid bot mechanics. While the indicator generates entry, exit, and stop signals, no guarantee is made regarding the profitability of these signals. Like all technical indicators, the grid levels and signals generated by this tool may appear to align with favorable trading opportunities in hindsight. However, these signals are not intended as standalone recommendations for trading decisions. This indicator is intended for educational and analytical purposes, complementing other tools and methods of market analysis.
🧠 BEYOND THE CODE 🧠
Gridbot Ping Pong is part of the Grid Bot Series, building on the concepts introduced in the Grid Bot Simulator , Grid Bot Auto , and Grid Bot Parabolic indicators. While those tools established the foundation for grid-based analysis, this indicator introduces dynamic tilt and anchor mechanics that adapt to trending market conditions.
This indicator shares the same educational philosophy as the Fibonacci Time-Price Zones and the Fibonacci Geometry Series - providing frameworks for understanding market concepts through visualization and experimentation rather than black-box signals.
The Gridbot Ping Pong indicator, like other xxattaxx indicators , is designed to encourage both education and community engagement. Feedback and insights are invaluable to refining and enhancing this tool. We look forward to the creative applications, observations, and discussions this indicator inspires within the trading community.
Velocity Divergence Radar [JOAT]
Velocity Divergence Radar - Momentum Physics Edition
Overview
Velocity Divergence Radar is an open-source oscillator indicator that applies physics concepts to market analysis. It calculates price velocity (rate of change), acceleration (rate of velocity change), and jerk (rate of acceleration change) to provide a multi-dimensional view of momentum. The indicator also includes divergence detection and force vector analysis.
What This Indicator Does
The indicator calculates and displays:
Velocity - Rate of price change over a configurable period, smoothed with EMA
Acceleration - Rate of velocity change, showing momentum shifts
Jerk (3rd Derivative) - Rate of acceleration change, indicating momentum stability
Force Vectors - Volume-weighted acceleration representing market force
Kinetic Energy - Calculated as 0.5 * mass (volume ratio) * velocity squared
Momentum Conservation - Tracks momentum relative to historical average
Divergence Detection - Identifies when price and velocity diverge at pivots
How It Works
Velocity is calculated as smoothed rate of change:
calculateVelocity(series float price, simple int period) =>
float roc = ta.roc(price, period)
float velocity = ta.ema(roc, period / 2)
velocity
Acceleration is the change in velocity:
calculateAcceleration(series float velocity, simple int period) =>
float accel = ta.change(velocity, period)
float smoothAccel = ta.ema(accel, period / 2)
smoothAccel
Jerk is the change in acceleration:
calculateJerk(series float acceleration, simple int period) =>
float jerk = ta.change(acceleration, period)
float smoothJerk = ta.ema(jerk, period / 2)
smoothJerk
Force is calculated using F = m * a (mass approximated by volume ratio):
calculateForceVector(series float mass, series float acceleration) =>
float force = mass * acceleration
float forceDirection = math.sign(force)
float forceMagnitude = math.abs(force)
Signal Generation
Signals are generated based on velocity behavior:
Bullish Divergence: Price makes lower low while velocity makes higher low
Bearish Divergence: Price makes higher high while velocity makes lower high
Velocity Cross: Velocity crosses above/below zero line
Extreme Velocity: Velocity exceeds 1.5x the upper/lower zone threshold
Jerk Extreme: Jerk exceeds 2x standard deviation
Force Extreme: Force magnitude exceeds 2x average
Dashboard Panel (Top-Right)
Velocity - Current velocity value
Acceleration - Current acceleration value
Momentum Strength - Combined velocity and acceleration strength
Radar Score - Composite score based on velocity and acceleration
Direction - STRONG UP/SLOWING UP/STRONG DOWN/SLOWING DOWN/FLAT
Jerk - Current jerk value
Force Vector - Current force magnitude
Kinetic Energy - Current kinetic energy value
Physics Score - Overall physics-based momentum score
Signal - Current actionable status
Visual Elements
Velocity Line - Main oscillator line with color based on direction
Velocity EMA - Smoothed velocity for trend reference
Acceleration Histogram - Bar chart showing acceleration direction
Jerk Area - Filled area showing jerk magnitude
Vector Magnitude - Line showing combined vector strength
Radar Scan - Oscillating pattern for visual effect
Zone Lines - Upper and lower threshold lines
Divergence Labels - BULL DIV / BEAR DIV markers
Extreme Markers - Triangles at velocity extremes
Input Parameters
Velocity Period (default: 14) - Period for velocity calculation
Acceleration Period (default: 7) - Period for acceleration calculation
Divergence Lookback (default: 10) - Bars to scan for divergence
Radar Sensitivity (default: 1.0) - Zone threshold multiplier
Jerk Analysis (default: true) - Enable 3rd derivative calculation
Force Vectors (default: true) - Enable force analysis
Kinetic Energy (default: true) - Enable energy calculation
Momentum Conservation (default: true) - Enable momentum tracking
Suggested Use Cases
Identify momentum direction using velocity sign and magnitude
Watch for divergences as potential reversal warnings
Use acceleration to detect momentum shifts before price confirms
Monitor jerk for momentum stability assessment
Combine force and kinetic energy for conviction analysis
Timeframe Recommendations
Works on all timeframes. Higher timeframes provide smoother readings; lower timeframes show more granular momentum changes.
Limitations
Physics analogies are conceptual and not literal market physics
Divergence detection uses pivot-based lookback and may lag
Force calculation uses volume ratio as mass proxy
Kinetic energy is a derived metric, not actual energy
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always use proper risk management.
- Made with passion by officialjackofalltrades
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Mid-term RibbonWhat the indicator is meant to tell you
-Mid-term trend direction (bullish vs bearish)
-Trend transitions when the ribbon flips color
-Trend strength (wider ribbon = stronger momentum)
-Helps traders stay in trends longer and avoid chop
Typical use cases
-Trend-following entries and exits
-Filtering trades in the direction of the ribbon
-Visual confirmation for other signals
-Swing trading and position trading
Colors are customizable
Only for educational purposes, no recommendation to buy or sell
Polynomial Regression Channel [ChartPrime]⯁ OVERVIEW
The Polynomial Regression Channel fits price action using advanced polynomial regression, extending beyond simple linear or logarithmic models. By leveraging matrix calculations, it builds a curved regression line that adapts to swings more naturally. The channel includes extrapolated forward projections, helping traders visualize where price may gravitate in the near future. Midline color shifts reflect directional bias, while prediction ranges are marked with dashed extensions, labeled prices, and a live table for clarity.
⯁ KEY FEATURES
Polynomial Regression Core:
Uses matrix algebra to calculate a polynomial fit of customizable degree, adapting to complex, non-linear market structures.
polyreg(source, length, degree, extrapolate) =>
total = length + extrapolate
X_all = matrix.new(total, degree + 1, 0.0)
for i = 0 to total - 1
for j = 0 to degree
matrix.set(X_all, i, j, math.pow(i, j))
// y (length × 1), oldest→newest over the fit window
y = matrix.new(length, 1, 0.0)
for i = 0 to length - 1
matrix.set(y, i, 0, source )
// X_train (first `length` rows of X_all)
X_tr = matrix.new(length, degree + 1, 0.0)
for i = 0 to length - 1
for j = 0 to degree
matrix.set(X_tr, i, j, matrix.get(X_all, i, j))
// OLS via normal equations: (X'X)^(-1)b = X'y ⇒ b = (X'X)^(-1) X'y
Xt = matrix.transpose(X_tr) // X'
XtX = matrix.mult(Xt, X_tr) // (X'X)
Xty = matrix.mult(Xt, y) // X'y
XtX_inv = matrix.inv(XtX) // (X'X)^(-1)
b = matrix.mult(XtX_inv, Xty) // b = (X'X)^(-1) X'y
// Predictions for all rows (fit + extrap)
preds = matrix.mult(X_all, matrix.col(b,0))
preds
Extrapolated Future Projections:
Forward-looking range (dashed lines + circular markers) shows where the fitted polynomial suggests price may move.
Dynamic Midline Coloring:
Regression midline shifts green when slope turns upward and magenta when slope turns downward, giving instant directional context.
Channel Boundaries:
Upper and lower levels expand from the midline using a volatility-based offset, framing potential overbought and oversold conditions.
Top-Right Data Table:
A live table displays Upper, Middle, and Lower Prediction values, updating in real time for quick reference without scanning the chart.
⯁ USAGE
Use the regression midline to gauge underlying market bias; green slopes suggest continuation, magenta slopes caution for weakness.
Watch dashed extrapolated ranges as potential targets or reaction zones during upcoming sessions.
Price labels and table values act as precise reference levels for planning entries, exits, or stop placement.
Increase Degree for more curve-fitting on choppy markets, or keep it low for broader trend approximation.
Adjust Period and Extrapolate length to balance stability vs. responsiveness.
⯁ CONCLUSION
The Polynomial Regression Channel offers a mathematically advanced way to visualize price trends and anticipate future paths. With matrix-driven polynomial fitting, extrapolated projections, and integrated live labels, it combines statistical rigor with practical trading visuals — a robust upgrade over standard regression channels.
