GLD GC Price Converter Its primary function is to fetch the prices of the Gold ETF (ticker: GLD) and Gold Futures (ticker: GC1!) and then project significant price levels from one or both of these assets onto the chart of whatever instrument you are currently viewing.
Core Functionality & Features
Dual Asset Tracking: The script simultaneously tracks the prices of GLD and Gold Futures (GC).
Dynamic Price Level Projection: The script's main feature is its ability to calculate and draw horizontal price levels. It determines a "base price" (e.g., the nearest $100 level for GC) and then draws lines at specified increments above and below it. The key is that these levels are projected onto the current chart's price scale.
On-Chart Information Display:
Price Table: A customizable table can be displayed in any corner of the chart, showing the current prices of GLD and GC. It can also show the daily percentage change for GC, colored green for positive changes and red for negative ones.
Last Price Label: It can show a label next to the most recent price bar that displays the current prices of both GLD and GC.
Extensive Customization: The user has significant control over the indicator's appearance and behavior through the settings panel.
This includes:
Toggling the display for GLD and GC levels independently.
Adjusting the multiplier for the price levels (e.g., show levels every $100 or $50 for GC).
Changing the colors, line styles (solid, dashed, dotted), and horizontal offset for the labels.
Defining the number of price levels to display.
Controlling the text size for labels and the table.
Choosing whether the script updates on every tick or only once per candle close for better performance.
在脚本中搜索"文华财经tick价格"
AsturRiskPanelIndicator Summary
ATR Engine
Length & Smoothing: Choose how many bars to use (default 14) and the smoothing method (RMA/SMA/EMA/WMA).
Median ATR: Computes a rolling median of ATR over a user-defined look-back (default 14) to derive a “scalp” target.
Scalp Target
Automatically set at ½ × median ATR, snapped to the nearest tick.
Optional rounding to whole points for simplicity.
Stop Calculation
ATR Multiplier: Scales current ATR by a user input (default 1.5) to produce your stop distance in points (and ticks when appropriate).
Distortion Handling: Switches between point-only and point + tick displays based on contract specifications.
Risk & Sizing
Risk % of account per trade (default 2 %).
Calculates dollar risk per contract and optimal contract count.
Displays all metrics (scalp, stop, risk/contract, max contracts, max risk, account size) in a customizable on-chart table.
ATR-Based Stop Placement Guidelines
Trade Context ATR Multiplier Notes
Tight Range Entry 1.0 × ATR High-conviction, precise entries. Expect more shake-outs.
Standard Trend Entry 1.5 × ATR Balanced for H2/L2, MTR, DT/DB entries.
Breakouts/Microchannels 2.0 × ATR Wide stops through chop—Brooks-style breathing room.
How to Use
Select ATR Settings
Pick an ATR length (e.g. 14) and smoothing (RMA for stability).
Adjust the median length if you want a faster/slower scalp line.
Align Multiplier with Your Setup
For tight-range entries, set ATR Multiplier ≈ 1.0.
For standard trend trades, leave at 1.5.
For breakout/pullback setups, increase to 2.0 or more.
Customize Risk Parameters
Enter your account size and desired risk % per trade (e.g. 2 %).
The table auto-calculates how many contracts you can take.
Read the On-Chart Table
Scalp shows your intraday target.
Stop gives Brooks-style stop distance in points (and ticks).
Risk/Contract is the dollar risk per contract.
Max Contracts tells you maximum position size.
Max Risk confirms total dollar exposure.
Visual Confirmation
Place your entry, then eyeball the scalp and stop levels against chart structure (e.g. swing highs/lows).
Adjust the ATR multiplier if market context shifts (e.g. volatility spikes).
By blending this sizing panel with contextual ATR multipliers, you’ll consistently give your trades the right amount of “breathing room” while keeping risk in check.
Entropy Chart Analysis [PhenLabs]📊 Entropy Chart analysis -
Version: PineScript™ v6
📌 Description
The Entropy Chart indicator analysis applies Approximate Entropy (ApEn) to identify zones of potential support and resistance on your price chart. It is designed to locate changes in the market’s predictability, with a focus on zones near significant psychological price levels (e.g., multiples of 50). By quantifying entropy, the indicator aims to identify zones where price action might stabilize (potential support) or become randomized (potential resistance).
This tool automates the visualization of these key areas for traders, which may have the effect of revealing reversal levels or consolidation zones that would be hard to discern through traditional means. It also filters the signals by proximity to key levels in an attempt to reduce noise and highlight higher-probability setups. These dynamic zones adapt to changing market conditions by stretching, merging, and expiring based on user-inputted rules.
🚀 Points of Innovation
Combines Approximate Entropy (ApEn) calculation with price action near significant levels.
Filters zone signals based on proximity (in ticks) to predefined significant price levels (multiples of 50).
Dynamically merges overlapping or nearby zones to consolidate signals and reduce chart clutter.
Uses ApEn crossovers relative to its moving average as the core trigger mechanism.
Provides distinct visual coloring for bullish, bearish, and merged (mixed-signal) zones.
Offers comprehensive customization for entropy calculation, zone sensitivity, level filtering, and visual appearance.
🔧 Core Components
Approximate Entropy (ApEn) Calculation : Measures the regularity or randomness of price fluctuations over a specified window. Low ApEn suggests predictability, while high ApEn suggests randomness.
Zone Trigger Logic : Creates potential support zones when ApEn crosses below its average (indicating increasing predictability) and potential resistance zones when it crosses above (indicating increasing randomness).
Significant Level Filter : Validates zone triggers only if they occur within a user-defined tick distance from significant price levels (multiples of 50).
Dynamic Zone Management : Automatically creates, extends, merges nearby zones based on tick distance, and removes the oldest zones to maintain a maximum limit.
Zone Visualization : Draws and updates colored boxes on the chart to represent active support, resistance, or mixed zones.
🔥 Key Features
Entropy-Based S/R Detection : Uses ApEn to identify potential support (low entropy) and resistance (high entropy) areas.
Significant Level Filtering : Enhances signal quality by focusing on entropy changes near key psychological price points.
Automatic Zone Drawing & Merging : Visualizes zones dynamically, merging close signals for clearer interpretation.
Highly Customizable : Allows traders to adjust parameters for ApEn calculation, zone detection thresholds, level filter sensitivity, merging distance, and visual styles.
Integrated Alerts : Provides built-in alert conditions for the formation of new bullish or bearish zones near significant levels.
Clear Visual Output : Uses distinct, customizable colors for buy (support), sell (resistance), and mixed (merged) zones.
🎨 Visualization
Buy Zones : Represented by greenish boxes (default: #26a69a), indicating potential support areas formed during low entropy periods near significant levels.
Sell Zones : Represented by reddish boxes (default: #ef5350), indicating potential resistance areas formed during high entropy periods near significant levels.
Mixed Zones : Represented by bluish/purple boxes (default: #8894ff), formed when a buy zone and a sell zone merge, indicating areas of potential consolidation or conflict.
Dynamic Extension : Active zones are automatically extended to the right with each new bar.
📖 Usage Guidelines
Calculation Parameters
Window Length
Default: 15
Range: 10-100
Description: Lookback period for ApEn calculation. Shorter lengths are more responsive; longer lengths are smoother.
Embedding Dimension (m)
Default: 2
Range: 1-6
Description: Length of patterns compared in ApEn calculation. Higher values detect more complex patterns but require more data.
Tolerance (r)
Default: 0.5
Range: 0.1-1.0 (step 0.1)
Description: Sensitivity factor for pattern matching (as a multiple of standard deviation). Lower values require closer matches (more sensitive).
Zone Settings
Zone Lookback
Default: 5
Range: 5-50
Description: Lookback period for the moving average of ApEn used in threshold calculations.
Zone Threshold
Default: 0.5
Range: 0.5-3.0
Description: Multiplier for the ApEn average to set crossover trigger levels. Higher values require larger ApEn deviations to create zones.
Maximum Zones
Default: 5
Range: 1-10
Description: Maximum number of active zones displayed. The oldest zones are removed first when the limit is reached.
Zone Merge Distance (Ticks)
Default: 5
Range: 1-50
Description: Maximum distance in ticks for two separate zones to be merged into one.
Level Filter Settings
Tick Size
Default: 0.25
Description: The minimum price increment for the asset. Must be set correctly for the specific instrument to ensure accurate level filtering.
Max Ticks Distance from Levels
Default: 40
Description: Maximum allowed distance (in ticks) from a significant level (multiple of 50) for a zone trigger to be valid.
Visual Settings
Buy Zone Color : Default: color.new(#26a69a, 83). Sets the fill color for support zones.
Sell Zone Color : Default: color.new(#ef5350, 83). Sets the fill color for resistance zones.
Mixed Zone Color : Default: color.new(#8894ff, 83). Sets the fill color for merged zones.
Buy Border Color : Default: #26a69a. Sets the border color for support zones.
Sell Border Color : Default: #ef5350. Sets the border color for resistance zones.
Mixed Border Color : Default: color.new(#a288ff, 50). Sets the border color for mixed zones.
Border Width : Default: 1, Range: 1-3. Sets the thickness of zone borders.
✅ Best Use Cases
Identifying potential support/resistance near significant psychological price levels (e.g., $50, $100 increments).
Detecting potential market turning points or consolidation zones based on shifts in price predictability.
Filtering entries or exits by confirming signals occurring near significant levels identified by the indicator.
Adding context to other technical analysis approaches by highlighting entropy-derived zones.
⚠️ Limitations
Parameter Dependency : Indicator performance is sensitive to parameter settings ( Window Length , Tolerance , Zone Threshold , Max Ticks Distance ), which may need optimization for different assets and timeframes.
Volatility Sensitivity : High market volatility or erratic price action can affect ApEn calculations and potentially lead to less reliable zone signals.
Fixed Level Filter : The significant level filter is based on multiples of 50. While common, this may not capture all relevant levels for every asset or market condition. Accurate Tick Size input is essential.
Not Standalone : Should be used in conjunction with other analysis methods (price action, volume, other indicators) for confirmation, not as a sole basis for trading decisions.
💡 What Makes This Unique
Entropy + Level Context : Uniquely combines ApEn analysis with a specific filter for proximity to significant price levels (multiples of 50), adding locational context to entropy signals.
Intelligent Zone Merging : Automatically consolidates nearby buy/sell zones based on tick distance, simplifying visual analysis and highlighting stronger confluence areas.
Targeted Signal Generation : Focuses alerts and zone creation on specific market conditions (entropy shifts near key levels).
🔬 How It Works
Calculate Entropy : The script computes the Approximate Entropy (ApEn) of the closing prices over the defined Window Length to quantify price predictability.
Check Triggers : It monitors ApEn relative to its moving average. A crossunder below a calculated threshold (avg_apen / zone_threshold) indicates potential support; a crossover above (avg_apen * zone_threshold) indicates potential resistance.
Filter by Level : A potential zone trigger is confirmed only if the low (for support) or high (for resistance) of the trigger bar is within the Max Ticks Distance of a significant price level (multiple of 50).
Manage & Draw Zones : If a trigger is confirmed, a new zone box is created. The script checks for overlaps with existing zones within the Zone Merge Distance and merges them if necessary. Zones are extended forward, and the oldest are removed to respect the Maximum Zones limit. Active zones are drawn and updated on the chart.
💡 Note:
Crucially, set the Tick Size parameter correctly for your specific trading instrument in the “Level Filter Settings”. Incorrect Tick Size will make the significant level filter inaccurate.
Experiment with parameters, especially Window Length , Tolerance (r) , Zone Threshold , and Max Ticks Distance , to tailor the indicator’s sensitivity to your preferred asset and timeframe.
Always use this indicator as part of a comprehensive trading plan, incorporating risk management and seeking confirmation from other analysis techniques.
Dskyz (DAFE) Adaptive Regime - Quant Machine ProDskyz (DAFE) Adaptive Regime - Quant Machine Pro:
Buckle up for the Dskyz (DAFE) Adaptive Regime - Quant Machine Pro, is a strategy that’s your ultimate edge for conquering futures markets like ES, MES, NQ, and MNQ. This isn’t just another script—it’s a quant-grade powerhouse, crafted with precision to adapt to market regimes, deliver multi-factor signals, and protect your capital with futures-tuned risk management. With its shimmering DAFE visuals, dual dashboards, and glowing watermark, it turns your charts into a cyberpunk command center, making trading as thrilling as it is profitable.
Unlike generic scripts clogging up the space, the Adaptive Regime is a DAFE original, built from the ground up to tackle the chaos of futures trading. It identifies market regimes (Trending, Range, Volatile, Quiet) using ADX, Bollinger Bands, and HTF indicators, then fires trades based on a weighted scoring system that blends candlestick patterns, RSI, MACD, and more. Add in dynamic stops, trailing exits, and a 5% drawdown circuit breaker, and you’ve got a system that’s as safe as it is aggressive. Whether you’re a newbie or a prop desk pro, this strat’s your ticket to outsmarting the markets. Let’s break down every detail and see why it’s a must-have.
Why Traders Need This Strategy
Futures markets are a gauntlet—fast moves, volatility spikes (like the April 28, 2025 NQ 1k-point drop), and institutional traps that punish the unprepared. Meanwhile, platforms are flooded with low-effort scripts that recycle old ideas with zero innovation. The Adaptive Regime stands tall, offering:
Adaptive Intelligence: Detects market regimes (Trending, Range, Volatile, Quiet) to optimize signals, unlike one-size-fits-all scripts.
Multi-Factor Precision: Combines candlestick patterns, MA trends, RSI, MACD, volume, and HTF confirmation for high-probability trades.
Futures-Optimized Risk: Calculates position sizes based on $ risk (default: $300), with ATR or fixed stops/TPs tailored for ES/MES.
Bulletproof Safety: 5% daily drawdown circuit breaker and trailing stops keep your account intact, even in chaos.
DAFE Visual Mastery: Pulsing Bollinger Band fills, dynamic SL/TP lines, and dual dashboards (metrics + position) make signals crystal-clear and charts a work of art.
Original Craftsmanship: A DAFE creation, built with community passion, not a rehashed clone of generic code.
Traders need this because it’s a complete, adaptive system that blends quant smarts, user-friendly design, and DAFE flair. It’s your edge to trade with confidence, cut through market noise, and leave the copycats in the dust.
Strategy Components
1. Market Regime Detection
The strategy’s brain is its ability to classify market conditions into five regimes, ensuring signals match the environment.
How It Works:
Trending (Regime 1): ADX > 20, fast/slow EMA spread > 0.3x ATR, HTF RSI > 50 or MACD bullish (htf_trend_bull/bear).
Range (Regime 2): ADX < 25, price range < 3% of close, no HTF trend.
Volatile (Regime 3): BB width > 1.5x avg, ATR > 1.2x avg, HTF RSI overbought/oversold.
Quiet (Regime 4): BB width < 0.8x avg, ATR < 0.9x avg.
Other (Regime 5): Default for unclear conditions.
Indicators: ADX (14), BB width (20), ATR (14, 50-bar SMA), HTF RSI (14, daily default), HTF MACD (12,26,9).
Why It’s Brilliant:
Regime detection adapts signals to market context, boosting win rates in trending or volatile conditions.
HTF RSI/MACD add a big-picture filter, rare in basic scripts.
Visualized via gradient background (green for Trending, orange for Range, red for Volatile, gray for Quiet, navy for Other).
2. Multi-Factor Signal Scoring
Entries are driven by a weighted scoring system that combines candlestick patterns, trend, momentum, and volume for robust signals.
Candlestick Patterns:
Bullish: Engulfing (0.5), hammer (0.4 in Range, 0.2 else), morning star (0.2), piercing (0.2), double bottom (0.3 in Volatile, 0.15 else). Must be near support (low ≤ 1.01x 20-bar low) with volume spike (>1.5x 20-bar avg).
Bearish: Engulfing (0.5), shooting star (0.4 in Range, 0.2 else), evening star (0.2), dark cloud (0.2), double top (0.3 in Volatile, 0.15 else). Must be near resistance (high ≥ 0.99x 20-bar high) with volume spike.
Logic: Patterns are weighted higher in specific regimes (e.g., hammer in Range, double bottom in Volatile).
Additional Factors:
Trend: Fast EMA (20) > slow EMA (50) + 0.5x ATR (trend_bull, +0.2); opposite for trend_bear.
RSI: RSI (14) < 30 (rsi_bull, +0.15); > 70 (rsi_bear, +0.15).
MACD: MACD line > signal (12,26,9, macd_bull, +0.15); opposite for macd_bear.
Volume: ATR > 1.2x 50-bar avg (vol_expansion, +0.1).
HTF Confirmation: HTF RSI < 70 and MACD bullish (htf_bull_confirm, +0.2); RSI > 30 and MACD bearish (htf_bear_confirm, +0.2).
Scoring:
bull_score = sum of bullish factors; bear_score = sum of bearish. Entry requires score ≥ 1.0.
Example: Bullish engulfing (0.5) + trend_bull (0.2) + rsi_bull (0.15) + htf_bull_confirm (0.2) = 1.05, triggers long.
Why It’s Brilliant:
Multi-factor scoring ensures signals are confirmed by multiple market dynamics, reducing false positives.
Regime-specific weights make patterns more relevant (e.g., hammers shine in Range markets).
HTF confirmation aligns with the big picture, a quant edge over simplistic scripts.
3. Futures-Tuned Risk Management
The risk system is built for futures, calculating position sizes based on $ risk and offering flexible stops/TPs.
Position Sizing:
Logic: Risk per trade (default: $300) ÷ (stop distance in points * point value) = contracts, capped at max_contracts (default: 5). Point value = tick value (e.g., $12.5 for ES) * ticks per point (4) * contract multiplier (1 for ES, 0.1 for MES).
Example: $300 risk, 8-point stop, ES ($50/point) → 0.75 contracts, rounded to 1.
Impact: Precise sizing prevents over-leverage, critical for micro contracts like MES.
Stops and Take-Profits:
Fixed: Default stop = 8 points, TP = 16 points (2:1 reward/risk).
ATR-Based: Stop = 1.5x ATR (default), TP = 3x ATR, enabled via use_atr_for_stops.
Logic: Stops set at swing low/high ± stop distance; TPs at 2x stop distance from entry.
Impact: ATR stops adapt to volatility, while fixed stops suit stable markets.
Trailing Stops:
Logic: Activates at 50% of TP distance. Trails at close ± 1.5x ATR (atr_multiplier). Longs: max(trail_stop_long, close - ATR * 1.5); shorts: min(trail_stop_short, close + ATR * 1.5).
Impact: Locks in profits during trends, a game-changer in volatile sessions.
Circuit Breaker:
Logic: Pauses trading if daily drawdown > 5% (daily_drawdown = (max_equity - equity) / max_equity).
Impact: Protects capital during black swan events (e.g., April 27, 2025 ES slippage).
Why It’s Brilliant:
Futures-specific inputs (tick value, multiplier) make it plug-and-play for ES/MES.
Trailing stops and circuit breaker add pro-level safety, rare in off-the-shelf scripts.
Flexible stops (ATR or fixed) suit different trading styles.
4. Trade Entry and Exit Logic
Entries and exits are precise, driven by bull_score/bear_score and protected by drawdown checks.
Entry Conditions:
Long: bull_score ≥ 1.0, no position (position_size <= 0), drawdown < 5% (not pause_trading). Calculates contracts, sets stop at swing low - stop points, TP at 2x stop distance.
Short: bear_score ≥ 1.0, position_size >= 0, drawdown < 5%. Stop at swing high + stop points, TP at 2x stop distance.
Logic: Tracks entry_regime for PNL arrays. Closes opposite positions before entering.
Exit Conditions:
Stop-Loss/Take-Profit: Hits stop or TP (strategy.exit).
Trailing Stop: Activates at 50% TP, trails by ATR * 1.5.
Emergency Exit: Closes if price breaches stop (close < long_stop_price or close > short_stop_price).
Reset: Clears stop/TP prices when flat (position_size = 0).
Why It’s Brilliant:
Score-based entries ensure multi-factor confirmation, filtering out weak signals.
Trailing stops maximize profits in trends, unlike static exits in basic scripts.
Emergency exits add an extra safety layer, critical for futures volatility.
5. DAFE Visuals
The visuals are pure DAFE magic, blending function with cyberpunk flair to make signals intuitive and charts stunning.
Shimmering Bollinger Band Fill:
Display: BB basis (20, white), upper/lower (green/red, 45% transparent). Fill pulses (30–50 alpha) by regime, with glow (60–95 alpha) near bands (close ≥ 0.995x upper or ≤ 1.005x lower).
Purpose: Highlights volatility and key levels with a futuristic glow.
Visuals make complex regimes and signals instantly clear, even for newbies.
Pulsing effects and regime-specific colors add a DAFE signature, setting it apart from generic scripts.
BB glow emphasizes tradeable levels, enhancing decision-making.
Chart Background (Regime Heatmap):
Green — Trending Market: Strong, sustained price movement in one direction. The market is in a trend phase—momentum follows through.
Orange — Range-Bound: Market is consolidating or moving sideways, with no clear up/down trend. Great for mean reversion setups.
Red — Volatile Regime: High volatility, heightened risk, and larger/faster price swings—trade with caution.
Gray — Quiet/Low Volatility: Market is calm and inactive, with small moves—often poor conditions for most strategies.
Navy — Other/Neutral: Regime is uncertain or mixed; signals may be less reliable.
Bollinger Bands Glow (Dynamic Fill):
Neon Red Glow — Warning!: Price is near or breaking above the upper band; momentum is overstretched, watch for overbought conditions or reversals.
Bright Green Glow — Opportunity!: Price is near or breaking below the lower band; market could be oversold, prime for bounce or reversal.
Trend Green Fill — Trending Regime: Fills between bands with green when the market is trending, showing clear momentum.
Gold/Yellow Fill — Range Regime: Fills with gold/aqua in range conditions, showing the market is sideways/oscillating.
Magenta/Red Fill — Volatility Spike: Fills with vivid magenta/red during highly volatile regimes.
Blue Fill — Neutral/Quiet: A soft blue glow for other or uncertain market states.
Moving Averages:
Display: Blue fast EMA (20), red slow EMA (50), 2px.
Purpose: Shows trend direction, with trend_dir requiring ATR-scaled spread.
Dynamic SL/TP Lines:
Display: Pulsing colors (red SL, green TP for Trending; yellow/orange for Range, etc.), 3px, with pulse_alpha for shimmer.
Purpose: Tracks stops/TPs in real-time, color-coded by regime.
6. Dual Dashboards
Two dashboards deliver real-time insights, making the strat a quant command center.
Bottom-Left Metrics Dashboard (2x13):
Metrics: Mode (Active/Paused), trend (Bullish/Bearish/Neutral), ATR, ATR avg, volume spike (YES/NO), RSI (value + Oversold/Overbought/Neutral), HTF RSI, HTF trend, last signal (Buy/Sell/None), regime, bull score.
Display: Black (29% transparent), purple title, color-coded (green for bullish, red for bearish).
Purpose: Consolidates market context and signal strength.
Top-Right Position Dashboard (2x7):
Metrics: Regime, position side (Long/Short/None), position PNL ($), SL, TP, daily PNL ($).
Display: Black (29% transparent), purple title, color-coded (lime for Long, red for Short).
Purpose: Tracks live trades and profitability.
Why It’s Brilliant:
Dual dashboards cover market context and trade status, a rare feature.
Color-coding and concise metrics guide beginners (e.g., green “Buy” = go).
Real-time PNL and SL/TP visibility empower disciplined trading.
7. Performance Tracking
Logic: Arrays (regime_pnl_long/short, regime_win/loss_long/short) track PNL and win/loss by regime (1–5). Updated on trade close (barstate.isconfirmed).
Purpose: Prepares for future adaptive thresholds (e.g., adjust bull_score min based on regime performance).
Why It’s Brilliant: Lays the groundwork for self-optimizing logic, a quant edge over static scripts.
Key Features
Regime-Adaptive: Optimizes signals for Trending, Range, Volatile, Quiet markets.
Futures-Optimized: Precise sizing for ES/MES with tick-based risk inputs.
Multi-Factor Signals: Candlestick patterns, RSI, MACD, and HTF confirmation for robust entries.
Dynamic Exits: ATR/fixed stops, 2:1 TPs, and trailing stops maximize profits.
Safe and Smart: 5% drawdown breaker and emergency exits protect capital.
DAFE Visuals: Shimmering BB fill, pulsing SL/TP, and dual dashboards.
Backtest-Ready: Fixed qty and tick calc for accurate historical testing.
How to Use
Add to Chart: Load on a 5min ES/MES chart in TradingView.
Configure Inputs: Set instrument (ES/MES), tick value ($12.5/$1.25), multiplier (1/0.1), risk ($300 default). Enable ATR stops for volatility.
Monitor Dashboards: Bottom-left for regime/signals, top-right for position/PNL.
Backtest: Run in strategy tester to compare regimes.
Live Trade: Connect to Tradovate or similar. Watch for slippage (e.g., April 27, 2025 ES issues).
Replay Test: Try April 28, 2025 NQ drop to see regime shifts and stops.
Disclaimer
Trading futures involves significant risk of loss and is not suitable for all investors. Past performance does not guarantee future results. Backtest results may differ from live trading due to slippage, fees, or market conditions. Use this strategy at your own risk, and consult a financial advisor before trading. Dskyz (DAFE) Trading Systems is not responsible for any losses incurred.
Backtesting:
Frame: 2023-09-20 - 2025-04-29
Slippage: 3
Fee Typical Range (per side, per contract)
CME Exchange $1.14 – $1.20
Clearing $0.10 – $0.30
NFA Regulatory $0.02
Firm/Broker Commis. $0.25 – $0.80 (retail prop)
TOTAL $1.60 – $2.30 per side
Round Turn: (enter+exit) = $3.20 – $4.60 per contract
Final Notes
The Dskyz (DAFE) Adaptive Regime - Quant Machine Pro is more than a strategy—it’s a revolution. Crafted with DAFE’s signature precision, it rises above generic scripts with adaptive regimes, quant-grade signals, and visuals that make trading a thrill. Whether you’re scalping MES or swinging ES, this system empowers you to navigate markets with confidence and style. Join the DAFE crew, light up your charts, and let’s dominate the futures game!
(This publishing will most likely be taken down do to some miscellaneous rule about properly displaying charting symbols, or whatever. Once I've identified what part of the publishing they want to pick on, I'll adjust and repost.)
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
Created by Dskyz, powered by DAFE Trading Systems. Trade smart, trade bold.
position_toolLibrary "position_tool"
Trying to turn TradingView's position tool into a library from which you can draw position tools for your strategies on the chart. Not sure if this is going to work
calcBaseUnit()
Calculates the chart symbol's base unit of change in asset prices.
Returns: (float) A ticks or pips value of base units of change.
calcOrderPipsOrTicks(orderSize, unit)
Converts the `orderSize` to ticks.
Parameters:
orderSize (float) : (series float) The order size to convert to ticks.
unit (simple float) : (simple float) The basic units of change in asset prices.
Returns: (int) A tick value based on a given order size.
calcProfitLossSize(price, entryPrice, isLongPosition)
Calculates a difference between a `price` and the `entryPrice` in absolute terms.
Parameters:
price (float) : (series float) The price to calculate the difference from.
entryPrice (float) : (series float) The price of entry for the position.
isLongPosition (bool)
Returns: (float) The absolute price displacement of a price from an entry price.
calcRiskRewardRatio(profitSize, lossSize)
Calculates a risk to reward ratio given the size of profit and loss.
Parameters:
profitSize (float) : (series float) The size of the profit in absolute terms.
lossSize (float) : (series float) The size of the loss in absolute terms.
Returns: (float) The ratio between the `profitSize` to the `lossSize`
createPosition(entryPrice, entryTime, tpPrice, slPrice, entryColor, tpColor, slColor, textColor, showExtendRight)
Main function to create a position visualization with entry, TP, and SL
Parameters:
entryPrice (float) : (float) The entry price of the position
entryTime (int) : (int) The entry time of the position in bar_time format
tpPrice (float) : (float) The take profit price
slPrice (float) : (float) The stop loss price
entryColor (color) : (color) Color for entry line
tpColor (color) : (color) Color for take profit zone
slColor (color) : (color) Color for stop loss zone
textColor (color) : (color) Color for text labels
showExtendRight (bool) : (bool) Whether to extend lines to the right
Returns: (bool) Returns true when position is closed
GRID EXTENSIONGRID EXTENSION
Overview
The GRID EXTENSION is a simple grid-based indicator for TradingView, built with Pine Script v6. It plots horizontal price levels starting from a user-defined anchor price, with spacing set by a tick increment. Use it to identify key support, resistance, or price zones on charts for Crypto, Forex, or Futures.
Key Features
Custom Grid Levels: Plot up to 22 levels (e.g., 0, 0.25, 1.25, -2.50) with options to show/hide, set values, and choose colors.
Market-Specific Tick Increments: Select your asset type (Crypto, Forex, Futures) and choose from a range of tick increments tailored for each market:
Crypto: 1 to 5000 ticks (e.g., 100 ticks = $0.001 on ADA/USD, 5000 ticks = $50 on BTC/USD).
Forex: 5 to 5000 ticks (e.g., 100 ticks = 1 pip on EUR/USD, 5000 ticks = 50 pips).
Futures: 1 to 2500 ticks (e.g., 25 ticks = 6.25 points on E-mini S&P 500, $312.50 per contract).
Visual Options:
Extend lines to the right.
Show price and level labels (as values or percentages).
Place labels on the left or right.
Adjust background transparency for filled areas between levels.
How to Use
Set Asset Type: Choose "Crypto," "Forex," or "Futures" to match your chart.
Set Anchor Price: Enter a starting price for the grid.
Pick Tick Increment: Select a tick increment from the dropdown, following the guidance for your asset type (see Key Features).
Customize Levels: Turn levels on/off, set values, and pick colors.
Add to Chart: Apply the indicator to see the grid on your chart.
Tips
Use levels to mark support/resistance zones for entries or exits.
Extend lines to project future price zones.
Choose smaller increments (e.g., 5 ticks) for scalping, or larger ones (e.g., 1000 ticks) for swing trading.
Combine with indicators like moving averages for better signals.
Settings
Asset Type: Select "Crypto," "Forex," or "Futures" (default: "Crypto").
Anchor Price: Starting price for the grid (default: 0.0).
Tick Increment: Space between levels (options: 1, 5, 10, 25, 50, 100, 250, 500, 1000, 2500, 5000). Choose based on asset type.
Extend Right: Extend lines to the right (default: true).
Show Prices: Show price labels (default: true).
Show Levels: Show level values or percentages (default: true).
Format: Display levels as "Values" or "Percent" (default: "Values").
Labels Position: Place labels on "Left" or "Right" (default: "Left").
Background Transparency: Set transparency for filled areas (default: 100, range 0-100).
Level Options: Enable/disable levels, set values, and choose colors.
Notes
Set the anchor price to a key level (like a recent high or low) for best results.
Check the tick increment tooltip to ensure the spacing suits your market type.
Works on any chart, best for clear price trends or ranges.
Acknowledgments
Made with Pine Script v6 for TradingView. This is v1.0—feedback welcome for future updates!
TickerLibLibrary "TickerLib"
Ticker Library
exists(tickerId)
Test if a tickerId exists
Parameters:
tickerId (string)
Returns: (bool)
notExist(tickerId)
Test if a tickerId do not exists
Parameters:
tickerId (string)
Returns: (bool)
getExchange(tickerId)
Pass a tickerId return the exchange
Parameters:
tickerId (string)
Returns: (string) exchange
isPerp(tickerId)
Test if tickerId is a perps pair
Parameters:
tickerId (string)
Returns: (bool)
isNotPerp(tickerId)
Test if tickerId is not a perps pair
Parameters:
tickerId (string)
Returns: (bool)
getPair(tickerId)
Pass a tickerId return the pair without exchange
Parameters:
tickerId (string)
Returns: (string) the pair
getSpotPair(tickerId)
Pass a tickerId return the pair without exchange and perps
Parameters:
tickerId (string)
Returns: (string) the pair
Employee Portfolio Generator [By MUQWISHI]▋ INTRODUCTION :
The “Employee Portfolio Generator” simplifies the process of building a long-term investment portfolio tailored for employees seeking to build wealth through investments rather than traditional bank savings. The tool empowers employees to set up recurring deposits at customizable intervals, enabling to make additional purchases in a list of preferred holdings, with the ability to define the purchasing investment weight for each security. The tool serves as a comprehensive solution for tracking portfolio performance, conducting research, and analyzing specific aspects of portfolio investments. The output includes an index value, a table of holdings, and chart plots, providing a deeper understanding of the portfolio's historical movements.
_______________________
▋ OVERVIEW:
● Scenario (The chart above can be taken as an example) :
Let say, in 2010, a newly employed individual committed to saving $1,000 each month. Rather than relying on a traditional savings account, chose to invest the majority of monthly savings in stable well-established stocks. Allocating 30% of monthly saving to AMEX:SPY and another 30% to NASDAQ:QQQ , recognizing these as reliable options for steady growth. Additionally, there was an admired toward innovative business models of NASDAQ:AAPL , NASDAQ:MSFT , NASDAQ:AMZN , and NASDAQ:EBAY , leading to invest 10% in each of those companies. By the end of 2024, after 15 years, the total monthly deposits amounted to $179,000, which would have been the result of traditional saving alone. However, by sticking into long term invest, the value of the portfolio assets grew, reaching nearly $900,000.
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▋ OUTPUTS:
The table can be displayed in three formats:
1. Portfolio Index Title: displays the index name at the top, and at the bottom, it shows the index value, along with the chart timeframe, e.g., daily change in points and percentage.
2. Specifications: displays the essential information on portfolio performance, including the investment date range, total deposits, free cash, returns, and assets.
3. Holdings: a list of the holding securities inside a table that contains the ticker, last price, entry price, return percentage of the portfolio's total deposits, and latest weighted percentage of the portfolio. Additionally, a tooltip appears when the user passes the cursor over a ticker's cell, showing brief information about the company, such as the company's name, exchange market, country, sector, and industry.
4. Indication of New Deposit: An indication of a new deposit added to the portfolio for additional purchasing.
5. Chart: The portfolio's historical movements can be visualized in a plot, displayed as a bar chart, candlestick chart, or line chart, depending on the preferred format, as shown below.
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▋ INDICATOR SETTINGS:
Section(1): Table Settings
(1) Naming the index.
(2) Table location on the chart and cell size.
(3) Sorting Holdings Table. By securities’ {Return(%) Portfolio, Weight(%) Portfolio, or Ticker Alphabetical} order.
(4) Choose the type of index: {Assets, Return, or Return (%)}, and the plot type for the portfolio index: {Candle, Bar, or Line}.
(5) Positive/Negative colors.
(6) Table Colors (Title, Cell, and Text).
(7) To show/hide any of selected indicator’s components.
Section(2): Recurring Deposit Settings
(1) From DateTime of starting the investment.
(2) To DateTime of ending the investment
(3) The amount of recurring deposit into portfolio and currency.
(4) The frequency of recurring deposits into the portfolio {Weekly, 2-Weeks, Monthly, Quarterly, Yearly}
(5) The Depositing Model:
● Fixed: The amount for recurring deposits remains constant throughout the entire investment period.
● Increased %: The recurring deposit amount increases at the selected frequency and percentage throughout the entire investment period.
(5B) If the user selects “ Depositing Model: Increased % ”, specify the growth model (linear or exponential) and define the rate of increase.
Section(3): Portfolio Holdings
(1) Enable a ticker in the investment portfolio.
(2) The selected deposit frequency weight for a ticker. For example, if the monthly deposit is $1,000 and the selected weight for XYZ stock is 30%, $300 will be used to purchase shares of XYZ stock.
(3) Select up to 6 tickers that the investor is interested in for long-term investment.
Please let me know if you have any questions
Mean Price
^^ Plotting switched to Line.
This method of financial time series (aka bars) downsampling is literally, naturally, and thankfully the best you can do in terms of maximizing info gain. You can finally chill and feed it to your studies & eyes, and probably use nothing else anymore.
(HL2 and occ3 also have use cases, but other aggregation methods? Not really, even if they do, the use cases are ‘very’ specific). Tho in order to understand why, you gotta read the following wall, or just believe me telling you, ‘I put it on my momma’.
The true story about trading volumes and why this is all a big misdirection
Actually, you don’t need to be a quant to get there. All you gotta do is stop blindly following other people’s contextual (at best) solutions, eg OC2 aggregation xD, and start using your own brain to figure things out.
Every individual trade (basically an imprint on 1D price space that emerges when market orders hit the order book) has several features like: price, time, volume, AND direction (Up if a market buy order hits the asks, Down if a market sell order hits the bids). Now, the last two features—volume and direction—can be effectively combined into one (by multiplying volume by 1 or -1), and this is probably how every order matching engine should output data. If we’re not considering size/direction, we’re leaving data behind. Moreover, trades aren’t just one-price dots all the time. One trade can consume liquidity on several levels of the order book, so a single trade can be several ticks big on the price axis.
You may think now that there are no zero-volume ticks. Well, yes and no. It depends on how you design an exchange and whether you allow intra-spread trades/mid-spread trades (now try to Google it). Intra-spread trades could happen if implemented when a matching engine receives both buy and sell orders at the same microsecond period. This way, you can match the orders with each other at a better price for both parties without even hitting the book and consuming liquidity. Also, if orders have different sizes, the remaining part of the bigger order can be sent to the order book. Basically, this type of trade can be treated as an OTC trade, having zero volume because we never actually hit the book—there’s no imprint. Another reason why it makes sense is when we think about volume as an impact or imbalance act, and how the medium (order book in our case) responds to it, providing information. OTC and mid-spread trades are not aggressive sells or buys; they’re neutral ticks, so to say. However huge they are, sometimes many blocks on NYSE, they don’t move the price because there’s no impact on the medium (again, which is the order book)—they’re not providing information.
... Now, we need to aggregate these trades into, let’s say, 1-hour bars (remember that a trade can have either positive or negative volume). We either don’t want to do it, or we don’t have this kind of information. What we can do is take already aggregated OHLC bars and extract all the info from them. Given the market is fractal, bars & trades gotta have the same set of features:
- Highest & lowest ticks (high & low) <- by price;
- First & last ticks (open & close) <- by time;
- Biggest and smallest ticks <- by volume.*
*e.g., in the array ,
2323: biggest trade,
-1212: smallest trade.
Now, in our world, somehow nobody started to care about the biggest and smallest trades and their inclusion in OHLC data, while this is actually natural. It’s the same way as it’s done with high & low and open & close: we choose the minimum and maximum value of a given feature/axis within the aggregation period.
So, we don’t have these 2 values: biggest and smallest ticks. The best we can do is infer them, and given the fact the biggest and smallest ticks can be located with the same probability everywhere, all we can do is predict them in the middle of the bar, both in time and price axes. That’s why you can see two HL2’s in each of the 3 formulas in the code.
So, summed up absolute volumes that you see in almost every trading platform are actually just a derivative metric, something that I call Type 2 time series in my own (proprietary ‘for now’) methods. It doesn’t have much to do with market orders hitting the non-uniform medium (aka order book); it’s more like a statistic. Still wanna use VWAP? Ok, but you gotta understand you’re weighting Type 1 (natural) time series by Type 2 (synthetic) ones.
How to combine all the data in the right way (khmm khhm ‘order’)
Now, since we have 6 values for each bar, let’s see what information we have about them, what we don’t have, and what we can do about it:
- Open and close: we got both when and where (time (order) and price);
- High and low: we got where, but we don’t know when;
- Biggest & smallest trades: we know shit, we infer it the way it was described before.'
By using the location of the close & open prices relative to the high & low prices, we can make educated guesses about whether high or low was made first in a given bar. It’s not perfect, but it’s ultimately all we can do—this is the very last bit of info we can extract from the data we have.
There are 2 methods for inferring volume delta (which I call simply volume) that are presented everywhere, even here on TradingView. Funny thing is, this is actually 2 parts of the 1 method. I wonder how many folks see through it xD. The same method can be used for both inferring volume delta AND making educated guesses whether high or low was made first.
Imagine and/or find the cases on your charts to understand faster:
* Close > open means we have an up bar and probably the volume is positive, and probably high was made later than low.
* Close < open means we have a down bar and probably the volume is negative, and probably low was made later than high.
Now that’s the point when you see that these 2 mentioned methods are actually parts of the 1 method:
If close = open, we still have another clue: distance from open/close pair to high (HC), and distance from open/close pair to low (LC):
* HC < LC, probably high was made later.
* HC > LC, probably low was made later.
And only if close = open and HC = LC, only in this case we have no clue whether high or low was made earlier within a bar. We simply don’t have any more information to even guess. This bar is called a neutral bar.
At this point, we have both time (order) and price info for each of our 6 values. Now, we have to solve another weighted average problem, and that’s it. We’ll weight prices according to the order we’ve guessed. In the neutral bar case, open has a weight of 1, close has a weight of 3, and both high and low have weights of 2 since we can’t infer which one was made first. In all cases, biggest and smallest ticks are modeled with HL2 and weighted like they’re located in the middle of the bar in a time sense.
P.S.: I’ve also included a "robust" method where all the bars are treated like neutral ones. I’ve used it before; obviously, it has lesser info gain -> works a bit worse.
Mizar_LibraryThe "Mizar_Library" is a powerful tool designed for Pine Script™ programmer’s, providing a collection of general functions that facilitate the usage of Mizar’s DCA (Dollar-Cost-Averaging) bot system.
To begin using the Mizar Library, you first need to import it into your indicator script. Insert the following line below your indicator initiation line: import Mizar_Trading/Mizar_Library/1 as mizar (mizar is the chosen alias).
In the import statement, Mizar_Trading.Mizar_Library_v1 refers to the specific version of the Mizar Library you wish to use. Feel free to modify mizar to your preferred alias name.
Once the library is imported, you can leverage its functions by prefixing them with mizar. . This will prompt auto-completion suggestions displaying all the available user-defined functions provided by the Mizar Library.
Now, let's delve into some of the key functions available in the Mizar Library:
DCA_bot_msg(_cmd)
The DCA_bot_msg function accepts an user-defined type (UDT) _cmd as a parameter and returns a string with the complete JSON command for a Mizar DCA bot.
Parameters:
_cmd (bot_params) : ::: User-defined type (UDT) that holds all the necessary information for the bot command.
Returns: A string with the complete JSON command for a Mizar DCA bot.
rounding_to_ticks(value, ticks, rounding_type)
The rounding_to_ticks function rounds a calculated price to the nearest actual price based on the specified tick size.
Parameters:
value (float) : ::: The calculated price as float type, to be rounded to the nearest real price.
ticks (float) : ::: The smallest possible price obtained through a request in your script.
rounding_type (int) : ::: The rounding type for the price: 0 = closest real price, 1 = closest real price above, 2 = closest real price below.
Returns: A float value representing the rounded price to the next tick.
bot_params
Bot_params is an user-defined type (UDT) that represents the parameters required for a Mizar DCA bot.
Fields:
bot_id (series string) : The ID number of your Mizar DCA bot.
api_key (series string) : Your private API key from your Mizar account (keep it confidential!).
action (series string) : The command to perform: "open" (standard) or "close" optional .
tp_perc (series string) : The take profit percentage in decimal form (1% = "0.01") optional .
base_asset (series string) : The cryptocurrency you want to buy (e.g., "BTC").
quote_asset (series string) : The coin or fiat currency used for payment (e.g., "USDT" is standard if not specified) optional .
direction (series string) : The direction of the position: "long" or "short" (only applicable for two-way hedge bots) optional .
To obtain the JSON command string for the alert_function call, you can use the DCA_bot_msg function provided by the library. Simply pass the cmd_msg UDT as an argument and assign the returned string value to a variable.
Here's an example to illustrate the process:
// Import of the Mizar Library to use the included functions
import/Mizar_Trading/Mizar_Library/1 as mizar
// Example to set a variable called “cmd_msg” and all of its parameters
cmd_msg = mizar.bot_params. new()
cmd_msg.action := "open"
cmd_msg.api_key := "top secret"
cmd_msg.bot_id := "9999"
cmd_msg.base_asset := "BTC"
cmd_msg.quote_asset := "USDT"
cmd_msg.direction := "long"
cmd_msg.tp_perc := "0.015"
// Calling the Mizar conversion function named “DCA_bot_msg()” with the cmd_msg as argument to receive the JSON command and save it in a string variable called “alert_msg”
alert_msg = mizar.DCA_bot_msg(cmd_msg)
Feel free to utilize (series) string variables instead of constant strings. By incorporating the Mizar Library into your Pine Script, you gain access to a powerful set of functions and can leverage them according to your specific requirements.
For additional help or support, you can join the Mizar Discord channel. There, you'll find a dedicated Pine Script channel where you can ask any questions related to Pine Script.
AggBands (v1) [qrsq]The "AggBands" indicator is a custom trading indicator designed to provide a consolidated view of the price action across multiple assets or trading pairs. It combines the price data from multiple tickers and calculates an aggregated price using user-defined weights for each ticker.
The indicator starts by defining the tickers to be included in the aggregation. You can choose from predefined configurations such as "BTC PAIRS," "CRYPTO TOTAL MARKET CAP," "TOP 5 PAIRS," "TOP 5 MEMECOINS," "SPX," "DXY," or "FANG." Each configuration includes specific tickers or indices relevant to the chosen category.
The indicator then fetches the closing, high, and low prices for each ticker and applies the user-defined weights to calculate the aggregated prices. The aggregated prices are normalized within a specified length to provide a consistent scale across different assets or pairs.
Next, the indicator calculates the midpoint, which is the average of the highest high and lowest low of the aggregated prices over a specified aggregation period.
To assess the volatility, the indicator calculates the price range and applies the Average True Range (ATR) indicator to determine the volatility value. The standard deviation is then computed using the price range and aggregation period, with an additional scaling factor applied to the volatility value.
Based on the standard deviation, the indicator generates multiple bands above and below the midpoint. By default, three standard deviation bands are calculated, but the user can choose between one and five bands. The upper and lower bands are smoothed using various moving average (MA) types, such as Simple Moving Average (SMA), Exponential Moving Average (EMA), Smoothed Moving Average (SMMA/RMA), Weighted Moving Average (WMA), Volume Weighted Moving Average (VWMA), Volume Weighted Average Price (VWAP), or Arnaud Legoux Moving Average (ALMA). The user can also adjust the length, offset, and sigma parameters for the moving averages.
The indicator can optionally smooth the midpoint, upper bands, and lower bands using a separate set of moving average parameters.
The indicator can be useful for traders and analysts who want to gain a consolidated view of price movements across multiple assets or trading pairs. It helps identify trends, volatility, and potential support and resistance levels based on the aggregated price and standard deviation bands. Traders can use this information to make informed decisions about trading strategies, risk management, and market analysis.
Volume Weighted Real Relative Strength (RS/RW)Volume Weighted Real Relative Strength (VRRS) measures the relative strength of a tickers vs. a benchmark ticker for the market, i.e. $SPY, and a benchmark ticker for the sector it is in. The calculation of VRRS is done as follow:
VRRS = * VolWeighted * 100
Where :
Close is Close price
smaClose is the last simple moving average value.
Ref is Reference ticker
VolWeighted is the volume weighted factor and is defined as (smaVol_short / smaVol_long); where smaVol_short, smaVol_long are the simple moving average of volume calculated for a short period (i.e. 21 period) and long period (i.e. 5 days), respectively.
Feature :
1. It can show two VRRS, one calculated against a market benchmark (i.e. $SPY) and one for a sector benchmark.
2. It shows also the bar plot of the benchmark ticker.
Linear Regression & RSI Multi-Function Screener with Table-LabelHi fellow traders..
Happy to share a Linear Regression & RSI Multi-Function Custom Screener with Table-Labels...
The Screener scans for Linear Regression 2-SD Breakouts and RSI OB/OS levels for the coded tickers and gives Summary alerts
Uses Tables (dynamica resizing) for the scanner output instead of standard labels!
This Screener cum indicator collection has two distinct objectives..
1. Attempt re-entry into trending trades.
2. Attempt Counter trend trades using linear regression , RSI and Zigzag.
Briefly about the Screener functions..
a. It uses TABLES as Labels a FIRST for any Screener on TV.
b. Tables dynamically resize based on criteria..
c. Alerts for breakouts of the UPPER and the LOWER regression channels.(2 SD)
d. In addition to LinReg it also Screens RSI for OB/OS levels so a multifunction Screener.
e. Of course has the standard summary Alerts and programmable format for Custom functions.
f. Uses only the inbuilt Auto Fib and Lin Reg code for the screener.(No proprietary stuff)
g. The auto Zigzag code is derived(Auto fib).
Question what are all these doing in a single screener ??
ZigZag is very useful in determining Trend Up or Down from one Pivot to another.
So Once you have a firm view of the Current Trend for your chosen timeframe and ticker…
We can consider few possible trading scenarios..
a. Re-entry in an Up Trend - Combination of OS Rsi And a Lower Channel breach followed by a re-entry back into the regression channel CAN be used as an effective re-entry.
b. Similarily one can join a Down Trend on OB Rsi and Upper Channel line breach followed by re-entry into the regression channel.
If ZigZag signals a range-bound market, bound within channel lines then the Upper breakout can be used to Sell and vice-versa!
In short many possibilities for using these functions together with Scanner and Alerts.
This facilitates timely PROFITABLE Trending and Counter trend opportunities across multiple tickers.
You must give a thorough READ to the various available tutorials on ZigZag / Regression and Fib retracements before attempting counter trend trades using these tools!!
A small TIP – Markets are sideways or consolidating 70% of the time!!
Acknowledgements: - Thanks a lot DGTRD for the Auto ZigZag code and also for the eagerness to help wherever possible..Respect!!
Disclaimer: The Alerts and Screener are just few tools among many and not any kind of Buy/Sell recommendations. Unless you have sufficient trading experience please consult a Financial advisor before investing real money.
*The alerts are set for crossovers however for viewing tickers trading above or below the channel use code in line 343 and 344 after setting up the Alerts!
** RSI alerts are disabled by default to avoid clutter, but if needed one can activate code lines 441,442,444 and 445
Wish you all, Happy Profitable Trading!
Miyuki Unit of AccountThis is a simple indicator that will show you candlesticks for the current ticker divided by a set ticker. This can be used to create a synthetic chart of two USD denominated tickers. E.g. set the indicator to ETHUSD and now you will have a ETH pair chart for any asset you view which uses USD as the quote asset.
Typically it would be set this to your personal 'unit of account' so you can quickly see how well assets are doing compared to you own denominator.
You can set any ticker as the indicator symbol.
There are options to change colours.
Note: if you view charts that have a different quote asset, the indicator may not show you anything useful. E.g. viewing BNBBTC and having ETHUSD set in the indicator.
ATR DAILY PROGRESSION)Indicator: ATR Daily Progression — Final Compact Edition
1. Indicator Objective
The ATR Daily Progression indicator measures the progression of intraday volatility as a percentage of the daily Average True Range (ATR).
It provides a quick visual overview of whether the market has reached or exceeded its average daily range of movement.
This helps traders avoid entering low-probability continuation trades once the day’s ATR is already completed.
2. Visual Presentation
Horizontal bar ranging from 0% to 150% of the ATR.
Green color up to 100%, then red beyond that point.
Main ticks: 0, 25, 50, 75, 90, 100, and 150%.
Full-height white vertical lines at 0%, 100%, and 150%.
A floating badge displaying the current ATR completion percentage, always visible.
Compact Height mode enabled by default for optimal visual integration.
3. Key Features
Function Description
Precise alignment The transition from green to red occurs exactly after the 100% tick.
Audio & visual alerts Triggered at 75%, 90%, 100%, and 150%.
Session flash effects The filled bar blinks when the ATR is reached (100%) or exceeded (150%).
Dynamic badge Displays the current ATR %, green before 100%, red after.
Compact layout Three-line table format for better chart integration.
4. Recommended Settings
ATR Length (Daily): 14
Bar width (steps): 32–40 (depending on chart size)
Always green below 100%: enabled
Show floating % badge: enabled
Compact Height: enabled by default
Flash at 75% and 90%: enabled
Flash at 100% and 150%: enabled
5. Strategic Use
The ATR Done Today is a visual discipline tool designed to help traders:
Identify when the market has likely completed its daily move.
Avoid late-session counter-trend trades.
Visualize volatility compression or expansion.
Determine optimal times to take profits or pause trading.
Adaptive Volume Delta Map---
📊 Adaptive Volume Delta Map (AVDM)
What is Adaptive Volume Delta Map (AVDM)?
The Adaptive Volume Delta Map (AVDM) is a smart, multi-timeframe indicator that visualizes buy and sell volume imbalances directly on the chart.
It adapts automatically to the best available data resolution (tick, second, minute, or daily), allowing traders to analyze market activity with micro-level precision .
In addition to calculating volume delta (the difference between buying and selling pressure), AVDM can display a Volume Distribution Map — a per-price-level visualization showing how volume is split between buyers and sellers.
Key Features
✅ Adaptive Resolution Selection — Automatically chooses the highest possible data granularity — from tick to daily timeframe.
✅ Volume Delta Visualization — Displays delta candles reflecting the dominance of buyers (green), sellers (red), and delta (orange).
✅ Per-Level Volume Map (optional) — Shows detailed buy/sell volume distribution per price level, grouped by `Ticks Per Row`.
✅ Bid/Ask Classification — When enabled, AVDM uses bid/ask logic to classify trade direction with greater accuracy.
✅ Smart Auto-Disable Protection — Automatically disables volume map if too many price levels (>50) are detected — preventing performance degradation.
Inputs Overview
Use Seconds Resolution — Enables use of second-level data (if your TradingView subscription allows it).
Use Tick Resolution — Enables tick-based analysis for the most detailed view. If available, enable both tick and seconds resolution.
Use Bid/Ask Calculated — Uses bid/ask midpoint logic to classify trades.
Show Volume Distribution — Toggles per-price-level buy/sell volume visualization.
Ticks Per Row — Controls how many ticks are grouped per volume level. Reduce this value for finer detail, or increase it to reduce visual load.
Calculated Bars — Sets how many historical bars the indicator should process. Higher value increases accuracy but may impact performance.
How to Use
1. Add the indicator to your chart.
2. Ensure that your symbol provides volume data (and preferably tick or second-level data).
3. The indicator will automatically select the optimal timeframe for detailed calculation.
4. If your TradingView subscription allows second-level data , enable “Use Seconds Resolution.”
5. If your subscription allows tick-level data , enable both “Use Tick Resolution” and “Use Seconds Resolution.”
6. Adjust the “Calculated Bars” input to set how many historical bars the indicator should process.
7. Observe the Volume Delta Candles :
* Green = Buy pressure dominates
* Red = Sell pressure dominates
8. To see buy/sell clustering by price, enable “Show Volume Distribution.”
9. If the indicator disables the map and shows:
" Volume Distribution disabled: Too many price levels detected (>50). Try decreasing 'Ticks Per Row' or using a lower chart resolution. If you don’t care about the map, just turn off 'Show Volume Distribution'. "
— follow the instructions to reduce chart load.
Notes
* Automatically adapts to your chart’s resolution and data availability.
* If your symbol doesn’t provide volume data, a runtime warning will appear.
* Works best on futures , FX , and crypto instruments with high-frequency volume streams.
Why Traders Love It
AVDM combines adaptive resolution , volume delta analysis , and visual distribution mapping into one clean, efficient tool.
Perfect for traders studying:
* Market microstructure
* Aggressive vs. passive participation
* Volume absorption
* Order flow imbalance zones
* Delta-based divergence signals
Technical Highlights
* Built with Pine Script v6
* Adaptive resolution logic (`security_lower_tf`)
* Smart memory-safe map rendering
* Dynamic bid/ask classification
* Automatic overload protection
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BOCS Channel Scalper Strategy - Automated Mean Reversion System# BOCS Channel Scalper Strategy - Automated Mean Reversion System
## WHAT THIS STRATEGY DOES:
This is an automated mean reversion trading strategy that identifies consolidation channels through volatility analysis and executes scalp trades when price enters entry zones near channel boundaries. Unlike breakout strategies, this system assumes price will revert to the channel mean, taking profits as price bounces back from extremes. Position sizing is fully customizable with three methods: fixed contracts, percentage of equity, or fixed dollar amount. Stop losses are placed just outside channel boundaries with take profits calculated either as fixed points or as a percentage of channel range.
## KEY DIFFERENCE FROM ORIGINAL BOCS:
**This strategy is designed for traders seeking higher trade frequency.** The original BOCS indicator trades breakouts OUTSIDE channels, waiting for price to escape consolidation before entering. This scalper version trades mean reversion INSIDE channels, entering when price reaches channel extremes and betting on a bounce back to center. The result is significantly more trading opportunities:
- **Original BOCS**: 1-3 signals per channel (only on breakout)
- **Scalper Version**: 5-15+ signals per channel (every touch of entry zones)
- **Trade Style**: Mean reversion vs trend following
- **Hold Time**: Seconds to minutes vs minutes to hours
- **Best Markets**: Ranging/choppy conditions vs trending breakouts
This makes the scalper ideal for active day traders who want continuous opportunities within consolidation zones rather than waiting for breakout confirmation. However, increased trade frequency also means higher commission costs and requires tighter risk management.
## TECHNICAL METHODOLOGY:
### Price Normalization Process:
The strategy normalizes price data to create consistent volatility measurements across different instruments and price levels. It calculates the highest high and lowest low over a user-defined lookback period (default 100 bars). Current close price is normalized using: (close - lowest_low) / (highest_high - lowest_low), producing values between 0 and 1 for standardized volatility analysis.
### Volatility Detection:
A 14-period standard deviation is applied to the normalized price series to measure price deviation from the mean. Higher standard deviation values indicate volatility expansion; lower values indicate consolidation. The strategy uses ta.highestbars() and ta.lowestbars() to identify when volatility peaks and troughs occur over the detection period (default 14 bars).
### Channel Formation Logic:
When volatility crosses from a high level to a low level (ta.crossover(upper, lower)), a consolidation phase begins. The strategy tracks the highest and lowest prices during this period, which become the channel boundaries. Minimum duration of 10+ bars is required to filter out brief volatility spikes. Channels are rendered as box objects with defined upper and lower boundaries, with colored zones indicating entry areas.
### Entry Signal Generation:
The strategy uses immediate touch-based entry logic. Entry zones are defined as a percentage from channel edges (default 20%):
- **Long Entry Zone**: Bottom 20% of channel (bottomBound + channelRange × 0.2)
- **Short Entry Zone**: Top 20% of channel (topBound - channelRange × 0.2)
Long signals trigger when candle low touches or enters the long entry zone. Short signals trigger when candle high touches or enters the short entry zone. This captures mean reversion opportunities as price reaches channel extremes.
### Cooldown Filter:
An optional cooldown period (measured in bars) prevents signal spam by enforcing minimum spacing between consecutive signals. If cooldown is set to 3 bars, no new long signal will fire until 3 bars after the previous long signal. Long and short cooldowns are tracked independently, allowing both directions to signal within the same period.
### ATR Volatility Filter:
The strategy includes a multi-timeframe ATR filter to avoid trading during low-volatility conditions. Using request.security(), it fetches ATR values from a specified timeframe (e.g., 1-minute ATR while trading on 5-minute charts). The filter compares current ATR to a user-defined minimum threshold:
- If ATR ≥ threshold: Trading enabled
- If ATR < threshold: No signals fire
This prevents entries during dead zones where mean reversion is unreliable due to insufficient price movement.
### Take Profit Calculation:
Two TP methods are available:
**Fixed Points Mode**:
- Long TP = Entry + (TP_Ticks × syminfo.mintick)
- Short TP = Entry - (TP_Ticks × syminfo.mintick)
**Channel Percentage Mode**:
- Long TP = Entry + (ChannelRange × TP_Percent)
- Short TP = Entry - (ChannelRange × TP_Percent)
Default 50% targets the channel midline, a natural mean reversion target. Larger percentages aim for opposite channel edge.
### Stop Loss Placement:
Stop losses are placed just outside the channel boundary by a user-defined tick offset:
- Long SL = ChannelBottom - (SL_Offset_Ticks × syminfo.mintick)
- Short SL = ChannelTop + (SL_Offset_Ticks × syminfo.mintick)
This logic assumes channel breaks invalidate the mean reversion thesis. If price breaks through, the range is no longer valid and position exits.
### Trade Execution Logic:
When entry conditions are met (price in zone, cooldown satisfied, ATR filter passed, no existing position):
1. Calculate entry price at zone boundary
2. Calculate TP and SL based on selected method
3. Execute strategy.entry() with calculated position size
4. Place strategy.exit() with TP limit and SL stop orders
5. Update info table with active trade details
The strategy enforces one position at a time by checking strategy.position_size == 0 before entry.
### Channel Breakout Management:
Channels are removed when price closes more than 10 ticks outside boundaries. This tolerance prevents premature channel deletion from minor breaks or wicks, allowing the mean reversion setup to persist through small boundary violations.
### Position Sizing System:
Three methods calculate position size:
**Fixed Contracts**:
- Uses exact contract quantity specified in settings
- Best for futures traders (e.g., "trade 2 NQ contracts")
**Percentage of Equity**:
- position_size = (strategy.equity × equity_pct / 100) / close
- Dynamically scales with account growth
**Cash Amount**:
- position_size = cash_amount / close
- Maintains consistent dollar exposure regardless of price
## INPUT PARAMETERS:
### Position Sizing:
- **Position Size Type**: Choose Fixed Contracts, % of Equity, or Cash Amount
- **Number of Contracts**: Fixed quantity per trade (1-1000)
- **% of Equity**: Percentage of account to allocate (1-100%)
- **Cash Amount**: Dollar value per position ($100+)
### Channel Settings:
- **Nested Channels**: Allow multiple overlapping channels vs single channel
- **Normalization Length**: Lookback for high/low calculation (1-500, default 100)
- **Box Detection Length**: Period for volatility detection (1-100, default 14)
### Scalping Settings:
- **Enable Long Scalps**: Toggle long entries on/off
- **Enable Short Scalps**: Toggle short entries on/off
- **Entry Zone % from Edge**: Size of entry zone (5-50%, default 20%)
- **SL Offset (Ticks)**: Distance beyond channel for stop (1+, default 5)
- **Cooldown Period (Bars)**: Minimum spacing between signals (0 = no cooldown)
### ATR Filter:
- **Enable ATR Filter**: Toggle volatility filter on/off
- **ATR Timeframe**: Source timeframe for ATR (1, 5, 15, 60 min, etc.)
- **ATR Length**: Smoothing period (1-100, default 14)
- **Min ATR Value**: Threshold for trade enablement (0.1+, default 10.0)
### Take Profit Settings:
- **TP Method**: Choose Fixed Points or % of Channel
- **TP Fixed (Ticks)**: Static distance in ticks (1+, default 30)
- **TP % of Channel**: Dynamic target as channel percentage (10-100%, default 50%)
### Appearance:
- **Show Entry Zones**: Toggle zone labels on channels
- **Show Info Table**: Display real-time strategy status
- **Table Position**: Corner placement (Top Left/Right, Bottom Left/Right)
- **Color Settings**: Customize long/short/TP/SL colors
## VISUAL INDICATORS:
- **Channel boxes** with semi-transparent fill showing consolidation zones
- **Colored entry zones** labeled "LONG ZONE ▲" and "SHORT ZONE ▼"
- **Entry signal arrows** below/above bars marking long/short entries
- **Active TP/SL lines** with emoji labels (⊕ Entry, 🎯 TP, 🛑 SL)
- **Info table** showing position status, channel state, last signal, entry/TP/SL prices, and ATR status
## HOW TO USE:
### For 1-3 Minute Scalping (NQ/ES):
- ATR Timeframe: "1" (1-minute)
- ATR Min Value: 10.0 (for NQ), adjust per instrument
- Entry Zone %: 20-25%
- TP Method: Fixed Points, 20-40 ticks
- SL Offset: 5-10 ticks
- Cooldown: 2-3 bars
- Position Size: 1-2 contracts
### For 5-15 Minute Day Trading:
- ATR Timeframe: "5" or match chart
- ATR Min Value: Adjust to instrument (test 8-15 for NQ)
- Entry Zone %: 20-30%
- TP Method: % of Channel, 40-60%
- SL Offset: 5-10 ticks
- Cooldown: 3-5 bars
- Position Size: Fixed contracts or 5-10% equity
### For 30-60 Minute Swing Scalping:
- ATR Timeframe: "15" or "30"
- ATR Min Value: Lower threshold for broader market
- Entry Zone %: 25-35%
- TP Method: % of Channel, 50-70%
- SL Offset: 10-15 ticks
- Cooldown: 5+ bars or disable
- Position Size: % of equity recommended
## BACKTEST CONSIDERATIONS:
- Strategy performs best in ranging, mean-reverting markets
- Strong trending markets produce more stop losses as price breaks channels
- ATR filter significantly reduces trade count but improves quality during low volatility
- Cooldown period trades signal quantity for signal quality
- Commission and slippage materially impact sub-5-minute timeframe performance
- Shorter timeframes require tighter entry zones (15-20%) to catch quick reversions
- % of Channel TP adapts better to varying channel sizes than fixed points
- Fixed contract sizing recommended for consistent risk per trade in futures
**Backtesting Parameters Used**: This strategy was developed and tested using realistic commission and slippage values to provide accurate performance expectations. Recommended settings: Commission of $1.40 per side (typical for NQ futures through discount brokers), slippage of 2 ticks to account for execution delays on fast-moving scalp entries. These values reflect real-world trading costs that active scalpers will encounter. Backtest results without proper cost simulation will significantly overstate profitability.
## COMPATIBLE MARKETS:
Works on any instrument with price data including stock indices (NQ, ES, YM, RTY), individual stocks, forex pairs (EUR/USD, GBP/USD), cryptocurrency (BTC, ETH), and commodities. Volume-based features require data feed with volume information but are optional for core functionality.
## KNOWN LIMITATIONS:
- Immediate touch entry can fire multiple times in choppy zones without adequate cooldown
- Channel deletion at 10-tick breaks may be too aggressive or lenient depending on instrument tick size
- ATR filter from lower timeframes requires higher-tier TradingView subscription (request.security limitation)
- Mean reversion logic fails in strong breakout scenarios leading to stop loss hits
- Position sizing via % of equity or cash amount calculates based on close price, may differ from actual fill price
- No partial closing capability - full position exits at TP or SL only
- Strategy does not account for gap openings or overnight holds
## RISK DISCLOSURE:
Trading involves substantial risk of loss. Past performance does not guarantee future results. This strategy is for educational purposes and backtesting only. Mean reversion strategies can experience extended drawdowns during trending markets. Stop losses may not fill at intended levels during extreme volatility or gaps. Thoroughly test on historical data and paper trade before risking real capital. Use appropriate position sizing and never risk more than you can afford to lose. Consider consulting a licensed financial advisor before making trading decisions. Automated trading systems can malfunction - monitor all live positions actively.
## ACKNOWLEDGMENT & CREDITS:
This strategy is built upon the channel detection methodology created by **AlgoAlpha** in the "Smart Money Breakout Channels" indicator. Full credit and appreciation to AlgoAlpha for pioneering the normalized volatility approach to identifying consolidation patterns. The core channel formation logic using normalized price standard deviation is AlgoAlpha's original contribution to the TradingView community.
Enhancements to the original concept include: mean reversion entry logic (vs breakout), immediate touch-based signals, multi-timeframe ATR volatility filtering, flexible position sizing (fixed/percentage/cash), cooldown period filtering, dual TP methods (fixed points vs channel percentage), automated strategy execution with exit management, and real-time position monitoring table.
NQ Position Size CalculatorNQ Position Size Line Calculator is designed specifically for Nasdaq 100 futures (NQ) and micro futures (MNQ) traders who want to maintain disciplined risk management. This visual tool eliminates the guesswork from position sizing by displaying distance lines and contract calculations directly on your chart.
The indicator creates horizontal lines at 10-tick intervals from your stop loss level, showing you exactly how many contracts to trade at each distance to maintain your predetermined risk amount. Whether you're trading regular NQ contracts or micro MNQ contracts, this calculator ensures you never risk more than intended while providing instant visual feedback for optimal position sizing decisions.
How to Use the Indicator
Step 1: Configure Your Settings
Stop Loss Price: Enter your exact stop loss level (e.g., 20000.00)
Risk Amount ($): Set your maximum dollar risk per trade (e.g., $500)
Contract Type: Choose between:
NQ (Regular): $5 per tick - for larger accounts
MNQ (Micro): $0.50 per tick - for smaller accounts or conservative sizing
Display Options:
Max Lines: Number of distance lines to show (default: 30)
Show Labels: Toggle tick distance and contract count labels
Line Color: Customize the color of distance lines
Label Size: Choose tiny, small, or normal label sizes
Step 2: Read the Visual Display
Once configured, the indicator displays:
Stop Loss Line:
Thick yellow line marking your exact stop loss level
Yellow label showing the stop loss price
Distance Lines:
Dashed red lines at 10-tick intervals above and below your stop loss
Lines appear on both sides for long and short position planning
Labels (if enabled):
Green labels (right side): For long positions above your stop loss
Red labels (left side): For short positions below your stop loss
Format: "20T 5x" means 20 ticks distance, 5 contracts maximum
Step 3: Use the Information Tables
The indicator provides two helpful tables:
Position Size Table (top-right):
Shows common tick distances (10, 20, 40, 80, 160 ticks)
Displays risk per contract at each distance
Contract count for your specified risk amount
Total risk with rounded contract numbers
Settings Table (bottom-right):
Confirms your current risk amount
Shows selected contract type
Displays current settings for quick reference
Step 4: Apply to Your Trading
For Long Positions:
Look at the green labels on the right side of your chart
Find your desired entry level
Read the label to see: distance in ticks and maximum contracts
Example: "30T 8x" = 30 ticks from stop, buy 8 contracts maximum
For Short Positions:
Look at the red labels on the left side of your chart
Find your desired entry level
Read the label for tick distance and contract count
Example: "40T 6x" = 40 ticks from stop, sell 6 contracts maximum
Step 5: Trading Execution
Before Entering a Trade:
Identify your stop loss level and input it into the indicator
Choose your entry point by looking at the distance lines
Note the contract count from the corresponding label
Verify the risk amount matches your trading plan
Execute your trade with the calculated position size
Risk Management Features:
Contract rounding: All position sizes are rounded down (never up) to ensure you don't exceed your risk limit
Zero position filtering: Lines only show where position size is at least 1 contract
Dual-sided display: Plan both long and short opportunities simultaneously
Share SizePurpose: The "Share Size" indicator is a powerful risk management tool designed to help traders quickly determine appropriate share/contract sizes based on their predefined risk per trade and the current market's volatility (measured by ATR). It calculates potential dollar differences from recent highs/lows and translates them into a recommended share/contract size, accounting for a user-defined ATR-based offset. This helps you maintain consistent risk exposure across different instruments and market conditions.
How It Works: At its core, the indicator aims to answer the question: "How many shares/contracts can I trade to keep my dollar risk within limits if my stop loss is placed at a recent high or low, plus an ATR-based buffer?"
Price Difference Calculation: It first calculates the dollar difference between the current close price and the high and low of the current bar (Now) and the previous 5 bars (1 to 5).
Tick Size & Value Conversion: These price differences are then converted into dollar values using the instrument's specific tickSize and tickValue. You can select common futures contracts (MNQ, MES, MGC, MCL), a generic "Stock" setting, or define custom values.
ATR Offset: An Average True Range (ATR) based offset is added to these dollar differences. This offset acts as a buffer, simulating a stop loss placed beyond the immediate high/low, accounting for market noise or volatility.
Risk-Based Share Size: Finally, using your Default Risk ($) input, the indicator calculates how many shares/contracts you can take for each of the 6 high/low scenarios (current bar, 5 previous bars) to ensure your dollar risk per trade remains constant.
Dynamic Table: All these calculations are presented in a clear, real-time table at the bottom-left of your chart. The table dynamically adjusts its "Label" to show the selected symbol preset, making it easy to see which instrument's settings are currently being used. The "Shares" rows indicate the maximum shares/contracts you can trade for a given risk and stop placement. The cells corresponding to the largest dollar difference (and thus smallest share size) for both high and low scenarios are highlighted, drawing your attention to the most conservative entry points.
Key Benefits:
Consistent Risk: Helps maintain a consistent dollar risk per trade, regardless of the instrument or its current price/volatility.
Dynamic Sizing: Automatically adjusts share/contract size based on market volatility and your chosen stop placement.
Quick Reference: Provides a real-time, easy-to-read table directly on your chart, eliminating manual calculations.
Informed Decision Making: Assists in quickly assessing trade opportunities and potential position sizes.
Setup Parameters (Inputs)
When you add the "Share Size" indicator to your chart, you'll see a settings dialog with the following parameters:
1. Symbol Preset:
Purpose: This is the primary setting to define the tick size and value for your chosen trading instrument.
Options:
MNQ (Micro Nasdaq 100 Futures)
MES (Micro E-mini S&P 500 Futures)
MGC (Micro Gold Futures)
MCL (Micro Crude Oil Futures)
Stock (Generic stock setting, with tick size/value of 0.01)
Custom (Allows you to manually input tick size and value)
Default: MNQ
Importance: Crucial for accurate dollar calculations. Ensure this matches the instrument you are trading.
2. Tick Size (Manual Override):
Purpose: Only used if Symbol Preset is set to Custom. This defines the smallest price increment for your instrument.
Type: Float
Default: 0.25
Hidden: This input is hidden (display=display.none) unless "Custom" is selected. You might need to change display=display.none to display=display.inline in the code if you want to see and adjust it directly in the settings for "Custom" mode.
3. Tick Value (Manual Override):
Purpose: Only used if Symbol Preset is set to Custom. This defines the dollar value of one tickSize increment.
Type: Float
Default: 0.50
Hidden: This input is hidden (display=display.none) unless "Custom" is selected. Similar to Tick Size, you might need to adjust its display property if you want it visible.
4. Default Risk ($):
Purpose: This is your maximum desired dollar risk per trade. All share size calculations will be based on this value.
Type: Float
Default: 50.0
Hidden: This input is hidden (display=display.none). It's a critical setting, so consider making it visible by changing display=display.none to display=display.inline in the code if you want users to easily adjust their risk.
ATR Offset Settings (Group): This group of settings allows you to fine-tune the ATR-based buffer added to your potential stop loss.
5. ATR Offset Length:
Purpose: Defines the lookback period for the Average True Range (ATR) calculation used for the offset.
Type: Integer
Default: 7
Hidden: This input is hidden (display=display.none).
6. ATR Offset Timeframe:
Purpose: Specifies the timeframe on which the ATR for the offset will be calculated. This allows you to use ATR from a higher timeframe for your stop buffer, even if your chart is on a lower timeframe.
Type: Timeframe string (e.g., "1" for 1 minute, "60" for 1 hour, "D" for Daily)
Default: "1" (1 Minute)
Hidden: This input is hidden (display=display.none).
7. ATR Offset Multiplier (x ATR):
Purpose: Multiplies the calculated ATR value to determine the final dollar offset added to your high/low price difference. A value of 1.0 means one full ATR is added. A value of 0.5 means half an ATR is added.
Type: Float
Minimum Value: 0 (no offset)
Default: 1.0
Hidden: This input is hidden (display=display.none).
Wick Size in USD with 10-Bar AverageWick Size in USD with 10-Bar Average
Version: 1.0
Author: QCodeTrader
🔍 Overview
This indicator converts the price wicks of your candlestick chart into USD values based on ticks, providing both raw and smoothed data via a 10-bar simple moving average. It helps traders visualize the monetary impact of price extremes, making it easier to assess volatility, potential risk, and plan appropriate stop loss levels.
⚙️ Key Features
Tick-Based Calculation:
Converts wick sizes into ticks (using a fixed tick size of 0.01, typical for stocks) and then into USD using a customizable tick value.
10-Bar Moving Average:
Smooths out the wick values over the last 10 bars, giving you a clearer view of average wick behavior.
Bullish/Bearish Visual Cues:
The chart background automatically highlights bullish candles in green and bearish candles in red for quick visual assessment.
Stop Loss Optimization:
The indicator highlights long wick sizes, which can help you set more accurate stop loss levels. Even when the price moves in your favor, long wicks may indicate potential reversals—allowing you to account for this risk when planning your stop losses.
User-Friendly Customization:
Easily adjust the USD value per tick through the settings to tailor the indicator to your specific instrument.
📊 How It Works
Wick Calculation:
The indicator calculates the upper and lower wicks by measuring the distance between the candle’s high/low and its body (open/close).
Conversion to Ticks & USD:
These wick sizes are first converted from price points to ticks (dividing by a fixed tick size of 0.01) and then multiplied by the user-defined tick value to convert the measurement into USD.
Smoothing Data:
A 10-bar simple moving average is computed for both the upper and lower wick values, providing smoothed data that helps identify trends and deviations.
Visual Representation:
Columns display the raw wick sizes in USD.
Lines indicate the 10-bar moving averages.
Background Color shifts between green (bullish) and red (bearish) based on candle type.
⚡ How to Use
Add the Indicator:
Apply it to your chart to begin visualizing wick sizes in monetary terms.
Customize Settings:
Adjust the Tick Value in USD in the settings to match your instrument’s tick value.
(Note: The tick size is fixed at 0.01, which is standard for many stocks.)
Optimize Your Stop Loss:
Analyze the raw and averaged wick values to understand volatility. Long wicks—even when the price moves in your favor—may indicate potential reversals. This insight can help you set more accurate stop loss levels to protect your gains.
Analyze:
Use the indicator’s data to gauge market volatility and assess the significance of price movements, aiding in more informed trading decisions.
This indicator is perfect for traders looking to understand the impact of extreme price movements in monetary terms, optimize stop loss levels, and effectively manage risk across stocks and other instruments with similar tick structures.
Moving Average Crossover Swing StrategyMoving Average Crossover Swing Strategy
**Overview:**
The basic concept of this strategy is to generate a signal when a faster/shorter length moving average crosses over (for Longs) or crosses under (for Shorts) a medium/longer length moving average. All of which are customizable. This strategy can work on any timeframe, however the daily is the timeframe used for the default settings and screenshots, as it was designed to be a multi-day swing strategy. Once a signal has been confirmed with a candle close, based on user options, the strategy will enter the trade on the open of the next candle.
The crossover strategy is nothing new to trading, but what can make this strategy unique and helpful, is the addition of further confirmation points, ATR based stop loss and take profit targets, optional early exit criteria, customizable to your needs and style, and just about everything visual can be toggled on/off. This strategy is based on a Trend (MA) indicator and a Momentum (MACD) indicator. While a Volume-based indicator is not shown here, one could consider using their favorite from that category to further compliment the signal idea.
It should be noted that depending on the time frame, direction(s) chosen, the signal options, confirmation options, and exit options selected, that a ticker may not produce more than 100 trades on the back test. Depending on your style and frequency, one could consider adjusting options and/or testing multiple tickers. It should also be noted that this strategy simply tests the underlying stock prices, not options contracts. And of course, testing this strategy against historical data does not assume that the same results will occur in future price action.
Shoutout given to Ripster's Clouds Indicator as pieces of that code were taken and modified to create both the Cloud visualization effects, and the Moving Average Pair Plots that are implemented in this strategy.
BASIC DEFAULTS
All can be changed as normal
Initial capital = 10,000
Order Sizing = 25% of equity (use the "Inputs" tab to modify this)
Pyramiding = 0
Commission = 0.65 USD per order
Price Verification = 1 tick
Slippage = 1 tick
RISK MANAGMENT
You will notice two different percentage options and ATR multipliers. This strategy will adjust position sizing by not exceeding either one of those % values based on the ATR (Average True Range) of the symbol and the multipliers selected, should the stock hit the stop loss price.
For Example, lets assume these values are true:
Account size = $10,000,
Max Risk = 1% of account size
Max Position Size = 25% of the account size
Stock Price = 23.45
ATR = 3.5
ATR Stop Loss Multiplier = 1.4
Then the formulas would be:
ACCT_SIZE * MaxRisk_% = 10000 * .01 = $100 (MaxCashRisk)
-----
MaxCashRisk / (ATR * ATR_SL_MULTIPLIER) = 100 / (3.5 * 1.4) = 20.4 Shares based on Max Cash Risk
-----
(ACCT_SIZE * MaxEquity_%) / STOCK_PRICE = (10000 * .25) / 23.45 = 106.61 Shares based on Max Equity Allocation
The minimum value of each of those options is then used, which in this case would be to purchase 20 shares so as not to exceed the max dollar risk should the stock reach the stop loss target. Likewise, if the ATR were to be much lower, say 0.48 cents, and all else the same, then the strategy would purchase the 106 shares based on Max Equity Allocation because the Max Cash Risk would require 149.25 shares.
MOVING AVERAGE OPTIONS
Select between and change the length & type of up to 5 pairs (10 total) of moving averages
The "Show Cloud-x" option will display a fill color between the "a" and "b" pairs
All moving averages lines can be toggled on/off in the "Style" tab, as well as adjusting their colors.
Visualization features do not affect calculations, meaning you could have all or nothing on the chart and the strategy will still produce results
SIGNAL CHOICES
Choose the fast/shorter length MA and the medium/longer length MA to determine the entry signal
CONFIRMATION OPTIONS
Both of these have customizable values and can be toggled on/off
A candle close over a slower/much longer length moving average
An additional cross-over (cross-under for Shorts) on the MACD indicator using default MACD values. While the MACD indicator is not necessary to have on the chart, it can help to add that for visualization. The calculations will perform whether the indicator is on the chart or not.
EARLY EXIT CRITERIA
Both can be toggled on/off with customizable values
MA Cross Exit will exit the trade early if the select moving averages cross-under (for longs) or cross-over (for shorts), indicating a potential reversal.
Max Bars in Trades will act as a last-resort exit by simply calculating the amount of full bars the trade has been open, and exiting on the opening of the next bar. For example: the default value is 8 bars, so after 8 full bars in the trade, if no other exit has been triggered (Stop Loss, Take Profit, or MA Cross(if enabled)), then the trade will exit at the opening of the 9th bar.
Finally, there is a table displaying the amount of trades taken for each side, and the amount & percent of both early exits. This table can be turned off in the "Style" tab
ADDITIONAL PLOTS
MACD (Moving Average Convergence/Divergence):
- The MACD is an optional confirmation indicator for this strategy.
- Plotting the indicator is not necessary for the strategy to work, but it can be helpful to visually see the status and position of the MACD if this feature is enabled in the strategy
- This helps to identify if there is also momentum behind the entry signal
ICT Turtle Soup | Flux Charts💎 GENERAL OVERVIEW
Introducing our new ICT Turtle Soup Indicator! This indicator is built around the ICT "Turtle Soup" model. The strategy has 5 steps for execution which are described in this write-up. For more information about the process, check the "HOW DOES IT WORK" section.
Features of the new ICT Turtle Soup Indicator :
Implementation of ICT's Turtle Soup Strategy
Adaptive Entry Method
Customizable Execution Settings
Customizable Backtesting Dashboard
Alerts for Buy, Sell, TP & SL Signals
📌 HOW DOES IT WORK ?
The ICT Turtle Soup strategy may have different implementations depending on the selected method of the trader. This indicator's implementation is described as :
1. Mark higher timerame liquidity zones.
Liquidity zones are where a lot of market orders sit in the chart. They are usually formed from the long / short position holders' "liquidity" levels. There are various ways to find them, most common one being drawing them on the latest high & low pivot points in the chart, which this indicator does.
2. Mark current timeframe market structure.
The market structure is the current flow of the market. It tells you if the market is trending right now, and the way it's trending towards. It's formed from swing higs, swing lows and support / resistance levels.
3. Wait for market to make a liquidity grab on the higher timeframe liquidity zone.
A liquidity grab is when the marked liquidity zones have a false breakout, which means that it gets broken for a brief amount of time, but then price falls back to it's previous position.
4. Buyside liquidity grabs are "Short" entries and Sellside liquidity grabs are "Long" entries by default.
5. Wait for the market-structure shift in the current timeframe for entry confirmation.
A market-structure shift happens when the current market structure changes, usually when a new swing high / swing low is formed. This indicator uses it as a confirmation for position entry as it gives an insight of the new trend of the market.
6. Place Take-Profit and Stop-Loss levels according to the risk ratio.
This indicator uses "Average True Range" when placing the stop-loss & take-profit levels. Average True Range calculates the average size of a candle and the indicator places the stop-loss level using ATR times the risk setting determined by the user, then places the take-profit level trying to keep a minimum of 1:1 risk-reward ratio.
This indicator follows these steps and inform you step by step by plotting them in your chart.
🚩UNIQUENESS
This indicator is an all-in-one suit for the ICT's Turtle Soup concept. It's capable of plotting the strategy, giving signals, a backtesting dashboard and alerts feature. It's designed for simplyfing a rather complex strategy, helping you to execute it with clean signals. The backtesting dashboard allows you to see how your settings perform in the current ticker. You can also set up alerts to get informed when the strategy is executable for different tickers.
⚙️SETTINGS
1. General Configuration
MSS Swing Length -> The swing length when finding liquidity zones for market structure-shift detection.
Higher Timeframe -> The higher timeframe to look for liquidity grabs. This timeframe setting must be higher than the current chart's timeframe for the indicator to work.
Breakout Method -> If "Wick" is selected, a bar wick will be enough to confirm a market structure-shift. If "Close" is selected, the bar must close above / below the liquidity zone to confirm a market structure-shift.
Entry Method ->
"Classic" : Works as described on the "HOW DOES IT WORK" section.
"Adaptive" : When "Adaptive" is selected, the entry conditions may chance depending on the current performance of the indicator. It saves the entry conditions and the performance of the past entries, then for the new entries it checks if it predicted the liquidity grabs correctly with the current setup, if so, continues with the same logic. If not, it changes behaviour to reverse the entries from long / short to short / long.
2. TP / SL
TP / SL Method -> If "Fixed" is selected, you can adjust the TP / SL ratios from the settings below. If "Dynamic" is selected, the TP / SL zones will be auto-determined by the algorithm.
Risk -> The risk you're willing to take if "Dynamic" TP / SL Method is selected. Higher risk usually means a better winrate at the cost of losing more if the strategy fails. This setting is has a crucial effect on the performance of the indicator, as different tickers may have different volatility so the indicator may have increased performance when this setting is correctly adjusted.
Inversion Fair Value Gap Screener | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Inverse Fair Value Gap Screener! This screener can provide information about the latest Inverse Fair Value Gaps in up to 5 tickers. You can also customize the algorithm that finds the Inverse Fair Value Gaps and the styling of the screener.
Features of the new Inverse Fair Value Gap (IFVG) Screener :
Find Latest Inverse Fair Value Gaps Across 5 Tickers
Shows Their Information Of :
Latest Status
Number Of Retests
Consumption Percent
Volume
Customizable Algorithm / Styling
📌 HOW DOES IT WORK ?
A Fair Value Gap generally occur when there is an imbalance in the market. They can be detected by specific formations within the chart. An Inverse Fair Value Gap is when a FVG becomes invalidated, thus reversing the direction of the FVG.
IFVGs get consumed when a Close / Wick enters the IFVG zone. Check this example:
This screener then finds Fair Value Gaps across 5 different tickers, and shows the latest information about them.
Status ->
Far -> The current price is far away from the IFVG.
Approaching ⬆️/⬇️ -> The current price is approaching the IFVG, and the direction it's approaching from.
Inside -> The price is currently inside the IFVG.
Retests -> Retest means the price tried to invalidate the IFVG, but failed to do so. Here you can see how many times the price retested the IFVG.
Consumed -> IFVGs get consumed when a Close / Wick enters the IFVG zone. For example, if the price hits the middle of the IFVG zone, the zone is considered 50% consumed.
Volume -> Volume of a IFVG is essentially the volume of the bar that broke the original FVG that formed it.
🚩UNIQUENESS
This screener can detect latest Inverse Fair Value Gaps and give information about them for up to 5 tickers. This saves the user time by showing them all in a dashboard at the same time. The screener also uniquely shows information about the number of retests and the consumed percent of the IFVG, as well as it's volume. We believe that this extra information will help you spot reliable IFVGs easier.
⚙️SETTINGS
1. Tickers
You can set up to 5 tickers for the screener to scan Fair Value Gaps here. You can also enable / disable them and set their individual timeframes.
2. General Configuration
FVG Zone Invalidation -> Select between Wick & Close price for FVG Zone Invalidation.
IFVG Zone Invalidation -> Select between Wick & Close price for IFVG Zone Invalidation. This setting also switches the type for IFVG consumption.
Zone Filtering -> With "Average Range" selected, algorithm will find FVG zones in comparison with average range of last bars in the chart. With the "Volume Threshold" option, you may select a Volume Threshold % to spot FVGs with a larger total volume than average.
FVG Detection -> With the "Same Type" option, all 3 bars that formed the FVG should be the same type. (Bullish / Bearish). If the "All" option is selected, bar types may vary between Bullish / Bearish.
Detection Sensitivity -> You may select between Low, Normal or High FVG detection sensitivity. This will essentially determine the size of the spotted FVGs, with lower sensitivities resulting in spotting bigger FVGs, and higher sensitivities resulting in spotting all sizes of FVGs.
