ICT Macro Time Window NYThis script highlights the typical ICT “macro” algorithm activity windows on your chart. It marks 10 minutes before to 10 minutes after each full hour, based on New York time (NY). The display is restricted to the 00:00 – 16:00 NY time range.
Overlay on chart with semi-transparent background
Automatically adjusts to the chart timeframe
Customizable: window start/end minutes, hours, and background color
Ideal for traders following ICT concepts to visually identify high-probability algorithm activity periods.
Volatilite
The Gain Anchor - Long/Short SignalsThe Gain Anchor – Long/Short Signals (WunderTrading Bot Ready)
Dual Anchored VWAP System Powered by Overbought & Oversold Signals
A high-precision AVWAP and Z-Score system designed to generate Long/Buy and Short/Sell signals.
This indicator is ideal for swing trades and can be used as a standard signal indicator or seamlessly integrated for automated trading with WunderTrading bots.
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Inputs
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• Master Symbol: Sets the symbol used to track market trend. When disabled, the chart’s symbol is used to track its own trend.
• Rolling AVWAP Length: Defines the AVWAP calculation lookback (the bar where calculation starts).
• Minimum Investment Amount ($): Minimum is $6. For WunderTrading, it should not be less than $12.
• Minimum Profit Target ($): Ensures returns are higher than the defined minimum profit.
• Z-Score Lookback: Sets the lookback length for the Z-Score calculation window.
• Z-Score Threshold: Defines the base threshold. (The code auto-adjusts thresholds as more data is processed.)
• Long/Short Strings Input: Enter the alert messages you want to receive. For WunderTrading bots, input your Long Entry, Long Exit, Short Entry, and Short Exit codes.
• Show Other Lines: Displays Rolling AVWAP plot, Take Profit, and Stop Loss lines.
• Table Position: Choose the dashboard placement on your chart.
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Core Logic
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• Z-Score: Detects price deviation from its mean. When the price overextends based on the lookback, AVWAPs are reset.
• Resetting AVWAP 1 / Fast AVWAP (White Line): Uses a weaker threshold.
• Resetting AVWAP 2 / Slow AVWAP (Blue Line): Uses stronger thresholds, confirming and filtering weaker crosses.
• When AVWAP 2 resets, it signals a possible trend change and may generate new signals.
• If AVWAP 2 detects excessively frequent trend changes (high volatility), new signals are automatically disabled.
• Stop Loss and Take Profit are derived from bar distance relative to the lowest AVWAP (longs) or highest AVWAP (shorts).
If this exceeds your minimum investment, the system auto-adjusts the size.
If stop loss is not positioned beyond the AVWAPs, no signal is generated.
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Trade Signals Logic
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The indicator’s signal mechanism is designed to prevent overtrading during
high volatility.
- Signals are disabled when a sudden surge in volatility is detected.
- Only one signal is generated per legitimate trend change.
- Example:
• When the trend switches to bullish, only one Long signal is given.
• Once that Long position is closed (profit or loss), no new signal will be issued until another valid trend change occurs.
• The same logic applies to bearish/Short positions.
This ensures that signals remain clean, infrequent, and aligned with real trend shifts rather than noise.
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Take Profit & Stop Loss
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• Take Profit has two levels:
1. First Level: Triggered when the trend changes and price is below the first TP level.
2. Second Level: Triggered if the price surges into the second TP level.
The position is closed on whichever condition is met first.
• On Scale:
- Take Profit (Gray Line): Rolling take profit value.
- Stop Loss (Maroon Line): Rolling stop loss value, auto-calculated as half the minimum profit.
- Gray Stop Loss and Take Profit: Rolling Stop Loss and Take Profit purpose is mainly for manual trading but when they are both gray it is not ideal to look for an entry.
• On Chart:
- Take Profit: Lime (Longs), Fuchsia (Shorts). Fixed from signal start until triggered.
- Stop Loss: Yellow (Longs), Maroon (Shorts). Fixed from signal start until triggered.
- You have to activate "Show Other Lines" in Input to see them
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Signal Markers
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• 👆 = Long Entry
• Green Dot = Long Exit (TP/SL)
• 👇 = Short Entry
• Fuchsia Dot = Short Exit (TP/SL)
• 💥 = Bullish Trend
• 🔥 = Bearish Trend
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Backtest System
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• Displays the number of days since the first trade/backtest.
• Shows trade count, win rate, net profit/loss.
• Useful for real-time analysis and alert validation.
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Dashboard Overview
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Row 1 (Per Symbol):
• Column 1: Win Rate + Total Trades / Wins / Losses
• Color Modes: Blue = Win rate rising and it's 50 or higher. Brown = Win rate falling and it's 50 or higher. Grey = Falling and less than 50
• Column 2: Backest - number of days since the first trade
• Column 3: Net Profit + Total Profit / Total Loss
• Color Modes: Red = Loss greater than Profit , Green = Net Profit exceeds minimum profit x Total Trade Won, Brown = Profit greater than Loss but high bad trades
• Column 4: Investment Amount + Minimum Profit | Gain % to Target
• Color Modes: Signal State: Lime = Long, Maroon = Short, Yellow = Both Active
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Usage Notes
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• Works for manual or automated execution.
• Fully compatible with WunderTrading’s JSON alert format (and any platform using the same format).
• Can also be used standalone with no dependencies.
• Dashboard and auto-calculated SL/TP make it flexible across all trading styles.
• Minimum Investment Amount affects SL/TP size and therefore win rate.
• Increasing Minimum Profit increases potential profit but also increases loss size.
• Loss-to-Win ratio is always 1:2+, meaning your wins are at least double your losses.
• Optimized for 1-minute timeframe. Other timeframes may also yield desirable results.
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⚠️ Disclaimer
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This indicator does not constitute financial advice or a trading recommendation.
All trading involves risk. Past performance does not guarantee future results.
Easy Trend by ZuperviewEasy Trend, a trend indicator, gives you many key features as below:
Allow defining moving average with (11 popular moving averages)
Allow smoothing moving average
Allow applying a plot change filter, either before or after smoothing
Paint plot to clearly show uptrend vs downtrend
Paint chart background to clearly show uptrend vs downtrend
Trigger alerts on trend shift
Print markers on trend shift
Be NinjaScript ready for advanced usage, only restricted by your imagination
Expose dedicated NinjaScript signals
Elite indicatorElite Indicator – AI-Driven Signals for Profitable Trading in Stocks, Forex, and Crypto !
Unlock your trading potential with the Elite Indicator, your ultimate AI-powered trading companion for stocks, forex, and crypto markets. Designed to simplify your trading journey, this indicator delivers precise BUY/SELL signals directly on your chart, empowering you to trade with confidence across multiple timeframes, from 1-minute scalping to 1-day trading strategies.
Leverage the power of AI to identify high-probability trading opportunities, backed by rigorous backtesting and a proven high win-rate.
Join the ranks of traders who have transformed their strategies with Elite Indicator – where advanced technology meets user-friendly design. Elevate your trading game and stay ahead of the curve in today's fast-paced markets.
Transform Your Trading – Join the Elite! 🔥
Disclaimer: Trading involves inherent risks. Use this indicator as part of a broader risk management strategy and never invest more than you can afford to lose.
Kitti-Playbook ATR Study R0
Date : Aug 22 2025
Kitti-Playbook ATR Study R0
This is used to study the operation of the ATR Trailing Stop on the Long side, starting from the calculation of True Range.
1) Studying True Range Calculation
1.1) Specify the Bar graph you want to analyze for True Range.
Enable "Show Selected Price Bar" to locate the desired bar.
1.2) Enable/disable "Display True Range" in the Settings.
True Range is calculated as:
TR = Max (|H - L|, |H - Cp|, |Cp - L|)
• Show True Range:
Each color on the bar represents the maximum range value selected:
◦ |H - L| = Green
◦ |H - Cp| = Yellow
◦ |Cp - L| = Blue
• Show True Range on Selected Price Bar:
An arrow points to the range, and its color represents the maximum value chosen:
◦ |H - L| = Green
◦ |H - Cp| = Yellow
◦ |Cp - L| = Blue
• Show True Range Information Table:
Displays the actual values of |H - L|, |H - Cp|, and |Cp - L| from the selected bar.
2) Studying Average True Range (ATR)
2.1) Set the ATR Length in Settings.
Default value: ATR Length = 14
2.2) Enable/disable "Display Average True Range (RMA)" in Settings:
• Show ATR
• Show ATR Length from Selected Price Bar
(An arrow will point backward equal to the ATR Length)
3) Studying ATR Trailing
3.1) Set the ATR Multiplier in Settings.
Default value: ATR Multiply = 3
3.2) Enable/disable "Display ATR Trailing" in Settings:
• Show High Line
• Show ATR Bands
• Show ATR Trailing
4) Studying ATR Trailing Exit
(Occurs when the Close price crosses below the ATR Trailing line)
Enable/disable "Display ATR Trailing" in Settings:
• Show Close Line
• Show Exit Points
(Exit points are marked by an orange diamond symbol above the price bar)
Solar Wave by ninZa.coSolar Wave - trend indicator stands out with many key features to help traders enhance their trading, let's check below:
Plot "Trend Vector" that interprets trend direction (uptrend or downtrend) and trend strength (strong or weak)
Plot "Trailing Stop" for stop trailing management
Allow configuring "Trend Vector" and "Trailing Stop" with ninZaATR adjustment
Print trend steps and highlight step decreases to warn of trend weakness
Colorize bars based on 4 statuses: uptrend strong, uptrend weak, downtrend strong, downtrend weak
Colorize "Trend Vector" based on 4 statuses: uptrend strong, uptrend weak, downtrend strong, downtrend weak
Colorize "Trailing Stop" to clearly show uptrend vs downtrend
Paint background to clearly show uptrend vs downtrend
Trigger alerts on trend start, pullback, strengthening
Print markers on trend start, pullback, strengthening
Be NinjaScript ready for advanced usage, only restricted by your imagination
Expose dedicated NinjaScript signals
4 states of the markets (strong/weak uptrend, strong/weak downtrend) are displayed clearly with various visual signals to help you easily read: bar painting, plot colorization, background highlight.
The best signal of Solar Wave is PULLBACK. As you know, a trend rarely goes straight, but often retraces – which creates great opportunities for pullback trading. In Solar Wave, pullbacks are our recommended signals for entries. From our testing and experiences, the first and second pullbacks are usually the most reliable and optimal entries.
Cosmik Z-TP by ninZa.coWith Cosmik Z-TP - Trading System, you can:
Enter trades confidently with highly reliable signals.
Pinpoint where to place stops and profit targets with ease.
Enjoy high rewards while keeping the risks low in every trade.
Simplify your charts by kicking out 2, 3, or even 10 indicators.
Customize the system to your unique trading approach.
Get started with trading immediately.
Enhance the enjoyment of your daily trading with a user-friendly interface.
Identify the market's direction, spot signal zones, and make timely entry decisions.
Simplified signal mechanism:
During an uptrend, indicated by a green background and blue trailing stop, buy signals emerge within the blue signal zone.
During a downtrend, identified by a red background and pink trailing stop, sell signals emerge within the pink signal zone.
Advanced signal filter: You have the flexibility to control the quantity of signals within a trend phase or a range.
MagnetOsc Turbo by ninZa.coMagnetOsc Turbo - Multi-timeframe momentum analysis
Unlike conventional oscillators, MagnetOsc Turbo analyzes momentum on two independent timeframes simultaneously (e.g., 100-tick & 5-minute).
Why it matters: Momentum alignment across timeframes is a key signal of trend strength or turning points.
Easy Trend by ninZa.coEasy Trend, a NinjaTrader trend indicator, gives you many key features as below:
Allow defining moving average with (11 popular moving averages)
Allow smoothing moving average
Allow applying a plot change filter, either before or after smoothing
Paint plot to clearly show uptrend vs downtrend
Paint chart background to clearly show uptrend vs downtrend
Trigger alerts on trend shift
Print markers on trend shift
Be NinjaScript ready for advanced usage, only restricted by your imagination
Expose dedicated NinjaScript signals
BandBreak Pro (BB×ST×SRC) — Live-Sync Indicator📌 Overview
BandBreak Pro is a volatility + trend confirmation indicator designed to provide traders with clean breakout signals.
It synchronizes Bollinger Bands (BB), a selectable SRC line (price source), and Super trend (ST) into one unified logic.
⚡ Signals only trigger when price breaks the Bollinger Bands and the Super trend confirms the same direction.
📖 Basics & Definitions
1. Bollinger Bands (BB)
Bollinger Bands measure volatility by building an envelope around price.
Middle line (Basis) = Simple Moving Average (SMA).
Upper Band = SMA + (Multiplier × Standard Deviation).
Lower Band = SMA – (Multiplier × Standard Deviation).
👉 Meaning: A break above the upper band often suggests bullish strength, while a break below the lower band suggests bearish momentum.
2. SRC Line (Source Line)
The SRC line is a chosen price input: close, hlc3, or ohlc4.
It acts as the backbone since both BB and ST derive from it.
Benefit: Ensures everything is perfectly synchronized and avoids repainting issues.
3. Super trend (ST)
Supertrend is an ATR (Average True Range) based trend filter.
If price is above the ST line → Uptrend (Green).
If price is below the ST line → Downtrend (Red).
👉 Meaning: ST is a simple yet powerful filter to confirm trend direction and reduce false breakouts.
📌 CONCEPTS (with Calculations)
Hybrid Sync (History vs Realtime)
History: All calculations use confirmed OHLC via request.security (no lookahead) → no repaint.
Realtime: (if ON) calculations follow live chart OHLC → what you see is what you get.
Strict No-Repaint: Forces realtime bar to also use confirmed OHLC values.
👉 Formula:
if strict = true → use confirmed OHLC only
else if realtime and followChart = true → use chart OHLC
else → use confirmed OHLC
SRC Line (Selected Source)
User can select close, hlc3 = (high+low+close)/3, or ohlc4 = (open+high+low+close)/4.
This SRC drives Bollinger Bands and Supertrend.
👉 Formula:
SRC = close | hlc3 | ohlc4 (user choice)
Bollinger Bands (BB Break Logic)
Basis:
Basis = SMA(SRC, Length)
Standard Deviation:
Dev = StDev(SRC, Length)
Bands:
Upper = Basis + (Multiplier × Dev)
Lower = Basis - (Multiplier × Dev)
Breakout Filter:
UpBB = Upper × (1 + Buffer%)
DnBB = Lower × (1 – Buffer%)
👉 Meaning: Breakouts only count when price crosses filtered bands.
Supertrend (Directional Filter)
True Range:
TR = max(High – Low, |High – PrevClose|, |Low – PrevClose|)
ATR:
ATR = RMA(TR, ST_Length)
Bands:
BasicUp = (High+Low)/2 + (ST_Factor × ATR)
BasicDn = (High+Low)/2 – (ST_Factor × ATR)
Final Line (flip logic):
If Close > PrevUp → Trend = UP → use Dn line
If Close < PrevDn → Trend = DOWN → use Up line
Signal Formation (Confirmed Bar Only)
Long Condition:
Long = crossover(SRC, UpBB) AND Supertrend = UP
Short Condition:
Short = crossunder(SRC, DnBB) AND Supertrend = DOWN
Validation: Signals trigger only on barstate.isconfirmed (bar close).
🛠️ FEATURES
Clean, synced plots: Bollinger Bands, Basis line, SRC line, Supertrend line.
Hybrid sync modes: live-follow or strict no-repaint.
Bollinger controls: length, multiplier, buffer %, show/hide.
Supertrend controls: enable, ATR length, factor, show/hide.
Signal labels: BB×ST ↑ and BB×ST ↓.
Alerts: Built-in LONG/SHORT ready to use.
Overlay = true; optimized for intraday with higher label capacity.
📊 HOW TO USE
Timeframes: 5m–1H intraday; 2H–1D for swing trades.
Markets: Crypto, Forex, Indices, Equities.
Workflow:
Keep chart clean with only BandBreak Pro.
Start BB = 20 length, 2.0 multiplier. Use buffer 0.25–0.75% in choppy pairs.
Keep Supertrend ON to reduce false signals. Lower factor = faster flips.
After breakout, manage trades using S/R or BB midline.
SL = opposite ST line, TP = midline or nearest support/resistance.
⚠️ LIMITATIONS
Ranging markets may produce whipsaws.
Strict mode = safest but slower signals.
Not a strategy → no backtesting/PnL.
Parameters must be tuned for volatile/illiquid assets.
Always use with risk management.
🔔 ALERTS
BB×ST LONG → SRC crosses above upper band + ST = UP.
BB×ST SHORT → SRC crosses below lower band + ST = DOWN.
👉 Recommended: “Once Per Bar Close”.
NOTES
Buffer % = micro filter, useful for high-volatility assets.
Higher ST factor = fewer flips, more trend fidelity.
Lower ST factor = faster flips, more frequent signals.
🌟 Why BandBreak Pro is Unique
✅ Both BB and ST are calculated from the same hybrid OHLC SRC source → perfectly aligned & repaint-free.
✅ Only issues dual-confirmation signals → fewer false breakouts.
✅ Beginner-friendly (clear definitions included) + Pro-level customization (buffer %, sync modes).
✅ Multi-market: Crypto, Forex, Indices, Stocks.
🙏 Thanks
Bollinger Bands = John Bollinger’s volatility framework.
Supertrend = ATR-based classic TA tool.
SRC + Hybrid Sync = original implementation adapted for TradingView.
ابو فيصل 12The Traders Trend Dashboard (ابو فيصل 12) is a comprehensive trend analysis tool designed to assist traders in making informed trading decisions across various markets and timeframes. Unlike conventional trend-following scripts,ابو فيصل12 goes beyond simple trend detection by incorporating
SMT - Squeeze Momentum Trend📊 Squeeze Momentum Trend
An indicator that combines volatility, momentum, and trend to anticipate the market’s strongest moves. 🚀
✅ Squeeze → when Bollinger Bands tighten inside the Keltner Channel: the market is in compression, ready to “explode”.
✅ Momentum → shows direction and strength (green = bullish push, red = bearish push).
✅ Trend Filter → confirms direction using a higher timeframe EMA (to avoid false signals).
💡 In practice:
🔥 If price breaks out of a squeeze with positive momentum → potential long breakout.
❄️ If it breaks out with negative momentum → potential short breakout.
📌 Perfect for spotting key moments when the market stops “resting” and makes its next big move.
🏹 EMA Momentum TheoryEMA Trend following system
Summary
This indicator blends EMA trend direction with momentum confirmation to plot high-quality Buy/Sell signals, plus safe exit and profit-booking cues. It’s designed to keep you aligned with the primary trend, avoid chop, and exit decisively when momentum fades.
How it works
Trend Engine: Fast and slow EMAs define bias (Uptrend when Fast EMA > Slow EMA; Downtrend when Fast EMA < Slow EMA).
Signals:
Buy when uptrend + momentum turns positive after a pullback.
Sell when downtrend + momentum turns negative after a bounce.
Best use
Works on all liquid symbols (Index, Equity, Futures, FX, Crypto).
Timeframes: 15m–1D for cleaner structure.
Risk management
Position sizing per trade ≤ 1–2% account risk.
Avoid trading during major news events on lower TFs.
Alerts
“Buy Signal” on confirmed uptrend + momentum flip
“Sell Signal” on confirmed downtrend + momentum flip
“Safe Exit” on momentum fade or trail stop hit
“Partial TP” when RR target reached
Disclaimer
This tool is for education & research. Past performance doesn’t guarantee future results. Always validate on demo and manage risk.
Changelog
v1.0 — Initial release: EMA trend + momentum filter, ATR/EMA trail, partial TP, full alert suite.
StdDev Supply/Demand Zone RefinerThis indicator uses standard deviation bands to identify statistically significant price extremes, then validates these levels through volume analysis and market structure. It employs a proprietary "Zone Refinement" technique that dynamically adjusts zones based on price interaction and volume concentration, creating increasingly precise support/resistance areas.
Key Features:
Statistical Extremes Detection: Identifies when price reaches 2+ standard deviations from mean
Volume-Weighted Zone Creation: Only creates zones at extremes with abnormal volume
Dynamic Zone Refinement: Automatically tightens zones based on touch points and volume nodes
Point of Control (POC) Identification: Finds the exact price with maximum volume within each zone
Volume Profile Visualization: Shows horizontal volume distribution to identify key liquidity levels
Multi-Factor Validation: Combines volume imbalance, zone strength, and touch count metrics
Unlike traditional support/resistance indicators that use arbitrary levels, this system:
Self-adjusts based on market volatility (standard deviation)
Refines zones through machine-learning-like feedback from price touches
Weights by volume to show where real money was positioned
Tracks zone decay - older, untested zones automatically fade
RVOL with Breakout Signals
Key Features
RVOL Line : Displays RVOL as a gray line on the chart. Values above 1 indicate above-average volume; above 2 suggests strong activity.
Horizontal Lines :
Base Line (light pink dotted at 0): Reference baseline.
RVOL 1 (gray dashed): Threshold for average volume.
RVOL 2 (green dashed): Threshold for high volume activity.
Breakout Buy Signals : Pink upward triangles (above the bar) appear when the price closes above the highest high of the past breakout lookback period AND RVOL exceeds the set threshold (default 2). This confirms potential valid breakouts backed by volume.
How to Use
Add the indicator to your chart.
Adjust inputs in the settings:
RVOL Lookback Period (default 10): Number of bars to calculate average volume. For short-term trades (intraday to mid-term), 5-20 works best; test based on your timeframe.
Breakout Lookback Period (default 20): Bars to check for the previous high. Shorter for aggressive breakouts, longer for stronger confirmations.
RVOL Threshold for Breakout (default 2.0): Minimum RVOL required to confirm a breakout signal.
Look for pink triangles as buy signals during breakouts. Combine with your strategy (e.g., support/resistance, trends) for entries.
For position sizing: Higher RVOL (e.g., >2) allows larger positions due to better liquidity and reward potential.
When to Use
Breakout Plays : Ideal for spotting valid breakouts in volatile stocks. High RVOL confirms the move isn't a fakeout, as volume indicates real interest (e.g., institutional buying).
Short to Mid-Term Trades : Best on 5-min to daily charts for day trading or swings. Use on "In Play" stocks with news, earnings, or catalysts.
Avoid in Low Volume : If RVOL <1, skip or use small positions—low liquidity increases risk.
Inspired by traders like those at SMB Capital, who use RVOL to decide execution and sizing.
Example
See the attached screenshot on Bitcoin daily chart, showing multiple valid breakouts marked by pink triangles where price breaks highs with RVOL >2, leading to strong upward moves. This demonstrates how the indicator filters noise and highlights high-probability setups. Always backtest and use risk management!
Let me knows u have any idea to improve the indicator. Thank you all!
ADR% / AWR% / AMR% (v5)This indicator calculates on the time scale you choose by modifying the parameters as you are the average range in daily, weekly and monthly percentage.
By Mr. Le Besque
VSOVSO
This is similar to LazyBear's WaveTrend oscillator but handles momentum calculation differently and has some extra components for trade analysis.
The oscillator calculates an adaptive mean, then measures how far price deviates from that mean. Instead of just looking at raw deviation, it normalizes this by dividing by smoothed absolute deviation values.
The key difference is how it separates momentum - it splits the deviation into positive (up) and negative (down) components, then applies directional strength smoothing to each separately before combining them:
100 * (up_strength - down_strength) / (up_strength + down_strength)
This directional strength calculation gives more weight to sustained moves in either direction rather than just price volatility. The result is the main Momentum Wave oscillating between -100 and +100. The Signal Wave is just a smoothed version of this. The Momentum Gap shows the difference between them.
You'll see the Momentum Wave as a colored area/line with four color states, the Signal Wave as a white area, the Momentum Gap as a yellow line, the Drip Rate as cyan/purple area, and Velocity as a colored line at the bottom. The overbought/oversold zones are shaded, volatility bands adapt to current conditions, and major/minor signals show up as circles when the waves cross.
For trading, the Drip Rate is your long-term signal for bigger shifts. When it makes lower lows into resistance, look for reversals. Works great across multiple timeframes. Volatility squeezes signal big moves coming - use these with support/resistance and divergences. Top/bottom signals show momentum shifts and usually lead to pumps or drops.
Velocity shows breakout speed or rejections. Higher readings mean faster moves, regardless of direction. Wave colors reveal continuation patterns - green to purple to green means strong continuation up, red to cyan to red means continuation down.
The Momentum Gap can signal divergence on its own. The angle it crosses zero often hints at how fast the next move will be. When momentum goes outside the volatility bands, watch the next wave for divergence or confirmation.
Works best when you combine the Drip Rate across timeframes with squeeze setups and color changes for high-probability entries.
Works well with Heikin Ashi candles, or use the smoothed candle mode in the settings to mimic them. You can set the candle colors to the momentum wave colors as well, it can be helpful.
Here is a trade setup and how you can use it to take trades.
Overnight Gap Dominance Indicator (OGDI)The Overnight Gap Dominance Indicator (OGDI) measures the relative volatility of overnight price gaps versus intraday price movements for a given security, such as SPY or SPX. It uses a rolling standard deviation of absolute overnight percentage changes divided by the standard deviation of absolute intraday percentage changes over a customizable window. This helps traders identify periods where overnight gaps predominate, suggesting potential opportunities for strategies leveraging extended market moves.
Instructions
A
pply the indicator to your TradingView chart for the desired security (e.g., SPY or SPX).
Adjust the "Rolling Window" input to set the lookback period (default: 60 bars).
Modify the "1DTE Threshold" and "2DTE+ Threshold" inputs to tailor the levels at which you switch from 0DTE to 1DTE or multi-DTE strategies (default: 0.5 and 0.6).
Observe the OGDI line: values above the 1DTE threshold suggest favoring 1DTE strategies, while values above the 2DTE+ threshold indicate multi-DTE strategies may be more effective.
Use in conjunction with low VIX environments and uptrend legs for optimal results.
KAMA Trend Flip - SightLing LabsBuckle up, traders—this open-source KAMA Trend Flip indicator is your ticket to sniping trend reversals with a Kaufman Adaptive Moving Average (KAMA) that’s sharper than a Wall Street shark’s tooth. No voodoo, no fluff—just raw, volatility-adaptive math that dances with the market’s rhythm. It zips through trending rockets and chills in choppy waters, slashing false signals like a samurai. Not laggy like the others - this thing is the real deal!
Core Mechanics:
• Efficiency Ratio (ER): Reads the market’s pulse (0-1). High ER = turbo-charged MA, low ER = smooth operator.
• Adaptive Smoothing: Mixes fast (default power 2) and slow (default 30) constants to match market mood swings.
• Trend Signals: KAMA climbs = blue uptrend (bulls run wild). KAMA dips = yellow downtrend (bears take over). Flat = gray snooze-fest.
• Alerts: Instant pings on flips—“Trend Flip Up” for long plays, “Down” for shorts. Plug into bots for set-and-forget domination.
Why It Crushes:
• Smokes static MAs in volatile arenas (crypto, stocks, you name it). Backtests show 20-30% fewer fakeouts than SMA50.
• Visual Pop: Overlays price with bold blue/yellow signals. Slap it on BTC 1D to see trends light up like Times Square.
• Tweakable: Dial ER length (default 50) to your timeframe. Short for scalps, long for swing trades.
Example Settings in Action:
• 10s Chart (Hyper-Scalping): Set Source: Close, ER Length: 100, Fast Power: 1, Slow Power: 6. Catches micro-trends in crypto like a heat-seeking missile. Blue/yellow flips scream entry/exit on fast moves.
• 2m Chart (Quick Trades): Set Source: Close, ER Length: 14, Fast Power: 1, Slow Power: 6. Perfect for rapid trend shifts in stocks or forex. Signals align with momentum bursts—check historical flips for proof.
Deployment:
• Drop it on any chart. Backtest settings to match your asset’s volatility—tweak until it sings.
• Pair with RSI or volume spikes for killer confirmation. Pro move: Enter on flip + volume pop, exit on reverse.
• Strategy-Ready: Slap long/short logic on alerts to build a lean, mean trading machine.
Open source from SightLing Labs—grab it, hack it, profit from it. Share your tweaks in the comments and let’s outsmart the market together. Trade hard, win big!
Realized Volatility (StdDev of Returns, %)📌 Realized Volatility (StdDev of Returns, %)
This indicator measures realized volatility directly from price returns, instead of the common but misleading approach of calculating standard deviation around a moving average.
🔹 How it works:
Computes close-to-close log returns (the most common way volatility is measured in finance).
Calculates the standard deviation of these returns over a chosen lookback period (default = 200 bars).
Converts results into percentages for easier interpretation.
Provides three key volatility measures:
Daily Realized Vol (%) – raw standard deviation of returns.
Annualized Vol (%) – scaled by √250 trading days (market convention).
Horizon Vol (%) – volatility over a custom horizon (default = 5 days, i.e. weekly).
🔹 Why use this indicator?
Shows true realized volatility from historical returns.
More accurate than measuring deviation around a moving average.
Useful for traders analyzing risk, position sizing, and comparing realized vs implied volatility.
⚠️ Note:
It is best used on the Daily Chart!
By default, this uses log returns (which are additive and standard in quant finance).
If you prefer, you can easily switch to simple % returns in the code.
Volatility estimates depend on your chosen lookback length and may vary across timeframes.
Range Percent Histogram📌 Range Percent Histogram – Indicator Description
The Range Percent Histogram is a custom indicator that behaves like a traditional volume histogram, but instead of showing traded volume it displays the percentage range of each candle.
In other words, the height of each bar represents how much the price moved (in percentage terms) within that candle, from its low to its high.
🔧 What it shows
The indicator has two main components:
Component Description
Histogram Bars Columns plotted in red or green depending on the candle direction (green = bullish candle, red = bearish). The height of each bar = (high - low) / low * 100. That means a candle that moved, for example, 1 % from its lowest point to its highest point will show a bar with 1 % height.
Moving Average (optional) A 20-period Simple Moving Average applied directly to the bar values. It can be turned ON/OFF via a checkbox and helps you detect whether current range activity is above or below the average range of the past candles.
⚙️ How it works
Every time a new candle closes, the indicator calculates its range and converts it into a percentage.
This value is drawn as a column under the chart.
If the closing price is above the opening price → the bar is green (bullish range).
If the closing price is below the opening price → the bar is red (bearish range).
When the Show Moving Average option is enabled, a smooth line is plotted on top of the histogram representing the average percentage range of the last 20 candles.
📈 How to use it
This indicator is very helpful for detecting moments of range expansion or contraction.
One powerful way to use it is similar to a volume exhaustion / low-volume pattern:
Situation Interpretation
Consecutive bars with very low height Price is in a period of low volatility → possible accumulation or "pause" phase.
A sudden large bar after a series of small ones Indicates a strong pickup in volatility → often marks the start of a new impulse in the direction of the breakout.
Auto Fib V2Auto Fib V2 — Advanced Fibonacci Mapping Tool
Introduction
Auto Fib V2 is an advanced Fibonacci retracement indicator that automatically adapts to recent market ranges. Rather than manually drawing Fibonacci lines, this script dynamically maps them based on the most recent highs and lows, allowing traders to see the chart as if it were a "navigation map." Its primary purpose is to help identify potential buy and sell zones with greater clarity.
Key Concept
The script is built on a simple but powerful interpretation of Fibonacci retracement:
When the price moves below the 0.236 level, it suggests an oversold zone, where buyers may step in and market reversal potential increases.
When the price rises above the 0.764 level, it highlights an overbought zone, where sellers may become more active and risk of reversal grows.
Between these extremes, the Golden Pocket (0.382–0.618 zone) is highlighted as the area where institutional traders and algorithms often react. Historically, this is one of the most respected Fibonacci areas in technical analysis.
Features & Customization
Automatic Range Detection: The indicator automatically finds the recent high/low (based on user-defined lookback bars) and applies Fibonacci levels.
Flexible Direction Setting: Traders can use Auto Mode to let the script decide direction from price movement, or manually choose upward/downward mapping.
Multiple Levels Display: Beyond the standard levels, extra fractional retracements (0.146, 0.309, 0.441, etc.) are included for more precise mapping.
Golden Pocket Highlighting: Visually emphasizes the 0.382–0.618 retracement zone for quick recognition.
Custom Styles: Switch between line-based and dot-based plotting, with adjustable colors and transparency for improved readability.
Practical Use
Auto Fib V2 is not intended as a direct buy/sell signal generator, but as a contextual guide. Traders can use it to:
Confirm whether the current price area is closer to an overbought or oversold condition.
Combine it with oscillators (RSI, MACD) or trend indicators (EMA, ADX) to strengthen trading decisions.
Identify confluence zones where Fibonacci levels overlap with key supports/resistances.
Quickly adapt to market shifts without the need to redraw Fibonacci retracement lines repeatedly.
Why Use Auto Fib V2?
Manual Fibonacci drawing can be subjective, often depending on the swing points a trader chooses. Auto Fib V2 reduces that subjectivity by using consistent logic, creating a more systematic approach. For intraday traders, it provides rapid context to assess whether the market is stretched or balanced. For swing traders, it offers a map of reaction zones across higher timeframes.
Machine Learning BBPct [BackQuant]Machine Learning BBPct
What this is (in one line)
A Bollinger Band %B oscillator enhanced with a simplified K-Nearest Neighbors (KNN) pattern matcher. The model compares today’s context (volatility, momentum, volume, and position inside the bands) to similar situations in recent history and blends that historical consensus back into the raw %B to reduce noise and improve context awareness. It is informational and diagnostic—designed to describe market state, not to sell a trading system.
Background: %B in plain terms
Bollinger %B measures where price sits inside its dynamic envelope: 0 at the lower band, 1 at the upper band, ~ 0.5 near the basis (the moving average). Readings toward 1 indicate pressure near the envelope’s upper edge (often strength or stretch), while readings toward 0 indicate pressure near the lower edge (often weakness or stretch). Because bands adapt to volatility, %B is naturally comparable across regimes.
Why add (simplified) KNN?
Classic %B is reactive and can be whippy in fast regimes. The simplified KNN layer builds a “nearest-neighbor memory” of recent market states and asks: “When the market looked like this before, where did %B tend to be next bar?” It then blends that estimate with the current %B. Key ideas:
• Feature vector . Each bar is summarized by up to five normalized features:
– %B itself (normalized)
– Band width (volatility proxy)
– Price momentum (ROC)
– Volume momentum (ROC of volume)
– Price position within the bands
• Distance metric . Euclidean distance ranks the most similar recent bars.
• Prediction . Average the neighbors’ prior %B (lagged to avoid lookahead), inverse-weighted by distance.
• Blend . Linearly combine raw %B and KNN-predicted %B with a configurable weight; optional filtering then adapts to confidence.
This remains “simplified” KNN: no training/validation split, no KD-trees, no scaling beyond windowed min-max, and no probabilistic calibration.
How the script is organized (by input groups)
1) BBPct Settings
• Price Source – Which price to evaluate (%B is computed from this).
• Calculation Period – Lookback for SMA basis and standard deviation.
• Multiplier – Standard deviation width (e.g., 2.0).
• Apply Smoothing / Type / Length – Optional smoothing of the %B stream before ML (EMA, RMA, DEMA, TEMA, LINREG, HMA, etc.). Turning this off gives you the raw %B.
2) Thresholds
• Overbought/Oversold – Default 0.8 / 0.2 (inside ).
• Extreme OB/OS – Stricter zones (e.g., 0.95 / 0.05) to flag stretch conditions.
3) KNN Machine Learning
• Enable KNN – Switch between pure %B and hybrid.
• K (neighbors) – How many historical analogs to blend (default 8).
• Historical Period – Size of the search window for neighbors.
• ML Weight – Blend between raw %B and KNN estimate.
• Number of Features – Use 2–5 features; higher counts add context but raise the risk of overfitting in short windows.
4) Filtering
• Method – None, Adaptive, Kalman-style (first-order),
or Hull smoothing.
• Strength – How aggressively to smooth. “Adaptive” uses model confidence to modulate its alpha: higher confidence → stronger reliance on the ML estimate.
5) Performance Tracking
• Win-rate Period – Simple running score of past signal outcomes based on target/stop/time-out logic (informational, not a robust backtest).
• Early Entry Lookback – Horizon for forecasting a potential threshold cross.
• Profit Target / Stop Loss – Used only by the internal win-rate heuristic.
6) Self-Optimization
• Enable Self-Optimization – Lightweight, rolling comparison of a few canned settings (K = 8/14/21 via simple rules on %B extremes).
• Optimization Window & Stability Threshold – Governs how quickly preferred K changes and how sensitive the overfitting alarm is.
• Adaptive Thresholds – Adjust the OB/OS lines with volatility regime (ATR ratio), widening in calm markets and tightening in turbulent ones (bounded 0.7–0.9 and 0.1–0.3).
7) UI Settings
• Show Table / Zones / ML Prediction / Early Signals – Toggle informational overlays.
• Signal Line Width, Candle Painting, Colors – Visual preferences.
Step-by-step logic
A) Compute %B
Basis = SMA(source, len); dev = stdev(source, len) × multiplier; Upper/Lower = Basis ± dev.
%B = (price − Lower) / (Upper − Lower). Optional smoothing yields standardBB .
B) Build the feature vector
All features are min-max normalized over the KNN window so distances are in comparable units. Features include normalized %B, normalized band width, normalized price ROC, normalized volume ROC, and normalized position within bands. You can limit to the first N features (2–5).
C) Find nearest neighbors
For each bar inside the lookback window, compute the Euclidean distance between current features and that bar’s features. Sort by distance, keep the top K .
D) Predict and blend
Use inverse-distance weights (with a strong cap for near-zero distances) to average neighbors’ prior %B (lagged by one bar). This becomes the KNN estimate. Blend it with raw %B via the ML weight. A variance of neighbor %B around the prediction becomes an uncertainty proxy ; combined with a stability score (how long parameters remain unchanged), it forms mlConfidence ∈ . The Adaptive filter optionally transforms that confidence into a smoothing coefficient.
E) Adaptive thresholds
Volatility regime (ATR(14) divided by its 50-bar SMA) nudges OB/OS thresholds wider or narrower within fixed bounds. The aim: comparable extremeness across regimes.
F) Early entry heuristic
A tiny two-step slope/acceleration probe extrapolates finalBB forward a few bars. If it is on track to cross OB/OS soon (and slope/acceleration agree), it flags an EARLY_BUY/SELL candidate with an internal confidence score. This is explicitly a heuristic—use as an attention cue, not a signal by itself.
G) Informational win-rate
The script keeps a rolling array of trade outcomes derived from signal transitions + rudimentary exits (target/stop/time). The percentage shown is a rough diagnostic , not a validated backtest.
Outputs and visual language
• ML Bollinger %B (finalBB) – The main line after KNN blending and optional filtering.
• Gradient fill – Greenish tones above 0.5, reddish below, with intensity following distance from the midline.
• Adaptive zones – Overbought/oversold and extreme bands; shaded backgrounds appear at extremes.
• ML Prediction (dots) – The KNN estimate plotted as faint circles; becomes bright white when confidence > 0.7.
• Early arrows – Optional small triangles for approaching OB/OS.
• Candle painting – Light green above the midline, light red below (optional).
• Info panel – Current value, signal classification, ML confidence, optimized K, stability, volatility regime, adaptive thresholds, overfitting flag, early-entry status, and total signals processed.
Signal classification (informational)
The indicator does not fire trade commands; it labels state:
• STRONG_BUY / STRONG_SELL – finalBB beyond extreme OS/OB thresholds.
• BUY / SELL – finalBB beyond adaptive OS/OB.
• EARLY_BUY / EARLY_SELL – forecast suggests a near-term cross with decent internal confidence.
• NEUTRAL – between adaptive bands.
Alerts (what you can automate)
• Entering adaptive OB/OS and extreme OB/OS.
• Midline cross (0.5).
• Overfitting detected (frequent parameter flipping).
• Early signals when early confidence > 0.7.
These are purely descriptive triggers around the indicator’s state.
Practical interpretation
• Mean-reversion context – In range markets, adaptive OS/OB with ML smoothing can reduce whipsaws relative to raw %B.
• Trend context – In persistent trends, the KNN blend can keep finalBB nearer the mid/upper region during healthy pullbacks if history supports similar contexts.
• Regime awareness – Watch the volatility regime and adaptive thresholds. If thresholds compress (high vol), “OB/OS” comes sooner; if thresholds widen (calm), it takes more stretch to flag.
• Confidence as a weight – High mlConfidence implies neighbors agree; you may rely more on the ML curve. Low confidence argues for de-emphasizing ML and leaning on raw %B or other tools.
• Stability score – Rising stability indicates consistent parameter selection and fewer flips; dropping stability hints at a shifting backdrop.
Methodological notes
• Normalization uses rolling min-max over the KNN window. This is simple and scale-agnostic but sensitive to outliers; the distance metric will reflect that.
• Distance is unweighted Euclidean. If you raise featureCount, you increase dimensionality; consider keeping K larger and lookback ample to avoid sparse-neighbor artifacts.
• Lag handling intentionally uses neighbors’ previous %B for prediction to avoid lookahead bias.
• Self-optimization is deliberately modest: it only compares a few canned K/threshold choices using simple “did an extreme anticipate movement?” scoring, then enforces a stability regime and an overfitting guard. It is not a grid search or GA.
• Kalman option is a first-order recursive filter (fixed gain), not a full state-space estimator.
• Hull option derives a dynamic length from 1/strength; it is a convenience smoothing alternative.
Limitations and cautions
• Non-stationarity – Nearest neighbors from the recent window may not represent the future under structural breaks (policy shifts, liquidity shocks).
• Curse of dimensionality – Adding features without sufficient lookback can make genuine neighbors rare.
• Overfitting risk – The script includes a crude overfitting detector (frequent parameter flips) and will fall back to defaults when triggered, but this is only a guardrail.
• Win-rate display – The internal score is illustrative; it does not constitute a tradable backtest.
• Latency vs. smoothness – Smoothing and ML blending reduce noise but add lag; tune to your timeframe and objectives.
Tuning guide
• Short-term scalping – Lower len (10–14), slightly lower multiplier (1.8–2.0), small K (5–8), featureCount 3–4, Adaptive filter ON, moderate strength.
• Swing trading – len (20–30), multiplier ~2.0, K (8–14), featureCount 4–5, Adaptive thresholds ON, filter modest.
• Strong trends – Consider higher adaptive_upper/lower bounds (or let volatility regime do it), keep ML weight moderate so raw %B still reflects surges.
• Chop – Higher ML weight and stronger Adaptive filtering; accept lag in exchange for fewer false extremes.
How to use it responsibly
Treat this as a state descriptor and context filter. Pair it with your execution signals (structure breaks, volume footprints, higher-timeframe bias) and risk management. If mlConfidence is low or stability is falling, lean less on the ML line and more on raw %B or external confirmation.
Summary
Machine Learning BBPct augments a familiar oscillator with a transparent, simplified KNN memory of recent conditions. By blending neighbors’ behavior into %B and adapting thresholds to volatility regime—while exposing confidence, stability, and a plain early-entry heuristic—it provides an informational, probability-minded view of stretch and reversion that you can interpret alongside your own process.
