[FRK] Volatility-Adjusted Mean Reversion 🎯 What It Does :
- Spots when price has moved "too far" from average
- Adjusts for how jumpy/calm the market is right now
- Gives you better signals than simple oscillators
⚙️ Every Setting Explained:
- MA Length (9): How many bars for the "center line"
- Volatility Length (20): How many bars to measure "jumpiness"
- Threshold (0.04): When to actually signal you
- Price Input (Close): Which price to use
- MA Type (SMA): How to calculate the average
- Vol Multiplier (10.0): Just visual scaling
📊 Visual Guide:
- Blue line above red dotted = Price too high, expect drop
- Blue line below green dotted = Price too low, expect bounce
- Background colors = Active signals
- Table = Current stats and history
🧮 Simple Formula:
Signal = (Price - Average) ÷ Average ÷ (Volatility × 10)
When Signal > 0.04 or < -0.04 → Trade signal!
// ⚠️ IMPORTANT TRADING WARNING:
// DO NOT TRADE ON THIS SIGNAL ALONE! This is a confluence tool that helps you:
// • Understand current volatility vs historical levels
// • Get a "feel" for how extended current price moves are
// • Confirm other trading setups with volatility context
// • See when market is unusually calm or wild
波動率
[DIP] Inverse BB HighlightThis indicator allows you to highlight the area outside of the Bollinger Bands in order to draw more attention to it. This is especially useful for those who only trade when we are outside of the bands.
Keep in mind this indicator only works on bars, not on candles.
Liquidity Grab Detector (Stop Hunt Sniper) v2.2📌 Purpose
This indicator detects Stop Hunts (Liquidity Grabs) — false breakouts above/below recent highs or lows — filtered by trend direction, volatility, and volume conditions.
It is designed for scalpers and intraday traders who want to identify high-probability reversal zones.
🧠 How It Works
1. Key Logic
Detects previous swing high / swing low over the Lookback Bars.
Marks a false breakout when price moves beyond the level and closes back inside.
Requires a volume spike on the breakout to confirm liquidity sweep.
2. Trend Filter (EMA 50)
Bullish signals only if price is above EMA 50.
Bearish signals only if price is below EMA 50.
This removes most counter-trend stop hunts.
3. ADX Filter
Signals appear only when ADX < Max ADX (low-trend conditions).
This avoids false signals in strong trending markets.
📈 How to Use
Green Arrows: Bullish stop hunt (potential long entry).
Red Arrows: Bearish stop hunt (potential short entry).
Works best in range conditions, liquidity zones, or near session highs/lows.
Combine with order flow, volume profile, or price action for extra confirmation.
Recommended Timeframes: 1m–15m for scalping; 30m–1h for intraday.
Markets: Crypto, Forex, Indices.
⚙️ Inputs
Lookback Bars — swing detection
Volume Spike Multiplier
EMA Length (trend filter)
Min Retrace — how much price must return inside range
Max ADX — trend filter sensitivity
⚠️ Disclaimer
This script is for educational purposes only and does not constitute financial advice.
Always test thoroughly before live trading.
Open Interest Screener (Fixed Zones)📌 Purpose
This indicator scans Open Interest (OI) changes across selected exchanges and highlights significant spikes or drops directly on the chart using dynamic shaded zones.
It is designed to help traders detect unusual market positioning changes that may precede volatility events.
🧠 How It Works
1. Data Sources
Supports multiple exchanges: BitMEX USD, BitMEX USDT, Kraken USD (toggle on/off in settings).
Automatically adapts symbol prefix based on the chart’s base asset.
2. Spike / Drop Detection
OI % Change is calculated over a configurable lookback (Bars to look back).
Spike Up: OI increases by more than Threshold %.
Spike Down: OI decreases by more than Threshold %.
3. Dynamic Zones
When a spike occurs, a green zone (increase) or red zone (decrease) is drawn on the chart.
Zone height is dynamic, based on price high/low ± 5%, preventing chart distortion.
Minimum spacing (Zone Spacing) prevents clustering.
📈 How to Use
Green Zones: Large OI increase can signal fresh positioning (possible breakout setups).
Red Zones: Large OI decrease can signal liquidation events or position unwinds.
Combine with price action, funding rates, or volatility measures for higher confidence.
Recommended Timeframes: Works best on 15m, 1h, 4h.
Markets: Crypto derivatives (OI data available).
⚙️ Inputs
Bars to Look Back
OI % Change Threshold
Zone Width
Exchange toggles (BitMEX USD/USDT, Kraken USD)
⚠️ Disclaimer
This script is for educational purposes only and does not constitute financial advice.
Always test thoroughly before live trading.
Volume Scanner (Spikes & Drops) [Context]📌 Purpose
This indicator detects significant volume spikes or drops and optionally filters them by price context (local highs/lows).
It helps identify potential breakout or exhaustion points with improved signal quality compared to raw volume alerts.
🧠 How It Works
1. Volume Spike / Drop Detection
SMA Volume over N bars is calculated as baseline.
Volume Spike: Volume > SMA × Spike Multiplier (default 1.5×).
Volume Drop: Volume < SMA × Drop Multiplier (default 0.5×).
2. Context Filter (optional)
When Use Context = ON:
Bullish Context: Volume spike at/near local price high (last Lookback bars).
Bearish Context: Volume drop at/near local price low (last Lookback bars).
3. Signal Gap
Minimum spacing between signals (Min Gap Bars) prevents excessive clustering.
4. Visuals
Background shading:
Green = Volume Spike in bullish context.
Red = Volume Drop in bearish context.
Alerts can be configured for both conditions.
📈 How to Use
Volume Spikes near highs can indicate breakouts or exhaustion tops.
Volume Drops near lows can signal liquidity dry-up or potential reversals.
Combine with price action or support/resistance for confirmation.
Recommended Timeframes: Works on all timeframes; more reliable on 15m, 1h, 4h.
Markets: Crypto, Forex, Stocks.
⚙️ Inputs
Volume SMA Length
Spike Multiplier / Drop Multiplier
Use Context (High/Low filter)
Min Gap Bars (avoid clustered signals)
⚠️ Disclaimer
This script is for educational purposes only. It does not constitute financial advice.
Always test thoroughly before live trading.
Smart Volatility Squeeze + Trend Filter📌 Purpose
This indicator detects volatility squeeze conditions when Bollinger Bands contract inside Keltner Channels and signals potential breakout opportunities.
It also includes an optional EMA-based trend filter to align signals with the dominant market direction.
🧠 How It Works
1. Squeeze Condition
Bollinger Bands (BB): Length = 20, StdDev = 2.0 (default)
Keltner Channels (KC): EMA Length = 20, ATR Multiplier = 1.5 (default)
Squeeze ON: Occurs when BB Upper < KC Upper and BB Lower > KC Lower (low volatility zone).
2. Breakout Signals
Long Breakout: Price crosses above BB Upper after squeeze.
Short Breakout: Price crosses below BB Lower after squeeze.
3. Trend Filter (optional)
EMA(50) used to confirm breakout direction:
Long signals allowed only if price > EMA(50)
Short signals allowed only if price < EMA(50)
Toggle Use Trend Filter to enable/disable.
4. Visual & Alerts
Green circle at chart bottom indicates Squeeze ON.
Green/Red triangles mark breakouts.
Background gradually brightens during squeeze buildup.
Alerts available for long and short breakouts.
📈 How to Use
Look for Squeeze ON → then wait for breakout arrows.
Trade in breakout direction, preferably with trend filter ON.
Works best on higher timeframes (1h, 4h, D) and trending markets.
Markets: Crypto, Forex, Stocks — effective in volatile assets.
⚙️ Inputs
BB Length / StdDev
KC EMA Length / ATR Multiplier
Use Trend Filter
Trend EMA Length
⚠️ Disclaimer
This script is for educational purposes only. It does not constitute financial advice.
Always test thoroughly before live trading.
Smart Impulse Exhaustion Finder (ATR + ADX Filter)📌 Purpose
This indicator detects potential exhaustion of strong bullish or bearish impulses at fresh swing highs/lows by combining multiple price action and volatility-based filters.
🧠 How It Works
A signal is triggered only when all core conditions are satisfied:
1. Swing High/Low Detection
Current high (or low) must be the highest (or lowest) over the last Extremum Lookback bars (default: 50).
This ensures the move is significant relative to recent price action.
2. Impulse Confirmation
Price must extend by at least 1 × ATR from the previous swing point.
This filters out minor fluctuations.
3. Exhaustion Conditions (at least 2 out of 3 must be met)
RSI Extreme: RSI > Overbought Level (default: 80) for bearish signals, RSI < Oversold Level (default: 20) for bullish signals.
Volume Spike: Volume > SMA(Volume, Volume SMA Length) × Volume Spike Multiplier.
Candle Wick Rejection: Upper wick ≥ Wick Threshold % for bearish setups, Lower wick ≥ Wick Threshold % for bullish setups.
4. Trend Filter
ADX > ADX Threshold ensures the market is trending and filters out sideways conditions.
5. Candle Body Filter
Candle body must be ≥ Body Size ATR Factor × ATR.
This avoids weak signals from small candles or doji formations.
📈 How to Use
Bearish Signal:
Appears at fresh swing highs with exhaustion conditions met. Useful for tightening stops, taking partial profits, or counter-trend shorts.
Bullish Signal:
Appears at fresh swing lows with exhaustion conditions met. Useful for trailing stops, profit-taking, or counter-trend longs.
Recommended Timeframes: Works best on 1h, 4h, and Daily charts.
Markets: Crypto, Forex, Stocks — wherever volatility and trends are present.
⚙️ Inputs
RSI Length / Overbought / Oversold
Volume SMA Length & Volume Spike Multiplier
Wick Threshold %
Extremum Lookback (bars for highs/lows)
ADX Length & Threshold
Body Size ATR Factor
⚠️ Disclaimer
This script is for educational purposes only and does not constitute financial advice.
Always test thoroughly and apply proper risk management before live trading.
💡 Tip: Combine this tool with your own market context and confluence factors for higher probability setups.
PrismNorm (Rolling)# PrismNorm (Rolling)
Overview
PrismNorm (Rolling) frames four series — VWMA, TWMA, TrueWMA, and a half-price line — over a fixed lookback window, with all series scaled by a chosen volatility measure. Each bar shows how far price has strayed from its rolling anchor, expressed in StdDev, MAD, ATR-scaled, or fixed-percent units.
How It Works
• Compute rolling Weighted Moving Averages over the last lookback bars:
— VWMA: volume-weighted HLC3
— TWMA: simple average of OHLC midpoint
— TrueWMA: TrueRange-weighted TrueMid average
• Anchor each series to its value lookback bars ago (first bar in window). The half-price series uses either close or an SMA lagged by half the window.
• Calculate a volatility measure over volWindowLen = lookback × normMult bars:
— Std Dev of close
— MAD of close
— ATR averaged and scaled to approximate σ
— A fixed percent of the window’s anchor value
• Band width = volatility (or percent of anchor). Normalized output = (net move) ÷ (band width)
Inputs
Settings / Description
• Lookback Period (bars) / Bars used for rolling WMAs and as the anchor lookback
• Deviation Measure / Volatility method: Std Dev, MAD, ATR (scaled), or Percent
• Normalization Span (×Lookback) / Multiplier (1–10) to expand lookback into volatility window
• Percent Deviation (%) / When Percent mode is on, band width = this % of the anchor WMA (or price)
• Scale MAD to σ / Scale Mad by √(π/2) so it aligns with σ under Normal distribution
• Use MA Anchor for Price (½×) / Off: anchor = close ; On: anchor = SMA(close, lookback) shifted by half the lookback
Display
• Show Normalized VWMA
• Show Normalized TWMA
• Show Normalized TrueWMA
• Show Normalized Price (½×)
Tips & Use Cases
• Percent mode yields fixed-width bands, handy for identifying structural shifts without volatility scaling.
• Toggling the MA anchor smooths the reference point, reducing noise in price normalization.
References:
1. TrueWMA Description
## 1. TrueWMA: Volatility-Weighted Price Averaging
What Is TrueWMA?
TrueWMA weights each bar’s TrueMid (TrueRange midpoint) by its TrueRange, so high-volatility bars carry more influence. It blends price level and volatility into one moving average.
In short, it’s a *TrueRange-weighted TrueMid average*.
Pseudocode
// TWMA Example for Comparison
window_size = 50
OHLC = (Open + High + Low + Close) / 4
TWMA = MA(OHLC, window_size)
// VWMA Example for Comparison
window_size = 50
HLC3 = (High + Low + Close) / 3
VWMA = Sum(HLC3 * Volume, window_size) / Sum(Volume, window_size)
// TrueWMA (Rolling)
window_size = 50
max_val = Maximum(Close , High) // TrueRange High
min_val = Minimum(Close , Low) // TrueRange Low
true_mid = (max_val + min_val) / 2 // TrueMid
TrueWMA = Sum(true_mid * TrueRange, window_size) / Sum(TrueRange, window_size)
Interpretation
For each bar, Rolling TrueWMA:
• Computes a TrueMid (“contextual midpoint”) from the prior close and the current bar’s high/low.
• Weights each TrueMid by that bar’s TrueRange.
• Divides the sum of those weighted midpoints by the total TrueRange over the lookback window.
The result is a single series that dynamically blends price levels with recent volatility.
ATR as % of CloseATR 14day period in % terms
the Normal ATR indicator by TV helps but this gives a clear idea as to the range in percentage terms as and when market rises to newer and newer highs
better than an absolute value
PrismNorm (Anchored)# PrismNorm (Anchored)
Overview
PrismNorm plots anchored, span-normalized price averages (VWAP, TWAP, TrueWAP) alongside a half-price line, with all series scaled by a blended volatility measure. This frames price swings across anchor periods of varying lengths in units of recent volatility.
How It Works
On each new anchor span (session, week, month, etc.), the script:
• Resets an anchor line to the first bar’s open.
• Computes raw VWAP, TWAP, TrueWAP and a half-price delta (close–anchor)/2 cumulatively over the span.
• Calculates a deviation metric (Std Dev, MAD, ATR-scaled, or Percent of anchor price) for the current span.
• Blends the current span’s deviation with up to N prior spans (for non-Percent modes).
• Divides each net price series by the blended deviation to yield normalized outputs.
Inputs
Settings / Description
• Anchor Period / Span for resetting the anchor line (Week, Month, etc.)
• Deviation Measure / Volatility method for normalization: Std Dev, MAD, ATR (scaled), or Percent
• Normalization Interval / Number of past spans (current+1 … current+10) to include in blended deviation
• Percent Deviation (%) / Band width % when Percent mode is selected (applied to anchor price)
• Scale MAD to σ / Scale MAD by √(π/2) so it aligns with σ under Normal distribution
Display
• Show Normalized VWAP
• Show Normalized TWAP
• Show Normalized TrueWAP
• Show Normalized Price (½×)
Tips & Use Cases
• Use shorter anchor spans (Session, Week) for intraday normalization.
• Use longer spans (Quarter, Year) to compare price action across macro periods.
References:
1. TrueWAP Description
2. SD, MAD, ATR (scaled) Deviation Measure Methodology
## 1. TrueWAP: Volatility-Weighted Price Averaging
What Is TrueWAP?
TrueWAP plugs actual price fluctuations into your average. Instead of only tracking time (TWAP) or volume (VWAP), it weights each bar’s TrueMid (TrueRange midpoint) by its TrueRange—so when the market moves more, that bar counts more.
In short, it’s a *TrueRange-weighted TrueMid average* anchored at your start date.
TrueWAP (Anchored) Overview
• On the first bar, it uses the simple high-low midpoint for price and the bar’s high-low range for weighting.
• From the next bar onward, it computes TrueMid (TrueRange midpoint).
• Each TrueMid is weighted by its TrueRange and cumulatively summed from the anchor point.
Pseudocode
// TWAP Example for Comparison
current_days = BarsSince("start_of_period")
OHLC = (Open + High + Low + Close) / 4
TWAP = MA(OHLC, current_days)
// VWAP Example for Comparison
current_days = BarsSince("start_of_period")
HLC3 = (High + Low + Close) / 3
VWAP = Sum(HLC3 * Volume, current_days) / Sum(Volume, current_days)
// TrueWAP (Anchored)
current_days = BarsSince("start_of_period") // Count of bars since the period began
first_bar = (current_days == 0) // Boolean flag if current bar is 1st of period
hilo_mid = (High + Low) / 2
max_val = max(Close , High)
min_val = min(Close , Low)
true_mid = (max_val + min_val) / 2
// Use hilo_mid and (High - Low) for the first bar; otherwise, use true_mid and True Range
mid_val = IF(first_bar, hilo_mid, true_mid)
range_val = IF(first_bar, (High - Low), TrueRange)
TrueWAP = Sum(mid_val * range_val, current_days) / Sum(range_val, current_days)
Recap: Interpretation
• The first bar uses the simple high-low midpoint and range.
• Subsequent bars use TrueMid and TrueRange based on prior close.
• This ensures the average reflects only the observed volatility and price since the anchor.
A Note on True Range
TrueRange captures the full extent of bar-to-bar volatility as the maximum of:
• High – Low
• |High – Previous Close|
• |Low – Previous Close|
## 2. SD, MAD, ATR (scaled) Deviation Measure Methodology: Segmented Weighted-Average Volatility
### Introduction
Conventional standard deviation calculations aggregate data over an expanding window and rely on a single mean, producing one summary statistic. This can obscure segmented, sequential datasets—such as MTD, QTD, and YTD—where additional granularity and time-sensitive insights matter.
This methodology isolates standard deviation within defined time frames and then proportionally allocates them based on custom lookback criteria. The result is a dynamic, multi-period normalization benchmark that captures both emerging volatility and historical stability.
Note: While this example uses SD, the same fixed-point approach applies to MAD and ATR (scaled).
### 2.1 Standard Deviation (Rolling Window)
pseudocode
// -- STANDARD DEVIATION (ROLLING) Calculation --
window_size = 20
rolling_SD = STDDEV(Close, window_size)
• Ideal for immediate trading insights.
• Reflects pure, short-term price dynamics.
• Captures volatility using the most recent 20 bars.
### 2.2 Blended SD: Current + 3 Past Periods
This method fuses current month data with the last three complete months.
pseudocode
// -- MULTI-PERIOD STANDARD DEVIATION (PROXY) with Three Past Periods --
current_days = BarsSince("start_of_month")
current_SD = STDDEV(Close, current_days)
prev1_days = TradingDaysLastMonth
prev1_SD = STDDEV_LastMonth(Close)
prev2_days = TradingDaysTwoMonthsAgo
prev2_SD = STDDEV_TwoMonthsAgo(Close)
prev3_days = TradingDaysThreeMonthsAgo
prev3_SD = STDDEV_ThreeMonthsAgo(Close)
// Blending with Proportional Weights
Weighted_SD = (current_SD * current_days +
prev1_SD * prev1_days +
prev2_SD * prev2_days +
prev3_SD * prev3_days) /
(current_days + prev1_days + prev2_days + prev3_days)
• Merges evolving volatility with the stability of three prior months.
• Weights each period by its trading days.
• Yields a robust normalization benchmark.
### 2.3 Blended SD: Current + 1 Past Period
This variant tempers emerging volatility by blending the current month with last month only.
pseudocode
// -- MULTI-PERIOD STANDARD DEVIATION (PROXY) with One Past Period --
current_days = BarsSince("start_of_month")
current_SD = STDDEV(Close, current_days)
prev1_days = TradingDaysLastMonth
prev1_SD = STDDEV_LastMonth(Close)
// Proportional Blend
Weighted_SD = (current_SD * current_days +
prev1_SD * prev1_days) /
(current_days + prev1_days)
• Anchors current volatility to last month’s baseline.
• Softens spikes by blending with historical data.
Conclusion
Segmented weighted-average volatility transforms global benchmarking by integrating immediate market dynamics with historical context. This fixed-point approach—applicable to SD, MAD, and ATR (scaled)—delivers time-sensitive analysis.
Master Trend Navigator/趋势大师导航仪[4H] by mrlazycat趋势大师导航仪使用说明
⚠ 非常重要，使用指标前请认真阅读这个使用说明
指标核心功能 本指标通过分析比特币的成交量、动能指标（MACD）、相对强弱指数（RSI）、趋势强度和成交量比率，生成在-1到1之间波动的趋势大师导航仪，帮助判断买卖时机。指标最佳适用场为4小时（4H）图表，适合1-2周的中短期交易。该趋势大师导航仪适用于 BTC,ETH, DOGE 等现货成交量大的虚拟货币
趋势曲线解读指南
① 市场状态（曲线颜色）
暗紫色：区间震荡市场 浅红色：弱多头趋势 深红色：强多头趋势 浅绿色：弱空头趋势 深绿色：强空头趋势
② 关键信号区域
红色区域（超买）：趋势曲线 ≥ 0.6 时，可能出现回调风险
绿色区域（超卖）：趋势曲线 ≤ -0.615 时，可能出现反弹机会
③ 锁定机制
在强多头趋势（深红色）和深绿色（强空头趋势）和部分弱趋势期间：
如果趋势曲线突破红色区域（超买）且市场趋势强度保持在强趋势或较强的弱趋势，趋势曲线会锁定在0.7附近（原始曲线以灰色继续）。
如果趋势曲线跌破绿色区域（超卖）且市场趋势强度保持在强趋势或较强的弱趋势，趋势曲线会锁定在-0.7附近（原始曲线以灰色继续）。 这表示趋势可能继续发展，建议等待锁定期结束后再进行操作。
✅ 极端多头趋势的特殊案例：（如ETH在2025年7月10日到20日，趋势曲线一直维持红色，意味着多头趋势不变。但这段时间ETH的趋势曲线曾跌到超卖区，因此曲线曾在底部锁定3个K线的时间，这意味着是多头右侧追多的机会。）
交易信号
① 超买超卖信号
红色区域（超买）：趋势曲线 ≥ 0.6 时，可能出现回调风险
绿色区域（超卖）：趋势曲线 ≤ -0.615 时，可能出现反弹机会
② 成交量爆发信号
顶部红色圆圈：代表成交量比率的爆发期，可能在当前或未来1-6根K线内出现阶段性高点。
底部黄色圆圈：代表成交量比率的潜在底部机会，可能在当前或未来1-6根K线内出现阶段性低点。
✅ 注意连续大量的顶部红色圆圈和底部黄色圆圈的出现，这意味着极端行情的出现。
③ 背离信号
顶背离（卖出信号）：红色倒三角图标（标记为Bearish divergence\Sell）出现在趋势曲线顶部，当价格创新高但趋势曲线未创新高时触发，预示大幅回调风险。
底背离（买入信号）：绿色正三角图标（标记为Bullish divergence\Buy）出现在趋势曲线底部，当价格创新低但趋势曲线未创新低时触发，预示底部反弹机会。
使用注意事项
① 交易所推荐：同时使用币安(Binance)和OKX的BTC/USDT现货数据（不同交易所的量能差异可能影响信号准确性）。
② 特殊行情优化：已针对2024-2025年比特币ETF上市后的低波动行情调整参数，未来将持续根据市场变化优化。
③ 强趋势操作提示：当趋势曲线锁定在超买或超卖区，应减少逆势操作。
④ 首次使用建议：观察历史行情以验证信号特征，震荡市捕捉反转点，趋势市识别延续信号。
最简单操作要诀
✅ 底部抄底组合：强空头趋势转弱空头 + 绿色超卖区 + 底背离绿色三角 + 底部黄色成交量圈
✅ 顶部逃顶组合：强多头趋势转弱多头趋势转换 + 红色超买区 + 顶背离红色三角 + 顶部红色成交量圈
✅ 趋势延续信号：趋势曲线锁定在 ±0.7 时，耐心等待锁定解除
推特联系：Jeffmo0769
Trend Master Navigator User Guide
⚠ Important: Please read this guide carefully before using the indicator
Core Functionality
This indicator analyzes Bitcoin's trading volume, MACD, RSI, trend strength, and volume ratio to generate the Trend Master Navigator, which oscillates between -1 and 1 to assist in buy/sell decisions. The indicator is best suited for 4-hour (4H) charts and is ideal for 1-2 week swing trading.The Trend Master Navigator is suitable for cryptocurrencies with high spot trading volumes, such as BTC ， ETH , and DOGE .
Interpreting the Trend Curve
① Market States (Curve Colors)
Dark Purple: Range-bound market
Light Red: Weak bullish trend
Deep Red: Strong bullish trend
Light Green: Weak bearish trend
Deep Green: Strong bearish trend
② Key Signal Zones
Red Zone (Overbought): Trend curve ≥ 0.6 → Potential pullback risk
Green Zone (Oversold): Trend curve ≤ -0.615 → Potential rebound opportunity
③ Locking Mechanism
During strong bullish trends (deep red) and strong bearish trends (deep green), and partial weak trends:
If the trend curve breaks above the red zone (overbought) and market trend strength remains in a strong trend or robust weak trend, the trend curve will lock near 0.7 (original curve continues in gray).
If the trend curve breaks below the green zone (oversold) and market trend strength remains in a strong trend or robust weak trend, the trend curve will lock near -0.7 (original curve continues in gray).
This indicates that the trend may continue, and it is advisable to wait until the lock period ends before taking action.
✅ In the context of extreme bullish trends (e.g., ETH from July 10 to 20, 2025, where the trend curve remained red, indicating a persistent bullish trend), even though ETH's trend curve once dipped into the oversold zone, causing the curve to lock at the bottom for 3 K-line periods, this signifies a right-side buying opportunity during the bullish trend.
Trading Signals
① Overbought/Oversold Signals
Red Zone (Overbought): Trend curve ≥ 0.6 → Potential pullback risk
Green Zone (Oversold): Trend curve ≤ -0.615 → Potential rebound opportunity
② Volume Explosion Signals
Top Red Circle: Represents a volume ratio explosion period, possibly indicating a phase peak within the current or next 1-6 bars.
Bottom Yellow Circle: Represents a potential bottom opportunity in volume ratio, possibly indicating a phase trough within the current or next 1-6 bars.
✅ Pay attention to the continuous appearance of top red circles and bottom yellow circles, as this signals the emergence of extreme market conditions.
③ Divergence Signals
Bearish Divergence (Sell): Red inverted triangle icon (marked as Bearish divergence\Sell) appears at the trend curve top when the price makes a new high, but the trend curve does not; this indicates a significant pullback risk.
Bullish Divergence (Buy): Green upright triangle icon (marked as Bullish divergence\Buy) appears at the trend curve bottom when the price makes a new low, but the trend curve does not; this indicates a potential bottom rebound opportunity.
Other Usage Notes
① Exchange Recommendation: Use Binance and OKX BTC/USDT spot data simultaneously (volume discrepancies across different exchanges may affect signal accuracy).
② Special Market Optimization: Parameters have been adjusted for the low-volatility era following the Bitcoin ETF launch (2024-2025) and will continue to be optimized based on market changes.
③ Strong Trend Operation Tips: When the trend curve is locked in overbought or oversold zones, reduce counter-trend operations.
④ First Use Recommendation: Observe historical market trends to validate signal characteristics. Capture reversal points in range-bound markets and identify continuation signals in trending markets.
Simplest Trading Tactics
✅ Bottom Picking Setup: Transition from strong bearish trend to weak bearish + Green oversold zone + Bullish divergence green triangle + Bottom yellow volume circle
✅ Top Selling Setup: Transition from strong bullish trend to weak bullish trend + Red overbought zone + Bearish divergence red triangle + Top red volume circle
✅ Trend Continuation Signal: Trend curve locked at ±0.7 → Wait patiently for lock release
Contact on X: Jeffmo0769
Price Exhaustion Envelope [BackQuant]Price Exhaustion Envelope
Visual preview of the bands:
What it is
The Price Exhaustion Envelope (PEE) is a multi‑factor overextension detector wrapped inside a dynamic envelope framework. It measures how “tired” a move is by blending price stretch, volume surges, momentum and acceleration, plus optional RSI divergence. The result is a composite exhaustion score that drives both on‑chart signals and the adaptive width of three optional envelope bands around a smoothed baseline. When the score spikes above or below your chosen threshold, the script can flag exhaustion, paint candles, tint the background and fire alerts.
How it works under the hood
Exhaustion score
Price component: distance of close from its mean in standard deviation units.
Volume component: normalized volume pressure that highlights unusual participation.
Momentum component: rate of change and acceleration of price, scaled by their own volatility.
RSI divergence (optional): bullish and bearish divergences gently push the score lower or higher.
Mode control: choose Price, Volume, Momentum or Composite. Composite averages the main pieces for a balanced view.
Energy scale (0 to 100)
The composite score is pushed through a logistic transform to create an “energy” value. High energy (above 70 to 80) signals a move that may be running hot, while very low energy (below 20 to 30) points to exhaustion on the downside.
Envelope engine
Baseline: EMA of price over the main lookback length.
Width: base width is standard deviation times a multiplier.
Type selector:
• Static keeps the width fixed.
• Dynamic expands width in proportion to the absolute exhaustion score.
• Adaptive links width to the energy reading so bands breathe with market “heat.”
Smoothing: a short EMA on the width reduces jitter and keeps bands pleasant to trade around.
Band architecture
You can toggle up to three symmetric bands on each side of the baseline. They default to 1.0, 1.6 and 2.2 multiples of the smoothed width. Soft transparent fills create a layered thermograph of extension. The outermost band often maps to true blow‑off extremes.
On‑chart elements
Baseline line that flips color in real time depending on where price sits.
Up to three upper and lower bands with progressive opacity.
Triangle markers at fresh exhaustion triggers.
Tiny warning glyphs at extreme upper or lower breaches.
Optional bar coloring to visually tag exhausted candles.
Background halo when energy > 80 or < 20 for instant context.
A compact info table showing State, Score, Energy, Momentum score and where price sits inside the envelope (percent).
How to use it in trading
Mean reversion plays
When price pierces the outer band and an exhaustion marker prints, look for reversal candles or lower‑timeframe confirmation to fade the move back toward the baseline.
For conservative entries, wait for the composite score to roll back under the threshold or for energy to drop from extreme to neutral.
Set stops just beyond the extreme levels (use extreme_upper and extreme_lower as natural invalidation points). Targets can be the baseline or the opposite inner band.
Trend continuation with smart pullbacks
In strong trends, the first tag of Band 1 or Band 2 against the dominant direction often offers low‑risk continuation entries. Use energy readings: if energy is low on a pullback during an uptrend, a bounce is more likely.
Combine with RSI divergence: hidden bullish divergence near a lower band in an uptrend can be a powerful confirmation.
Breakout filtering
A breakout that occurs while the composite score is still moderate (not exhausted) has a higher chance of follow‑through. Skip signals when energy is already above 80 and price is punching the outer band, as the move may be late.
Watch env_position (Envelope %) in the table. Breakouts near 40 to 60 percent of the envelope are “healthy,” while those at 95 percent are stretched.
Scaling out and risk control
Use exhaustion alerts to trim positions into strength or weakness.
Trail stops just outside Band 2 or Band 3 to stay in trends while letting the envelope expand in volatile phases.
Multi‑timeframe confluence
Run the script on a higher timeframe to locate exhaustion context, then drill down to a lower timeframe for entries.
Opposite signals across timeframes (daily exhaustion vs. 5‑minute breakout) warn you to reduce size or tighten management.
Key inputs to experiment with
Lookback Period: larger values smooth the score and envelope, ideal for swing trading. Shorter values make it reactive for scalps.
Exhaustion Threshold: raise above 2.0 in choppy assets to cut noise, drop to 1.5 for smooth FX pairs.
Envelope Type: Dynamic is great for crypto spikes, Adaptive shines in stocks where volume and volatility wave together.
RSI Divergence: turn off if you prefer a pure price/volume model or if divergence floods the score in your asset.
Alert set included
Fresh upper exhaustion
Fresh lower exhaustion
Extreme upper breach
Extreme lower breach
RSI bearish divergence
RSI bullish divergence
Hook these to TradingView notifications so you get pinged the moment a move hits exhaustion.
Best practices
Always pair exhaustion signals with structure. Support and resistance, liquidity pools and session opens matter.
Avoid blindly shorting every upper signal in a roaring bull market. Let the envelope type help you filter.
Use the table to sanity‑check: a very high score but mid‑range env_position means the band may still be wide enough to absorb more movement.
Backtest threshold combinations on your instrument. Different tickers carry different volatility fingerprints.
Final note
Price Exhaustion Envelope is a flexible framework, not a turnkey system. It excels as a context layer that tells you when the crowd is pressing too hard or when a move still has fuel. Combine it with sound execution tactics, risk limits and market awareness. Trade safe and let the envelope breathe with the market.
Custom NY Opening Bell - Today OnlyThis indicator shows NYC ET opening bell.
It will displace a dashed line on it.
This can be very useful for trades journaling their trades with screenshots.
My indicator will let you know when opening bell happened.
It is also very great when doing backtesting.
Multi Rate of Change (ROC) - 3 LinesMulti Rate of Change (ROC) - 3 Lines
This custom indicator displays three Rate of Change (ROC) lines, each with independently adjustable lookback periods (default: 7, 30, and 100 days). It allows you to quickly compare short-, mid-, and long-term price momentum on the same chart.
All ROC lines show the percent change of the close price compared to N bars ago.
The color, thickness, and style (solid, dotted, dashed) of each ROC line can be customized in the settings.
A zero reference line is included and can also be customized.
Suitable for momentum analysis and identifying trend acceleration or deceleration at multiple timeframes.
Designed for easy use: simply add the indicator to your chart and adjust the settings as needed.
How to use:
Add the indicator to your chart.
Set each ROC period (e.g., 7, 30, 100 days) as desired.
Adjust colors, line widths, and styles for better visibility.
Interpret positive ROC values as upward momentum, negative values as downward momentum.
No repainting. All calculations use close prices only.
If you need more ROC lines or additional features, let me know!
MR.Z Stoch RSI %K Reversal Signals🟢 K Strategy Description
The K Strategy is a momentum-based trading technique using the %K line from the Stochastic Oscillator. It is designed to detect potential reversal points in price trends by identifying extreme conditions of overbought and oversold levels.
✅ Core Logic:
The strategy monitors the %K line (a smoothed form of RSI momentum).
A Buy Signal is triggered when:
The %K line dips to or below a defined lower threshold (commonly 30 or less).
This suggests the asset is oversold and may soon reverse upward.
A Sell Signal is triggered when:
The %K line peaks above an upper threshold (commonly 70 or more).
This suggests the asset is overbought and may reverse downward.
⚙️ Adjustable Parameters:
K Length: The sensitivity of the %K calculation (affects how fast it responds).
Buy Level: Set your oversold trigger (e.g., 20–40).
Sell Level: Set your overbought trigger (e.g., 60–100).
Signal Smoothing (optional): Helps reduce noise and avoid false triggers.
📈 Use Case:
This strategy is effective in ranging markets where prices frequently oscillate. It can also be used with other indicators (like EMA, volume filters, or price action confirmation) to increase accuracy in trending conditions.
Turttle_Dalmata Indicator v10📘 Turttle_Dalmata Indicator – Overview
The Turttle_Dalmata v10 is a proprietary trading indicator engineered for high-precision intraday scalping and trend breakout validation. It combines real-time price action, volume dynamics, and multi-timeframe confluence to generate high-quality entry signals while filtering out noise and chop.
⸻
🧠 What It Does
• Dynamically scores market conditions using a multi-layered confluence engine
• Detects trend-aligned breakout setups, fair value gaps, and volume surges
• Uses a session-anchored VWAP to keep entries near equilibrium
• Implements advanced filtering logic to avoid signals during overextended or sideways conditions
• Includes intelligent signal throttling to prevent back-to-back entries in choppy markets
⸻
🎯 Why It Works
• Filters out low-conviction moves and extended breakouts that often lead to reversals
• Waits for structure-confirmed and volume-backed price breaks
• Avoids false signals by enforcing cooldown windows and signal cycle rotation
⸻
🧠 Core Features
• 🔟 Confluence Scoring System: Combines EMA trend, RSI strength, volume spikes, break of structure, fair value gaps, CVC momentum, and more.
• 🟣 Market Cipher-Style VWAP: Uses a daily session VWAP anchored at 00:00 UTC for equilibrium-based trade filters.
• 🧮 Custom Signal Filtering:
• ✅ VWAP max distance filter – blocks trades too far from VWAP (mean reversion bias)
• ✅ Cooldown system – blocks signals if another signal happened in the last X bars (default: 5)
• ✅ EMA velocity – detects acceleration during breakouts
• 🔁 Signal Lock Logic: Prevents same-side signals from repeating until an opposite signal occurs.
📈 How It Looks
• 🔼 Green triangles for high-probability long entries
• 🔽 Red triangles for high-probability short entries
• Clean visual overlays: session VWAP and EMA for trend tracking
⸻
✅ Optimized For
• 1-minute and 2-minute charts
• Crypto and futures markets
• Traders who value signal quality over quantity
Enhanced Predator Suite🎯 Simple Predator Suite Guide - What You See on Your Chart
📍 What to Look For RIGHT NOW on Your BTC Chart
1. BAR COLORS (Most Important)
Look at the color of each price bar:
🟢 BRIGHT GREEN = BUY SIGNAL (Bull Strong)
🟢 LIGHT GREEN = Weak buy (be careful)
🟠 ORANGE = Weak sell (take profits)
🔴 RED = SELL SIGNAL (Bear Strong)
⚫ GRAY = DON'T TRADE (choppy market)
2. TRIANGLE SIGNALS
These are your entry points:
▲ GREEN TRIANGLE UP = Enter LONG (buy) on next bar
▼ RED TRIANGLE DOWN = Enter SHORT (sell) on next bar
3. TRAILING STOP LINES
🟢 GREEN LINE = Exit your long trades if price hits this
🔴 RED LINE = Exit your short trades if price hits this
🚀 SUPER SIMPLE TRADING METHOD
FOR LONG TRADES (BUYING)
Wait for a green triangle ▲ to appear
Buy on the next candle
Set stop loss below the green line
Take profit when bars turn orange or red
FOR SHORT TRADES (SELLING)
Wait for a red triangle ▼ to appear
Sell on the next candle
Set stop loss above the red line
Take profit when bars turn light green or bright green
WHEN TO STAY OUT
Gray bars = Market is confused, don't trade
No triangles = No clear entry signal
Price far from lines = You missed the move
🚫 COMMON MISTAKES TO AVOID
DON'T Do These Things:
❌ Trade during gray bars (choppy market)
❌ Enter without seeing a triangle signal
❌ Ignore the trailing stop lines
❌ Trade with big position sizes at first
❌ Chase price if you missed the triangle
DO These Instead:
✅ Wait patiently for clear triangle signals
✅ Always use the stop loss lines
✅ Start with tiny position sizes
✅ Take profits when bar colors change
✅ Stay out during gray bar periods
Hawkes Volatility Exit IndicatorOverview
The Hawkes Volatility Exit Indicator is a powerful tool designed to help traders capitalize on volatility breakouts and exit positions when momentum fades. Built on the Hawkes process, it models volatility clustering to identify optimal entry points after quiet periods and exit signals during volatility cooling. Designed to be helpful for swing traders and trend followers across markets like stocks, forex, and crypto.
Key Features Volatility-Based Entries: Detects breakouts when volatility spikes above the 95th percentile (adjustable) after quiet periods (below 5th percentile).
This indicator is probably better on exits than entries.
Smart Exit Signals: Triggers exits when volatility drops below a customizable threshold (default: 30th percentile) after a minimum hold period.
Hawkes Process: Uses a decay-based model (kappa) to capture volatility clustering, making it responsive to market dynamics.
Visual Clarity: Includes a volatility line, exit threshold, percentile bands, and intuitive markers (triangles for entries, X for exits).
Status Table: Displays real-time data on position (LONG/SHORT/FLAT), volatility regime (HIGH/LOW/NORMAL), bars held, and exit readiness.
Customizable Alerts: Set alerts for breakouts and exits to stay on top of trading opportunities.
How It Works Quiet Periods: Identifies low volatility (below 5th percentile) that often precede significant moves.
Breakout Entries: Signals bullish (triangle up) or bearish (triangle down) entries when volatility spikes post-quiet period.
Exit Signals: Suggests exiting when volatility cools below the exit threshold after a minimum hold (default: 3 bars).
Visuals & Table: Tracks volatility, position status, and signals via lines, shaded zones, and a detailed status table.
Settings
Hawkes Kappa (0.1): Adjusts volatility decay (lower = smoother, higher = more sensitive).
Volatility Lookback (168): Sets the period for percentile calculations.
ATR Periods (14): Normalizes volatility using Average True Range.
Breakout Threshold (95%): Volatility percentile for entries.
Exit Threshold (30%): Volatility percentile for exits.
Quiet Threshold (5%): Defines quiet periods.
Minimum Hold Bars (3): Ensures positions are held before exiting.
Alerts: Enable/disable breakout and exit alerts.
How to Use
Entries: Look for triangle markers (up for long, down for short) and confirm with the status table showing "ENTRY" and "LONG"/"SHORT."
Exits: Exit on X cross markers when the status table shows "EXIT" and "Exit Ready: YES."
Monitoring: Use the status table to track position, bars held, and volatility regime (HIGH/LOW/NORMAL).
Combine: Pair with price action, support/resistance, or other indicators for better context.
Tips : Adjust thresholds for your market: lower breakout thresholds for more signals, higher exit thresholds for earlier exits.
Test on your asset to ensure compatibility (best for markets with volatility clustering).
Use alerts to automate signal detection.
Limitations Requires sufficient data (default: 168 bars) for reliable signals. Check "Data Status" in the table.
Focuses on volatility, not price direction—combine with trend tools.
May lag slightly due to the smoothing nature of the Hawkes process.
Why Use It?
The Hawkes Volatility Exit Indicator offers a unique, data-driven approach to timing trades based on volatility dynamics. Its clear visuals, customizable settings, and real-time status table make it a valuable addition to any trader’s toolkit. Try it to catch breakouts and exit with precision!
This indicator is based on neurotrader888's python repo. All credit to him. All mistakes mine.
This conversion published for wider attention to the Hawkes method.
Fibonacci Range Detector ║ BullVision🔬 Overview
The Fibonacci Range Mapper is a dynamic technical tool designed to identify, track, and visualize price ranges using Fibonacci levels. Whether you're trading manually or prefer automated structure recognition, this indicator helps you contextualize market moves and locate key price zones with precision.
⚙️ Core Logic
🔍 Range Detection (Auto & Manual Modes)
In Auto mode, the indicator uses an advanced ZigZag system based on ATR or percentage thresholds to confirm market swings and construct Fibonacci-based ranges.
In Manual mode, traders can define their own swing low and high to generate precise custom ranges.
📐 Fibonacci Mapping
Each detected range is automatically plotted with key Fibonacci retracement levels — 0%, 25%, 50%, 75%, 100% — along with optional extensions (127.2% and 161.8%) to anticipate price continuations or reversals.
📋 Live Data Table
An integrated info panel dynamically displays crucial metrics:
• Range size
• Current price zone (Discount / Mid / Premium)
• Position within range (%)
• Distance to range extremes
• Range status (Pending or Confirmed)
🕰️ Historical Memory
Up to 20 past ranges can be stored and visualized simultaneously, helping traders recognize repeated price behaviors and contextual support/resistance levels.
🎨 Visual Highlights
Zones of interest (0–25% = Discount, 75–100% = Premium) are color-coded with custom transparency, and labels can be toggled for clarity. The current active range updates in real time as structure evolves.
🔧 User Customization
• Detection Method: Choose between ATR or % ZigZag for automated swing identification
• Confirmation Delay: Set how many bars to wait before confirming a new high
• Manual Overrides: Select exact price levels when you want full control
• Extensions & Labels: Toggle additional lines and info to suit your charting style
• Visual Table Position: Customize where the data table appears on screen
• Color Scheme: Define your own zone gradients for better visual interpretation
📈 Use Cases
This indicator is ideal for traders who want to:
• Identify value zones within local or macro price structures
• Plan trades around Fibonacci retracement and extension levels
• Detect shifts in market structure using an adaptive ZigZag logic
• Track recurring price ranges and historical reaction points
• Enhance technical confluence with clean, visual price mapping
⚠️ Important Notes
This tool is not a buy/sell signal generator — it is a visual framework for structure-based analysis.
Use it in conjunction with your existing strategy and risk management process.
Always confirm with broader context and multi-timeframe alignment.
IV PercentileIV Percentile Indicator - Brief Description
What It Does
The IV Percentile Indicator measures where current implied volatility ranks compared to the past year, showing what percentage of time volatility was lower than today's level.
How It Works
Data Collection:
Tracks implied volatility (or historical volatility as proxy) for each trading day
Stores the last 252 days (1 year) of volatility readings
Uses VIX data for SPY/SPX, historical volatility for other stocks
Calculation:
IV Percentile = (Days with IV below current level) ÷ (Total days) × 100
Example: If IV Percentile = 75%, it means current volatility is higher than 75% of the past year's readings.
Visual Output
Main Display:
Blue line showing percentile (0-100%)
Reference lines at key levels (20%, 30%, 50%, 70%, 80%)
Color-coded backgrounds for quick identification
Info table with current readings
Key Levels:
80%+ (Red): Very high IV → Sell premium
70-79% (Orange): High IV → Consider selling
30-20% (Green): Low IV → Consider buying
<20% (Bright Green): Very low IV → Buy premium
Trading Application
When IV Percentile is HIGH (70%+):
Options are expensive relative to recent history
Good time to sell premium (iron condors, credit spreads)
Expect volatility to decrease toward normal levels
When IV Percentile is LOW (30%-):
Options are cheap relative to recent history
Good time to buy premium (straddles, long options)
Expect volatility to increase from compressed levels
Core Logic
The indicator helps answer: "Is this a good time to buy or sell options based on how expensive/cheap they are compared to recent history?" It removes the guesswork from volatility timing by providing historical context for current option prices.
PrismWMA (Rolling)# PrismWMA (Rolling)
Overview
PrismWMA computes rolling VWMA, TWMA and TrueWMA over a fixed lookback window, then plots dynamic volatility bands around each. It’s the rolling-window counterpart to PrismWAP’s anchored spans, giving you per-bar, up-to-date average levels and band excursions.
How It Works
Every bar, PrismWMA:
• Calculates VWMA, TWMA and TrueWMA over the last wmaWindowLen bars.
• Computes your chosen volatility measure (Std Dev, MAD, ATR-scaled) or Percent of WMA over volWindowLen bars.
• Draws upper/lower bands as ±mult × volatility (or ±mult % of the WMA in Percent mode).
Inputs
Settings/Default/Description
WMA Lookback (bars)/50/Number of bars for rolling WMA
Volatility Measure/Std Dev/Band width method: Std Dev, MAD, ATR (scaled), or Percent of WMA
Volatility Lookback (bars)/50/Number of bars used to compute rolling volatility
Band Multiplier (or %)/3.0/Multiplier for band width (or percent of WMA in Percent mode)
Scale MAD to σ/true/When MAD is selected, scale by √(π/2) so it aligns with σ
Display
• Show VWMA true
• Show TWMA true
• Show TrueWMA true
• Show VBands false
• Show TBands false
• Show TrueBands true
References:
1. TrueWMA Description
## 1. TrueWMA: Volatility-Weighted Price Averaging
What Is TrueWMA?
TrueWMA weights each bar’s TrueMid (TrueRange midpoint) by its TrueRange, so high-volatility bars carry more influence. It blends price level and volatility into one moving average
Pseudocode
// TWMA Example for Comparison
window_size = 50
OHLC = (Open + High + Low + Close) / 4
TWMA = MA(OHLC, window_size)
// VWMA Example for Comparison
window_size = 50
HLC3 = (High + Low + Close) / 3
VWMA = Sum(HLC3 * Volume, window_size) / Sum(Volume, window_size)
// TrueWMA (Rolling)
window_size = 50
max_val = Maximum(Close , High)
min_val = Minimum(Close , Low)
true_mid = (max_val + min_val) / 2
TrueWMA = Sum(true_mid * TrueRange, window_size) / Sum(TrueRange, window_size)
Interpretation
For each bar, Rolling TrueWMA:
• Computes a TrueMid (“contextual midpoint”) from the prior close and the current bar’s high/low.
• Weights each TrueMid by that bar’s TrueRange.
• Divides the sum of those weighted midpoints by the total TrueRange over the lookback window.
The result is a single series that dynamically blends price levels with recent volatility.
PrismWAP (Anchored)# PrismWAP (Anchored)
Overview
PrismWAP plots three anchored weighted-average prices (VWAP, TWAP, TrueWAP) with dynamic volatility bands and a resettable anchor line. It helps you see key value levels since your chosen anchor period and gauge price excursions relative to volatility.
How It Works
On each new span (session, week, month, quarter, etc.), the indicator resets a base price from the first bar’s open. It computes anchored VWAP, TWAP, and TrueWAP cumulatively over the span. Volatility bands are drawn as ±multiplier × a span-length-weighted average of your chosen volatility measure (Std Dev, MAD, ATR-scaled, or Percent of WAP).
Inputs
Settings/Default/Description
Anchor Period/Quarter/Span for resetting WAP and anchor line (Week, Month, etc.)
Volatility Measure/Std Dev/Method for band width: SD, MAD, ATR (scaled), Percent of WAP
Volatility Spans/current+2/Number of spans (current + previous spans) used in volatility
Band Multiplier(or %)/3.0/Multiplier for band width (or Percent of WAP in Percent mode)
Scale MAD to σ/true/When MAD selected, scale by √(π/2) so it aligns with σ
Display
• Show Anchor Line true
• Show VWAP true
• Show TWAP true
• Show TrueWAP true
• Show VWAP Bands false
• Show TWAP Bands false
• Show TrueWAP Bands true
Tips & Use Cases
• Use shorter spans (Session, Week) for sub-daily bar intervals.
• Use longer spans (Quarter, Year) for daily bar intervals.
References:
1. TrueWAP Description
2. SD, MAD, ATR (scaled) weighted average volatility
## 1. TrueWAP: Volatility-Weighted Price Averaging
What Is TrueWAP?
TrueWAP plugs actual price fluctuations into your average. Instead of only tracking time (TWAP) or volume (VWAP), it weights each bar’s TrueRange midpoint by its TrueRange—so when the market moves more, that bar counts more.
TrueWAP (Anchored) Overview
• On the first bar, it uses the simple high-low midpoint for price and the bar’s high-low range for weighting.
• From the next bar onward, it computes TrueMid by averaging the TrueRange high (higher of prior close or current high) with the TrueRange low (lower of prior close or current low).
• Each TrueMid is weighted by its TrueRange and cumulatively summed from the anchor point.
Pseudocode
// TWAP Example for Comparison
current_days = BarsSince("start_of_period")
OHLC = (Open + High + Low + Close) / 4
TWAP = MA(OHLC, current_days)
// VWAP Example for Comparison
current_days = BarsSince("start_of_period")
HLC3 = (High + Low + Close) / 3
VWAP = Sum(HLC3 * Volume, current_days) / Sum(Volume, current_days)
// TrueWAP (Anchored)
current_days = BarsSince("start_of_period") // Count of bars since the period began
first_bar = (current_days == 0) // Boolean flag that is true if current bar is the first of period
hilo_mid = (High + Low) / 2 // For the first bar, use its simple high/low avg
max_val = max(Close , High) // For subsequent bars, TrueRange high
min_val = min(Close , Low) // For subsequent bars, TrueRange low
true_mid = (max_val + min_val) / 2 // True Range midpoint for subsequent bars
// Use hilo_mid and (High - Low) for the first bar; otherwise, use true_mid and True Range
mid_val = IF(first_bar, hilo_mid, true_mid)
range_val = IF(first_bar, (High - Low), TrueRange)
TrueWAP = Sum(mid_val * range_val, current_days) / Sum(range_val, current_days)
Recap: Interpretation
• The first bar uses the simple high-low midpoint and range.
• Subsequent bars use TrueMid and TrueRange based on prior close.
• This ensures the average reflects only the observed volatility and price since the anchor.
A Note on True Range
TrueRange captures the full extent of bar-to-bar volatility as the maximum of:
• High – Low
• |High – Previous Close|
• |Low – Previous Close|
## 2. Segmented Weighted-Average Volatility: A Fixed-Point Multi-Period Approach
### Introduction
Conventional standard deviation calculations aggregate data over an expanding window and rely on a single mean, producing one summary statistic. This can obscure segmented, sequential datasets—such as MTD, QTD, and YTD—where additional granularity and time-sensitive insights matter.
This methodology isolates standard deviation within defined time frames and then proportionally allocates them based on custom lookback criteria. The result is a dynamic, multi-period normalization benchmark that captures both emerging volatility and historical stability.
Note: While this example uses SD, the same fixed-point approach applies to MAD and ATR (scaled).
### 2.1 Standard Deviation (Rolling Window)
pseudocode
// -- STANDARD DEVIATION (ROLLING) Calculation --
window_size = 20
rolling_SD = STDDEV(Close, window_size)
• Ideal for immediate trading insights.
• Reflects pure, short-term price dynamics.
• Captures volatility using the most recent 20 trading days.
### 2.2 Blended SD: Current + 3 Past Periods
This method fuses current month data with the last three complete months.
pseudocode
// -- MULTI-PERIOD STANDARD DEVIATION (PROXY) with Three Past Periods --
current_days = BarsSince("start_of_month")
current_SD = STDDEV(Close, current_days)
prev1_days = TradingDaysLastMonth
prev1_SD = STDDEV_LastMonth(Close)
prev2_days = TradingDaysTwoMonthsAgo
prev2_SD = STDDEV_TwoMonthsAgo(Close)
prev3_days = TradingDaysThreeMonthsAgo
prev3_SD = STDDEV_ThreeMonthsAgo(Close)
// Blending with Proportional Weights
Weighted_SD = (current_SD * current_days +
prev1_SD * prev1_days +
prev2_SD * prev2_days +
prev3_SD * prev3_days) /
(current_days + prev1_days + prev2_days + prev3_days)
• Merges evolving volatility with the stability of three prior months.
• Weights each period by its trading days.
• Yields a robust normalization benchmark.
### 2.3 Blended SD: Current + 1 Past Period
This variant tempers emerging volatility by blending the current month with last month only.
pseudocode
// -- MULTI-PERIOD STANDARD DEVIATION (PROXY) with One Past Period --
current_days = BarsSince("start_of_month")
current_SD = STDDEV(Close, current_days)
prev1_days = TradingDaysLastMonth
prev1_SD = STDDEV_LastMonth(Close)
// Proportional Blend
Weighted_SD = (current_SD * current_days +
prev1_SD * prev1_days) /
(current_days + prev1_days)
• Anchors current volatility to last month’s baseline.
• Softens spikes by blending with historical data.
Conclusion
Segmented weighted-average volatility transforms global benchmarking by integrating immediate market dynamics with enduring historical context. This fixed-point approach—applicable to SD, MAD (scaled), and ATR (scaled)—delivers time-sensitive analysis.
RSI+BOLLINGER (LONG & SHORT)This indicator combines two of the most popular tools in technical analysis, the Relative Strength Index (RSI) and Bollinger Bands (BB), to generate both long (BUY) and short (SELL) trading signals.
Strategy:
Entries (Buy/Short): Entry signals are based on the RSI.
A BUY is suggested when the RSI crosses above an oversold level (default: 29), indicating a possible upward reversal.
A SHORT is suggested when the RSI crosses below an overbought level (default: 71), indicating a possible downward reversal.
Exits (Position Closure): Exit signals are based on Bollinger Bands.
A long position is closed when the price crosses below the upper Bollinger Band.
A short position is closed when the price crosses above the lower Bollinger Band.
Key Features:
Cascade Filter: Includes a smart filter that prevents opening new consecutive trades if the price hasn't moved significantly in favor of a new entry, optimizing signal quality.
Automation Alerts: Generates detailed alerts in JSON format for each event (buy, sell, close), designed for easy integration with trading bots and automated systems via webhooks.
Fully Configurable: All parameters of the RSI, Bollinger Bands, and strategy filters can be adjusted from the indicator’s settings menu.
