🐬RSI_CandleRSI_Candle
Calculates the RSI based on the open, high, low, and close prices, and displays it in the form of candles.
The overbought and oversold zones are highlighted with background colors, which become darker as the RSI value approaches 100 or 0.
-----
RSI_Candle
RSI를 시가, 고가, 저가, 종가로 계산하여 캔들로 보여줍니다.
과매수/과매도 구간에서 배경색으로 보여주며, 100/0에 가까울수록 배경색이 짙어집니다.
-----
Indicadores e estratégias
🐬Stochastic_RSIStochastic RSI
The indicator highlights the chart background for two specific signals:
- A bearish deadcross occurring above the upper band.
- A bullish goldencross occurring below the lower band.
-----
스토캐스틱 RSI
두가지 신호를 배경색으로 나타냅니다.
- 어퍼 밴드 위에서의 데드크로스
- 로우어 밴드 아래에서의 골든크로스
-----
Session-Conditioned Regime ATRWhy this exists
Classic ATR is great—until the open. The first few bars often inherit overnight gaps and 24-hour noise that have nothing to do with the intraday regime you actually trade. That inflates early ATR, scrambles thresholds, and invites hyper-recency bias (“today is crazy!”) when it’s just the open being the open.
This tool was built to:
Separate session reality from 24h noise. Measure volatility only inside your defined session (e.g., NYSE 09:30–16:00 ET).
Judge candles against the current regime, not the last 2–3 bars. A rolling statistic from the last N completed sessions defines what “typical” means right now.
Label “large” and “small” objectively. Bars are colored only when True Range meaningfully departs from the session regime—no gut feel, no open-bar distortion (gap inclusion optional).
Overview
Purpose: objectively identify unusually big or small candles within the active trading session, compared to the recent session regime.
Use cases: volatility filters, entry/exit confirmation, session bias detection, adaptive sizing.
This indicator replaces generic ATR with a session-conditioned, regime-aware measure. It colors candles only when their True Range (TR) is abnormally large/small versus the last N completed sessions of the same session window.
How it works
Session gating: Only bars inside the selected session are evaluated (presets for NYSE, CME RTH, FX NY; custom supported).
Per-bar TR: TR = max(high, prevRef) − min(low, prevRef).
prevRef is the prior close for in-session bars.
First bar of the session can include the overnight gap (optional; default off).
Regime statistic: For any bar in session k, aggregate all in-session TRs from the previous N completed sessions (k−N … k−1), then compute Median (default) or Mean.
Today’s anchor: Running statistic from today’s session start → current bar (for context and the on-chart ratio).
Color logic:
Big if TR ≥ bigMult × RegimeStat
Small if TR ≤ smallMult × RegimeStat
Colored states: big bull, big bear, small bull, small bear.
Non-triggering bars retain the chart’s native colors.
Panel (top-right by default)
Regime ATR (Nd): session-conditioned statistic over the past N completed sessions.
Today ATR (anchored): running statistic for the current session.
Ratio (Today/Regime): intraday volatility vs regime.
Sample size n: number of bars used in the regime calculation.
Inputs
Session Preset: NYSE (09:30–16:00 ET), CME RTH (08:30–15:00 CT), FX NY (08:00–17:00 ET), Custom (session + IANA timezone).
Regime Window: number of completed sessions (default 5).
Statistic: Median (robust) or Mean.
Include Open Gap: include overnight gap in the first in-session bar’s TR (default off).
Big/Small thresholds: multipliers relative to RegimeStat (defaults: Big=1.5×, Small=0.67×).
Colors: four independent colors for big/small × bull/bear.
Panel position & text size.
Hidden outputs: expose RegimeStat, TodayStat, Ratio, and Z-score to other scripts.
Alerts
RegimeATR: BIG bar — triggers when a bar meets the “Big” condition.
RegimeATR: SMALL bar — triggers when a bar meets the “Small” condition.
Hidden outputs (for strategies/screeners)
RegimeATR_stat, TodayATR_stat, Today_vs_Regime_Ratio, BarTR_Zscore.
Notes & limitations
No look-ahead: calculations only use information available up to that bar. Historical colors reflect what would have been known then.
Warm-up: colors begin once there are at least N completed sessions; before that, regime is undefined by design.
Changing inputs (session window, multipliers, median/mean, gap toggle) recomputes the full series using the same rolling regime logic per bar.
Designed for standard candles. Styling respects existing chart colors when no condition triggers.
Practical tips
For a broader or tighter notion of “unusual,” adjust Big/Small multipliers.
Prefer Median in markets prone to outliers; use Mean if you want Z-score alignment with the panel’s regime mean/std.
Use the Ratio readout to spot compression/expansion days quickly (e.g., <0.7× = compressed session, >1.3× = expanded).
Roadmap
More session presets:
24h continuous (crypto, index CFDs).
23h/Globex futures (CME ETH with a 60-minute maintenance break).
Regional equities (LSE, Xetra, TSE), Asia/Europe/NY overlaps for FX.
Half-day/holiday templates and dynamic calendars.
Multi-regime comparison: track multiple overlapping regimes (e.g., RTH vs ETH for futures) and show separate stats/ratios.
Robust stats options: trimmed mean, MAD/Huber alternatives; optional percentile thresholds instead of fixed multipliers.
Subpanel visuals: rolling TodayATR and Ratio plots; optional Z-score ribbon.
Screener/strategy hooks: export boolean series for BIG/SMALL, plus a lightweight strategy template for backtesting entries/exits conditioned on regime volatility.
Performance/QOL: per-symbol presets, smarter warm-up, and finer control over sample caps for ultra-low TF charts.
Changelog
v0.9b (Beta)
Session presets (NYSE/CME RTH/FX NY/Custom) with timezone handling.
Panel enhancements: ratio + sample size n.
Four-state bar coloring (big/small × bull/bear).
Alerts for BIG/SMALL bars.
Hidden Z-score stream for downstream use.
Gap-in-TR toggle for the first in-session bar.
Disclaimer
For educational purposes only. Not investment advice. Validate thresholds and session settings across symbols/timeframes before live use.
Kalman Filter [DCAUT]█ Kalman Filter
📊 ORIGINALITY & INNOVATION
The Kalman Filter represents an important adaptation of aerospace signal processing technology to financial market analysis. Originally developed by Rudolf E. Kalman in 1960 for navigation and guidance systems, this implementation brings the algorithm's noise reduction capabilities to price trend analysis.
This implementation addresses a common challenge in technical analysis: the trade-off between smoothness and responsiveness. Traditional moving averages must choose between being smooth (with increased lag) or responsive (with increased noise). The Kalman Filter improves upon this limitation through its recursive estimation approach, which continuously balances historical trend information with current price data based on configurable noise parameters.
The key advancement lies in the algorithm's adaptive weighting mechanism. Rather than applying fixed weights to historical data like conventional moving averages, the Kalman Filter dynamically adjusts its trust between the predicted trend and observed prices. This allows it to provide smoother signals during stable periods while maintaining responsiveness during genuine trend changes, helping to reduce whipsaws in ranging markets while not missing significant price movements.
📐 MATHEMATICAL FOUNDATION
The Kalman Filter operates through a two-phase recursive process:
Prediction Phase:
The algorithm first predicts the next state based on the previous estimate:
State Prediction: Estimates the next value based on current trend
Error Covariance Prediction: Calculates uncertainty in the prediction
Update Phase:
Then updates the prediction based on new price observations:
Kalman Gain Calculation: Determines the weight given to new measurements
State Update: Combines prediction with observation based on calculated gain
Error Covariance Update: Adjusts uncertainty estimate for next iteration
Core Parameters:
Process Noise (Q): Represents uncertainty in the trend model itself. Higher values indicate the trend can change more rapidly, making the filter more responsive to price changes.
Measurement Noise (R): Represents uncertainty in price observations. Higher values indicate less trust in individual price points, resulting in smoother output.
Kalman Gain Formula:
The Kalman Gain determines how much weight to give new observations versus predictions:
K = P(k|k-1) / (P(k|k-1) + R)
Where:
K is the Kalman Gain (0 to 1)
P(k|k-1) is the predicted error covariance
R is the measurement noise parameter
When K approaches 1, the filter trusts new measurements more (responsive).
When K approaches 0, the filter trusts its prediction more (smooth).
This dynamic adjustment mechanism allows the filter to adapt to changing market conditions automatically, providing an advantage over fixed-weight moving averages.
📊 COMPREHENSIVE SIGNAL ANALYSIS
Visual Trend Indication:
The Kalman Filter line provides color-coded trend information:
Green Line: Indicates the filter value is rising, suggesting upward price momentum
Red Line: Indicates the filter value is falling, suggesting downward price momentum
Gray Line: Indicates sideways movement with no clear directional bias
Crossover Signals:
Price-filter crossovers generate trading signals:
Golden Cross: Price crosses above the Kalman Filter line, suggests potential bullish momentum development, may indicate a favorable environment for long positions, filter will naturally turn green as it adapts to price moving higher
Death Cross: Price crosses below the Kalman Filter line, suggests potential bearish momentum development, may indicate consideration for position reduction or shorts, filter will naturally turn red as it adapts to price moving lower
Trend Confirmation:
The filter serves as a dynamic trend baseline:
Price Consistently Above Filter: Confirms established uptrend
Price Consistently Below Filter: Confirms established downtrend
Frequent Crossovers: Suggests ranging or choppy market conditions
Signal Reliability Factors:
Signal quality varies based on market conditions:
Higher reliability in trending markets with sustained directional moves
Lower reliability in choppy, range-bound conditions with frequent reversals
Parameter adjustment can help adapt to different market volatility levels
🎯 STRATEGIC APPLICATIONS
Trend Following Strategy:
Use the Kalman Filter as a dynamic trend baseline:
Enter long positions when price crosses above the filter
Enter short positions when price crosses below the filter
Exit when price crosses back through the filter in the opposite direction
Monitor filter slope (color) for trend strength confirmation
Dynamic Support/Resistance:
The filter can act as a moving support or resistance level:
In uptrends: Filter often provides dynamic support for pullbacks
In downtrends: Filter often provides dynamic resistance for bounces
Price rejections from the filter can offer entry opportunities in trend direction
Filter breaches may signal potential trend reversals
Multi-Timeframe Analysis:
Combine Kalman Filters across different timeframes:
Higher timeframe filter identifies primary trend direction
Lower timeframe filter provides precise entry and exit timing
Trade only in direction of higher timeframe trend for better probability
Use lower timeframe crossovers for position entry/exit within major trend
Volatility-Adjusted Configuration:
Adapt parameters to match market conditions:
Low Volatility Markets (Forex majors, stable stocks): Use lower process noise for stability, use lower measurement noise for sensitivity
Medium Volatility Markets (Most equities): Process noise default (0.05) provides balanced performance, measurement noise default (1.0) for general-purpose filtering
High Volatility Markets (Cryptocurrencies, volatile stocks): Use higher process noise for responsiveness, use higher measurement noise for noise reduction
Risk Management Integration:
Use filter as a trailing stop-loss level in trending markets
Tighten stops when price moves significantly away from filter (overextension)
Wider stops in early trend formation when filter is just establishing direction
Consider position sizing based on distance between price and filter
📋 DETAILED PARAMETER CONFIGURATION
Source Selection:
Determines which price data feeds the algorithm:
OHLC4 (default): Uses average of open, high, low, close for balanced representation
Close: Focuses purely on closing prices for end-of-period analysis
HL2: Uses midpoint of high and low for range-based analysis
HLC3: Typical price, gives more weight to closing price
HLCC4: Weighted close price, emphasizes closing values
Process Noise (Q) - Adaptation Speed Control:
This parameter controls how quickly the filter adapts to changes:
Technical Meaning:
Represents uncertainty in the underlying trend model
Higher values allow the estimated trend to change more rapidly
Lower values assume the trend is more stable and slow-changing
Practical Impact:
Lower Values: Produces very smooth output with minimal noise, slower to respond to genuine trend changes, best for long-term trend identification, reduces false signals in choppy markets
Medium Values: Balanced responsiveness and smoothness, suitable for swing trading applications, default (0.05) works well for most markets
Higher Values: More responsive to price changes, may produce more false signals in ranging markets, better for short-term trading and day trading, captures trend changes earlier, adjust freely based on market characteristics
Measurement Noise (R) - Smoothing Control:
This parameter controls how much the filter trusts individual price observations:
Technical Meaning:
Represents uncertainty in price measurements
Higher values indicate less trust in individual price points
Lower values make each price observation more influential
Practical Impact:
Lower Values: More reactive to each price change, less smoothing with more noise in output, may produce choppy signals
Medium Values: Balanced smoothing and responsiveness, default (1.0) provides general-purpose filtering
Higher Values: Heavy smoothing for very noisy markets, reduces whipsaws significantly but increases lag in trend change detection, best for cryptocurrency and highly volatile assets, can use larger values for extreme smoothing
Parameter Interaction:
The ratio between Process Noise and Measurement Noise determines overall behavior:
High Q / Low R: Very responsive, minimal smoothing
Low Q / High R: Very smooth, maximum lag reduction
Balanced Q and R: Middle ground for most applications
Optimization Guidelines:
Start with default values (Q=0.05, R=1.0)
If too many false signals: Increase R or decrease Q
If missing trend changes: Decrease R or increase Q
Test across different market conditions before live use
Consider different settings for different timeframes
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Comparison with Traditional Moving Averages:
Versus Simple Moving Average (SMA):
The Kalman Filter typically responds faster to genuine trend changes
Produces smoother output than SMA of comparable length
Better noise reduction in ranging markets
More configurable for different market conditions
Versus Exponential Moving Average (EMA):
Similar responsiveness but with better noise filtering
Less prone to whipsaws in choppy conditions
More adaptable through dual parameter control (Q and R)
Can be tuned to match or exceed EMA responsiveness while maintaining smoothness
Versus Hull Moving Average (HMA):
Different noise reduction approach (recursive estimation vs. weighted calculation)
Kalman Filter offers more intuitive parameter adjustment
Both reduce lag effectively, but through different mechanisms
Kalman Filter may handle sudden volatility changes more gracefully
Response Characteristics:
Lag Time: Moderate and configurable through parameter adjustment
Noise Reduction: Good to excellent, particularly in volatile conditions
Trend Detection: Effective across multiple timeframes
False Signal Rate: Typically lower than simple moving averages in ranging markets
Computational Efficiency: Efficient recursive calculation suitable for real-time use
Optimal Use Cases:
Markets with mixed trending and ranging periods
Assets with moderate to high volatility requiring noise filtering
Multi-timeframe analysis requiring consistent methodology
Systematic trading strategies needing reliable trend identification
Situations requiring balance between responsiveness and smoothness
Known Limitations:
Parameters require adjustment for different market volatility levels
May still produce false signals during extreme choppy conditions
No single parameter set works optimally for all market conditions
Requires complementary indicators for comprehensive analysis
Historical performance characteristics may not persist in changing market conditions
USAGE NOTES
This indicator is designed for technical analysis and educational purposes. The Kalman Filter's effectiveness varies with market conditions, tending to perform better in markets with clear trending phases interrupted by consolidation. Like all technical indicators, it has limitations and should not be used as the sole basis for trading decisions, but rather as part of a comprehensive trading approach.
Algorithm performance varies with market conditions, and past characteristics do not guarantee future results. Always test thoroughly with different parameter settings across various market conditions before using in live trading. No technical indicator can predict future price movements with certainty, and all trading involves risk of loss.
MACD (Buy & Sell signals)This file uses the original code of the MACD and adds a Buy Sell signal when the MACD cuts the signal
Reversal Probability Meter PRO [optimized for Xau/Usd m5]🎯 Reversal Probability Meter PRO
A powerful multi-factor reversal probability detector that calculates the likelihood of bullish or bearish reversals using RSI, EMA bias, ATR spikes, candle patterns, volume spikes, and higher timeframe (HTF) trend alignment.
🧩 MAIN FEATURES
1. Reversal Probability (Bullish & Bearish)
Displays two key metrics:
Bull % — probability of bullish reversal
Bear % — probability of bearish reversal
These are computed using RSI, EMAs, ATR, demand/supply zones, candle confirmations, and volume spikes.
📊 Interpretation:
Bull % > 70% → Buying pressure building up
Bull % > 85% → Strong bullish reversal confirmed
Bear % > 70% → Selling pressure building up
Bear % > 85% → Strong bearish reversal confirmed
2. Alert Probability Threshold
Adjustable via alertThreshold (default = 85%).
Alerts trigger only when probability ≥ threshold, and confirmed by zone + volume spike + candle pattern.
🔔 Alerts Available:
✅ Bullish Smart Reversal
🔻 Bearish Smart Reversal
To activate: Right-click chart → “Add alert” → choose the alert condition from the indicator.
3. Demand / Supply Zone Detection
The script determines the price position within the last zoneLook (default 30) bars:
🟢 DEMAND → Lower 35% of range (potential bounce zone)
🔴 SUPPLY → Upper 35% of range (potential rejection zone)
⚪ MID → Neutral area
📘 Purpose: Validates reversals based on context:
Bullish only valid in Demand zones
Bearish only valid in Supply zones
4. Higher Timeframe (HTF) Trend Alignment
Reads EMA bias from a higher timeframe (default = 15m) for trend confirmation.
Reversals against HTF trend are automatically weighted down prevents false countertrend signals.
📈 Example:
M5 chart under M15 downtrend → Bullish probability is reduced.
5. Candle Confirmation Patterns
Two key price action confirmations:
Bullish: Engulfing or Pin Bar
Bearish: Engulfing or Pin Bar
A valid reversal requires both a candle confirmation and a volume spike.
6. Volume & ATR Spike Filters
Volume Spike: volume > SMA(20) × 1.3
ATR Spike: ATR > SMA(ATR, 50) × volMult
🎯 Ensures that only strong market moves with real energy are considered valid reversals.
7. Reversal Momentum Histogram
A color-gradient oscillator showing the momentum difference:
Green = bullish dominance
Red = bearish dominance
Flat near 0 = neutral
Controlled by showOscillator toggle.
8. Smart Info Panel
A compact dashboard displayed on the top-right with 4 rows:
Row Info Description
1 Bull % Bullish reversal probability
2 Bear % Bearish reversal probability
3 Zone Market context (DEMAND / SUPPLY / MID)
4 Signal Strength Current signal intensity (probability %)
Dynamic Colors:
90% → Bright (strong signal)
75–90% → Yellow/Orange (medium)
<75% → Gray (weak)
9. Sensitivity Mode
Fine-tunes indicator reactivity:
🟥 Aggressive: Detects reversals early (more signals, less accurate)
🟨 Normal: Balanced, default mode
🟩 Conservative: Filters only strongest reversals (fewer but more reliable)
10. Custom Color Options
Customize bullish and bearish colors via bullBaseColor and bearBaseColor inputs for your preferred chart theme.
⚙️ HOW TO USE
Add to Chart
→ Paste the script into Pine Editor → “Add to chart”.
Select Timeframe
→ Best for M5–M30 (scalping/intraday).
→ H1–H4 for swing trading.
Monitor the Info Panel:
Bull % ≥ 85% + Zone = Demand → Strong bullish reversal signal
Bear % ≥ 85% + Zone = Supply → Strong bearish reversal signal
Watch the Histogram:
Rising green bars = bullish momentum gaining
Deep red bars = bearish momentum gaining
Enable Alerts:
Right-click chart → “Add alert”
Choose Bullish Smart Reversal or Bearish Smart Reversal
🧠 TRADING TIPS
Use Conservative mode for noisy lower timeframes (M5–M15).
Use Aggressive mode for higher timeframes (H1–H4).
Combine with manual support/resistance or zone boxes for precision entries. Personally i use Order Block.
Best reversal setups occur when all align:
Bull % > 85%
Zone = DEMAND
Volume spike present
Candle = Bullish engulfing
HTF trend supportive
MACD Cross Above Zero Alert (Any Timeframe)For use on a large list to spot MACD cross overs in a bullish phase or bearish phase
High Volume & Near All-Time HighThe **High Volume & Near All-Time High Screener** is a simple yet powerful Pine Script tool designed to help traders identify stocks showing strong price momentum and trading activity. This screener automatically scans multiple tickers that you define in the settings and highlights those meeting two key conditions — daily trading volume greater than **500,000 shares** and the closing price being **within a set percentage (default 2%) of its all-time high**. The results are displayed in an easy-to-read table directly on your chart, making it ideal for traders who want to quickly spot potential breakout stocks without switching between multiple charts.
**How to Use:**
To use this script, open your **TradingView Pine Editor**, paste the code, and click **“Add to Chart.”** Make sure your chart is set to the **Daily timeframe (1D)**, as the script pulls daily data automatically. You can customize the list of symbols, the minimum volume threshold, and the proximity percentage in the settings panel to match your trading style. Once added, the screener will display a table on the right side of your chart showing each symbol, its latest closing price, and whether it currently meets the breakout conditions. A ✅ mark indicates that the stock meets both criteria. This tool works best for swing traders and momentum investors who want to focus on high-volume stocks nearing new highs for potential entries.
MACD 4H Cross Above Zero AlertMACD 4H Cross the signal line to screen for stocks across a wide demo list
Engulfing Bars - StrictIdentifies strict definition engulfing bars with a close in the leading 20% of the range.
ADAM Projection - Efficiency Ratio Adaptive)Overview
The ADAM Projection is a visualization of how a price path might extend from its recent motion, expressed as a continuation (trend reflection) or anti-trend (mean reversion) pattern. This indicator expands upon Jim Sloman’s original ADAM projection—introduced in “The Adam Theory of Markets or What Matters Is Profit” (1983)—by adding a modern quantitative framework for Efficiency Ratio (ER) weighting, time-scaled path normalization, and smooth blending between continuation and anti-trend projections.
What Is the ADAM Theory?
Jim Sloman’s original ADAM projection was designed to model pure trend continuation. He proposed that every market motion could be mirrored around a central anchor price (the “Adam line”), effectively reflecting past price movements forward in time to visualize what a continuation of the same geometric path would look like. This reflection concept captured the idea that market structure exhibits self-similarity and that price trends often extend symmetrically beyond recent pivots.
How This Script Extends It
This version generalizes Sloman’s concept by introducing an adjustable blend between continuation (reflection) and anti-trend (forward paste) behavior, weighted by an adaptive ER domain.
Anchor Axis
The reflection axis (anchorPrice) can be Close, HL2, HLC3, or OHLC4.
The projection is drawn forward from this anchor for a user-defined horizon (len bars).
Dual Paths
Continuation (Reflection): Mirrors historical closes across the anchor.
Anti-trend (Forward Paste): Extends historical closes directly forward without inversion.
Efficiency Ratio (ER)
The Efficiency Ratio measures how directional recent price movement has been: ER = |Net Change| / Σ|Δi|
Values near +1 indicate strong directionality (favoring continuation); values near 0 indicate noise or consolidation (favoring anti-trend behavior).
Signed ER Normalization
ER values are mapped into a user-defined domain between erMin and erMax, with:
erSharp (γ) controlling the steepness of the blend curve
erFloor providing stability when ER ≈ 0
beta (β) weighting volatility across time (β = 0.5 approximates √time scaling)
Blended Projection
Each projected point is a weighted combination of the two paths: y_proj = (1 − w) * y_fade + w * y_cont
The blend factor w is derived from the normalized ER domain and gamma shaping, producing a smooth morph between the anti-trend and continuation geometries.
Visualization
The teal projection line shows the dynamically blended continuation/anti-trend forecast for the next len bars.
The gray anchor line marks the reflection axis.
Each segment adapts in real time based on ER magnitude and recent path structure.
Key Parameters
Core: len, anchorPrice, lineThin — projection horizon and appearance
Lines: showProj, colProj — show or recolor projection
ER Domain: erMin, erMax, erSharp, erFloor, beta — control domain scaling, shaping, and time weighting
Practical Use
High ER values emphasize continuation (trend-following behavior).
Low or negative ER values emphasize fading or mean reversion.
The projection helps visualize whether recent structure supports trend persistence or weakening.
Interpretation
The ADAM Projection is not a predictive indicator but a geometric tool for studying market symmetry and efficiency. It provides a structured way to visualize how recent movements would look if extended forward under both continuation and anti-trend assumptions. This blends Sloman’s original reflection concept with modern ER-based adaptivity.
Summary
Origin: Jim Sloman (1983) — trend continuation via reflection symmetry.
Extension: Adds ER-driven blending to model both continuation and anti-trend regimes.
Concept: Price reflection vs. direct forward extension.
Purpose: Study of geometric price symmetry and efficiency, not a trade signal.
Options Momentum SignalCustomizable Intraday Options Scalping Alert.
Several important, complementary indicators combined into one simple signal that pops up under a bar to indicate sustained momentum on a trend. It uses a combination of calculations based on the 1m VWAP, price increase in contrast to previous day's close, and customizable Volatility and Volume Data.
It has adjustable values for the % increase from last close (labeled as Pre-Mkt % Threshold), minimal candle body % to filter out weaker signals, RVOL threshold, minimum CVD (it's rolling, so functions in tandem with the CVD lookback value for the number of bars.)
It offers individual boxes that can be checked on or off to help filter out noise. Boxes are: Use 1m VWAP, Use CVD, 3-bar cooldown (reduces back-to-back signals, especially on shorter (1m, 2m, and 5m) charts), VWAP bounce option to catch bounces happening in real time before the candle closes, Use RVOL, and Use Rolling CVD. These can all be checked on or off and will create vastly different signals depending on what you are filtering for.
These indicators were chosen specifically as I feel they help most with option scalping and is intended to be used alongside a few other indicators for confirmation. Personally, I use a couple anchored VWAPs (highest high, session) as well as a FRAMA channel for confirmation. I also use the following to further confirm trends: TradingView’s RVOL, CVD, and Price Pattern Oscillators, in addition to Beardy Fred's TTM Squeeze Pro.
Hope this helps some people!
Rolling Midpoint of Price & VWAP with ATR BandsThe Rolling Midpoint of Price & VWAP with ATR Bands indicator is a dual-equilibrium concept that fuses price-range structure and traded-volume flow into one continuously updating hybrid model. Traditional VWAPs reset each session and reflect where trading occurred by volume, while midpoints used here reveal where price has structurally balanced between extremes. This script merges both ideas into a cohesive, dynamic system. The Rolling Price Midpoint (50 % of range) represents the structural fair-value line, calculated as the average of the highest high and lowest low over a selected window. The Rolling VWAP (Volume-Weighted Window) tracks the flow-based fair-value line by weighting each bar’s typical price by its volume. Together, these components form the Hybrid Equilibrium — the adaptive center of gravity that shifts as price and volume evolve. Surrounding this equilibrium, ATR Bands at ± 2.226 ATR and ± 5.382 ATR define volatility envelopes that expand and contract with market energy. The result is a living cloud that breathes with the market: compressing during phases of balance and widening during impulsive movements, offering traders a clear visual framework for understanding equilibrium, volatility, and directional bias in real time.
➖
⚙️ Auto-Preset System
The Auto-Preset System intelligently adjusts lookback windows for both the Price Midpoint and VWAP calculations according to the active chart timeframe.
This ensures that the indicator automatically adapts to any trading style — from scalping on 1-minute charts to swing trading on daily or weekly charts — without manual tuning.
🔹 How It Works
When Auto-Preset mode is enabled, the script dynamically selects the most effective lookback lengths for each timeframe.
These presets are optimized to balance responsiveness and stability, maintaining consistent real-world coverage (e.g., the same approximate duration of price data) across all intervals.
📊 Preset Mapping Table
| Chart Timeframe | Price Midpoint Lookback | VWAP Lookback |
|:----------------:|:-----------------------:|:--------------:|
| 1–3m | 13 bars | 21 bars
| 5–10m | 21 bars | 34 bars
| 15–30m | 34 bars | 55 bars
| 1–2 hr | 55 bars | 89 bars
| 4 hr-1D | 89 bars | 144 bars
| 1W | 144 bars | 233 bars
| 1M | 233 bars | 377 bars
⚡ Notes & Customization
- Manual Override: Turn off Auto-Preset Mode to specify your own custom lookback lengths.
- Consistency Across Scales: These adaptive values keep the indicator visually coherent when switching between timeframes — avoiding distortions that can occur with static lengths.
- Practical Benefit: Traders can maintain a single chart layout that self-tunes seamlessly, removing the need to manually recalibrate settings when shifting from short-term to long-term analysis.
In short, the Auto-Preset System is designed to make this hybrid equilibrium tool timeframe-aware — automatically scaling its logic so that the cloud behaves consistently, regardless of chart resolution.
➖
🌐 Hybrid Equilibrium Envelope
The core hybrid midpoint acts as the mean of structural (price) and volumetric (VWAP) balance.
ATR-based bands project natural expansion zones:
🔸+2.226 / –2.226 ATR → inner equilibrium (controlled trend)
*🔸+5.382 / –5.382 ATR → outer volatility extension (over-stretch / reversion zones)
Color-coded fills show regime strength:
* 🟧 Upper Outer (+5.382) – strong bullish expansion
* 🟩 Upper Inner (+2.226) – trending equilibrium
* 🔴 Lower Inner (–2.226) – mild bearish control
* 🟣 Lower Outer (–5.382) – volatility exhaustion
➖
🧭 Higher-Timeframe Framework
Two macro anchors — Price length of 144 and VWAP length of 233 — outline higher-timeframe bias zones. These help confirm when local momentum aligns with (or fades against) long-term structure.
Labels on the right show active lookback values for quick readout:
`$(13) V(21)` → current rolling pair
`$144 / V233` → macro anchors
➖
🧩 Chart Examples
**AMD 15m (Equilibrium Expansion)**
Price steadily rides above the hybrid midpoint as teal and orange (bullish) ATR zones widen, confirming a phase of controlled bullish volatility and healthy trend expansion.
BTCUSD 1m (Volatility Compression)
Bitcoin coils tightly inside the teal-to-maroon equilibrium bands before breaking out.
The hybrid midpoint flattens and ATR envelopes contract, signaling a state of balance before volatility expansion.
ETHUSD 15m (Transition from Compression → Impulse)
Ethereum transitions from purple-zone compression into a clear upper-band expansion.
The hybrid midpoint breaks above the macro VWAP 233, confirming the shift from equilibrium to directional momentum.
SOFI 1m (Micro Bias Reversal)
SOFI’s intraday structure flips as price reclaims the hybrid midpoint.
The macro VWAP 233 flattens, signaling a transition from oversold lower bands back toward equilibrium and early trend recovery.
➖
🎯 How to Use
1. Bias Detection – Price > Hybrid Midpoint → bullish; < → bearish.
2. Volatility Gauge – Watch band spacing for compression / expansion cycles.
3. Confluence Checks – Align Hybrid Midpoint with HTF 233 VWAP for strong continuation signals.
4. Mean Reversion Zones – Outer bands highlight areas where probability of snap-back increases.
➖
🔧 Inputs & Customization
Auto Presets toggle
🔸Manual Lookback Overrides** for fine-tuning
🔸Plot Window Length** (show recent vs full history)
🔸ATR Sensitivity & Fill Opacity** controls
🔸Label Padding / Font Size** for cleaner overlay visuals
➖
🧮 Formula Highlights
➖Rolling Midpoint = (highest(high,N) + lowest(low,N)) / 2
➖Rolling VWAP = Σ(Typical Price×Vol) / Σ(Vol)
➖Hybrid = (PriceMid + VWAP) / 2
➖Upper₂ = Hybrid + ATR×2.226
➖Lower₂ = Hybrid − ATR×2.226
➖Upper₅ = Hybrid + ATR×5.382
➖Lower₅ = Hybrid − ATR×5.382
➖
🎯 Ideal For
➡️ Traders who want adaptive fair-value zones that evolve with both price and volume.
➡️ Analysts who shift between scalping, swing, and position timeframes, and need a tool that self-adjusts.
➡️ Those who rely on visual structure clarity to confirm setups across changing volatility conditions.
➡️ Anyone seeking a hybrid model that unites structural range logic (midpoint) and flow-based balance (VWAP).
➖
🏁 Final Word
This script is more than a visual overlay — it’s a complete trend and structure framework built to adapt with market rhythm. It helps traders visualize equilibrium, momentum, and volatility as one cohesive system. Whether you’re seeking clean trend alignment, dynamic support/resistance, or early warning signs of reversals, this indicator is tuned to help you react with confidence — not hindsight.
➖
Remember — no single indicator should ever stand alone. For best results, pair it with price action context, higher-timeframe structure, and complementary tools such as moving averages or trendlines. Use it to confirm setups, not define them in isolation.
💡 Turn logic into clarity, structure into trades, and uncertainty into confidence.
ICT Essentials [LDT]ICT Essentials
Overview
ICT Essentials is an all-in-one trading utility built to create a natural and efficient workflow for ICT-based traders.
Every component has been designed to integrate seamlessly and update dynamically across timeframes.
The indicator focuses on clarity, performance and customization, allowing traders to tailor every part of their trading experience.
Equal Highs & Lows
This feature automatically detects and marks Equal Highs (EQH) and Equal Lows (EQL) with full control over visuals and behavior.
Users can customize line colors, widths, and styles, label size, color, background transparency and text offset.
The logic uses an optimized scanning and caching system that maintains smooth performance even on higher timeframes.
It provides a precise and adaptive way to identify structural liquidity points whilst keeping the chart clean and readable.
Killzones & Session Pivots
Plots the main trading sessions such as Asia, London and New York (AM, Lunch, PM) with full flexibility and styling options.
Each session can be enabled or disabled individually, with its own color, transparency and label preferences.
Session highs and lows are automatically tracked and plotted as pivots with extension modes like Until Mitigated or Past Mitigation.
This system gives traders the ability to organize market sessions exactly how they prefer whilst keeping the chart consistent and efficient.
Daily Pivots and Tier System
Alongside session pivots, the script tracks daily highs and lows to provide a broader structural view of price. These pivots are stored and displayed on the chart with their appearance updating automatically when price interacts with them.
The system includes a unique tier-based visibility filter that maintains a clean chart by preventing duplicate or overlapping pivots. Recent daily pivots are cached and compared to session pivots and when two levels fall within a defined proximity, the redundant one is automatically hidden. This creates a clear hierarchy of daily and session levels, keeping the most relevant structure visible whilst removing noise.
All aspects of the daily pivot system are fully customizable, including the number of tracked pivots, color, style settings and how mitigated levels are handled. The caching and filtering logic ensures smooth performance and a visually organized workspace even as the data updates in real time.
Key Times
Allows up to five custom key time markers such as the Midnight Open, 6:00 AM or 10:00 AM.
Each marker can be fully customized with its own text, color, line style and thickness.
This makes it simple to visualize key reaction points that align with each traders timing model.
Higher Timeframe Candles
Displays higher timeframe candles such as 1H, 4H or Daily directly on the active chart to provide context without switching views.
Users can customize body, wick and border colors, along with adding optional trace lines for the open, close, high and low and can also show the countdown timers for remaining candle time.
Adjustable spacing, positioning and label visibility makes the display blend naturally with any trading setup.
This module helps traders connect multiple timeframes visually in a clean and intuitive way.
Watermark
Adds a customizable watermark with title, subtitle and symbol or timeframe information.
Every element can be adjusted for color, size, transparency, alignment and position.
The result is a polished, professional chart layout that adapts to the user's personal style.
Optimization and Design
ICT Essentials is built for performance, using cached arrays and lightweight calculations to maintain responsiveness on all timeframes.
Each feature can be toggled individually to suit the traders focus or system performance.
The script delivers a fluid, customizable and highly optimized trading experience designed to feel natural and effortless in day-to-day use.
Credits
This script takes reference and inspiration from several open-source indicators:
Equal Highs and Lows by jzstur
ICT HTF Candles (fadi) by fadizeidan
ICT Killzones + Pivots EP by tradeforopp
AG FX - Watermark by AGFXTRADING
All components have been refactored, optimized and unified into a single framework for a smoother and more efficient workflow.
Machine Learning Price Predictor: Ridge AR [Bitwardex]🔹Machine Learning Price Predictor: Ridge AR is a research-oriented indicator demonstrating the use of Regularized AutoRegression (Ridge AR) for short-term price forecasting.
The model combines autoregressive structure with Ridge regularization , providing stability under noisy or volatile market conditions.
The latest version introduces Bull and Bear signals , visually representing the current momentum phase and model direction directly on the chart.
Unlike traditional linear regression, Ridge AR minimizes overfitting, stabilizes coefficient dynamics, and enhances predictive consistency in correlated datasets.
The script plots:
Fit Line — in-sample fitted data;
Forecast Line — out-of-sample projection;
Trend Segments — color-coded bullish/bearish sections;
Bull/Bear Labels 🐂🐻 — dynamic visual signals showing directional bias.
Designed for researchers, students, and developers, this tool helps explore regularized time-series forecasting in Pine Script™.
🧩 Ridge AR Settings
Training Window — number of bars used for model training;
Forecast Horizon — forecast length (bars ahead);
AR Order — number of lags used as features;
Ridge Strength (λ) — regularization coefficient;
Damping Factor — exponential trend decay rate;
Trend Length — period for trend/volatility estimation;
Momentum Weight — strength of the recent move;
Mean Reversion — pullback intensity toward the mean.
🧮 Data Processing
Prefilter:
None — raw close price;
EMA — exponential smoothing;
SuperSmoother — Ehlers filter for noise reduction.
EMA Length, SuperSmoother Length — smoothing parameters.
🖥️ Display Settings
Update Mode:
Lock — static model;
Update Once Reached — rebuild after forecast horizon;
Continuous — update every bar.
Forecast Color — projection line color;
Bullish/Bearish Colors — colors for trend segments.
🐂🐻 Bull/Bear Signal System
The Bull/Bear Signal System adds directional visual cues to highlight local momentum shifts and model-based trend confirmation.
Bull (🐂) — appears when upward momentum is confirmed (momentum > 0) .
Displayed below the bar, colored with Bullish Color.
Bear (🐻) — appears when downward momentum is dominant (momentum < 0) .
Displayed above the bar, colored with Bearish Color.
Signals are generated during model recalculations or when the directional bias changes in Continuous mode.
These visual markers are analytical aids , not trading triggers.
🧠 Core Algorithmic Components
Regularized AutoRegression (Ridge AR):
Solves: (X′X+λI)−1X′y
to derive stable regression coefficients.
Matrix and Pseudoinverse Operations — implemented natively in Pine Script™.
Prefiltering (EMA / Ehlers SuperSmoother) — stabilizes noisy data.
Forecast Dynamics — integrates damping, momentum, and mean reversion.
Trend Visualization — color-coded bullish/bearish line segments.
Bull/Bear Signal Engine — visualizes real-time impulse direction.
📊 Applications
Academic and educational purposes;
Demonstration of Ridge Regression and AR models;
Analysis of bull/bear market phase transitions;
Visualization of time-series dependencies.
⚠️ Disclaimer
This script is provided for educational and research purposes only.
It does not provide trading or investment advice.
The author assumes no liability for financial losses resulting from its use.
Use responsibly and at your own risk.
Turn your back on me Scar ~_^What it does
Multi-timeframe support/resistance built from confirmed swing pivots on the timeframes you enable (5m, 15m, 1H, 4H, 1D, 1W). Levels are timeframe-invariant: the same prices show up whether you view the chart on 1m, 5m, 15m, 1H, 4H, 1D, or 1W.
How it works (simple)
Finds confirmed pivot highs/lows in each selected TF (no lookahead).
Brings those pivot prices to your chart and stores them as S/R candidates.
Optionally merges near-duplicate levels (within N ticks).
Draws up to X past levels per side (you choose the number).
Each line can show a small TF tag (e.g., “1H R”, “15m S”) so you know where it came from.
Why it stays the same across chart TFs
The “last pivots” are counted inside each source timeframe first, then displayed—so a 5m level is the same number no matter which chart timeframe you’re on.
Inputs
Pivot Left / Right – strictness of swing confirmation.
Enable TFs – 5m, 15m, 1H, 4H, 1D, 1W. (No 30m in this version.)
How many past levels per side – choose 5, 50, 500, etc.
Merge levels within N ticks – reduces clutter by combining overlapping lines.
Colors & widths – separate styling for Support/Resistance.
Show TF labels – toggle small tags on each line.
Notes & tips
Uses confirmed pivots; once a pivot is confirmed, its line does not repaint (new pivots will appear after right bars).
If you crank past levels very high with many TFs enabled, you may hit TradingView’s drawing limits—lower the count or increase merge ticks.
Works on any symbol and timeframe; outputs are consistent across chart TFs by design.
This script focuses only on S/R (no HH/HL/LH/LL, BOS/CHOCH, FVGs, or order blocks).
Disclaimer
For education only—always confirm levels with your own analysis and risk management.
Cumulative Volume DeltaCumulative Volume Delta (CVD) Indicator
This indicator is a modification of the Trading View CVD indicator. Cumulative Volume Delta (CVD), which represents the net difference between up volume (volume traded as the price increases) and down volume (volume traded as the price decreases) over a chosen Anchor Period.
The data for the CVD calculation is requested using the built-in ta.requestVolumeDelta function from a lower timeframe to approximate the directional volume with greater precision. This lower timeframe is either automatically selected based on the chart's timeframe or can be customized by the user.
Key Features and Inputs
Anchor Period: Defines the period over which the volume delta is accumulated and plotted. The default is "1D" (Daily), but it can be changed to any higher timeframe (e.g., "1W" for Weekly) to analyze CVD across different cycles.
CVD Candle Plot: The calculated volume delta values are plotted as a custom candle, where:
The open and close of the CVD candle represent the volume delta at the start and end of the anchor period, respectively.
The high and low represent the maximum and minimum volume delta reached during that period.
Up/Down Coloring Logic: The color of the CVD candle is determined by the directional movement of the price during the anchor period, allowing traders to quickly correlate volume delta with price action. Users can select between two methods via the "Strong Up/Down Coloring" input:
Strong Up/Down (Default): The candle is colored bullish (Teal) if the current price closes above the previous bar's high or bearish (Red) if it closes below the previous bar's low. This logic highlights significant momentum.
Regular Up/Down: The candle is colored bullish (Teal) if the close is greater than the open (price moved up) or bearish (Red) if the close is less than the open (price moved down).
Lower Timeframe Selection: This determines the resolution of the up and down volume components.
By default, the script automatically selects an appropriate lower timeframe (e.g., "1" minute for intraday charts, "5" minutes for daily charts) to balance historical data availability with calculation precision.
An option is provided to customize this "Lower Timeframe" for advanced users seeking higher or lower resolution.
The CVD indicator is a powerful tool for analyzing order flow dynamics and assessing the genuine strength of price movements by comparing the aggregate buying pressure (up volume) against the selling pressure (down volume).
Technical Notes (Code Details)
Language: Pine Script® //@version=6.
Function: Utilizes the ta.requestVolumeDelta() function with a user-defined anchorInput (default "1D") and a determined lowerTimeframe to retrieve the relevant delta data: .
Error Handling: Includes a check to confirm the symbol provides volume data, preventing runtime errors.
Multi Brownian Forecast📊 Multi Brownian Forecast (Time-Adaptive, Probabilistic)
This indicator uses a sophisticated Geometric Brownian Motion (GBM) Monte Carlo simulation to project future price paths. It adapts to any chart timeframe and provides quantitative, multi-period probability signals.
---
🧠 Core Mathematical Methodology
The model relies on GBM, which is a continuous-time stochastic process that models asset prices.
1. Historical Analysis (Drift & Volatility):
* The script first calculates Logarithmic Returns over a user-defined Historical Lookback (Hours) .
* Drift ($\mu$): Computed as the average of the log returns.
* Volatility ($\sigma$): Computed as the standard deviation of the log returns.
* These values are then time-adapted to an hourly step, compensating for the chart's current timeframe (e.g., 5-minute, 1-hour).
2. Monte Carlo Simulation:
* It runs a specified Number of Simulations (e.g., 1000).
* For each simulation, the price is stepped forward hourly using the GBM formula, which incorporates the calculated drift and a random shock drawn from a normal distribution (generated via the Box-Muller transform ).
---
✨ Key Features
Probabilistic Quartile Forecast: Plots a dynamic "cone" of probability on the chart. It shows key price percentiles (Q1, Q2/Median, Q3, and Q4/Outer Bound) at the forecast's expiration, visualizing the expected range of price outcomes based on the simulations.
Multi-Period Probability Signals: This is the core signal feature. Users can define multiple, independent forecast periods (e.g., 4h, 16h, 48h) in a comma-separated list.
* For each period, a Probability Up and Probability Down is calculated based on hitting a custom Target Price Change (%) (e.g., 2%) at a certain confidence level given a simulation over the historical backlook.
* The probabilities are displayed in a chart table. The cell text turns white if the calculated probability exceeds the user-defined Signal Confidence (%) .
Conditional Fibonacci Retracement: Optionally displays a Fibonacci Retracement on the chart. This feature is only activated when one of the multi-period signals reaches its minimum confidence threshold, providing a contextual technical level when a probabilistic edge is found.
EMA × MOST CrossThe EMA × MOST Cross indicator combines the Exponential Moving Average (EMA) with the Moving Stop (MOST) system to identify early trend reversals and confirm trend continuation phases.
MOST acts as a dynamic trailing stop that adapts to price volatility, while EMA provides directional bias and short-term momentum confirmation.
A BUY signal is generated when EMA crosses above the MOST line, indicating a possible bullish reversal or trend continuation.
A SELL signal is triggered when EMA crosses below the MOST line, suggesting bearish continuation or reversal conditions.
The indicator colors bars according to the EMA–MOST relationship to visually represent trend strength:
🟩 Green tones → bullish bias (EMA and price above MOST)
🟥 Red tones → bearish bias (EMA and price below MOST)
🟦 Aqua → neutral phase or transition zone
How to use:
Works best on trending markets and mid-term timeframes (e.g., 1h, 4h, 1D).
Combine it with volume or structure-based confirmations for higher accuracy.
Use the built-in parameters to fine-tune sensitivity:
MOST MA length: adjusts the responsiveness of the MOST line.
MOST percent: defines the offset distance of the stop bands.
EMA length: defines the crossover sensitivity.
Updated settings:
Default MOST Length: 5
Default MOST Percent: 1.5%
Concept:
This script refines the traditional MOST logic by pairing it with an EMA cross mechanism, aiming to filter false reversals and improve entry timing. It’s designed for traders who prefer clear, visual cross-based trend confirmation while maintaining adjustable flexibility for different instruments.
