Market Manipulation Index (MMI)The Composite Manipulation Index (CMI) is a structural integrity tool that quantifies how chaotic or orderly current market conditions are, with the aim of detecting potentially manipulated or unstable environments. It blends two distinct mathematical models that assess price behavior in terms of both structural rhythm and predictability.
1. Sine-Fit Deviation Model:
This component assumes that ideal, low-manipulation price behavior resembles a smooth oscillation, such as a sine wave. It generates a synthetic sine wave using a user-defined period and compares it to actual price movement over an adaptive window. The error between the real price and this synthetic wave—normalized by price variance—forms the Sine-Based Manipulation Index. A high error indicates deviation from natural rhythm, suggesting structural disorder.
2. Predictability-Based Model:
The second component estimates how well current price can be predicted using recent price lags. A two-variable rolling linear regression is computed between the current price and two lagged inputs (close and close ). If the predicted price diverges from the actual price, this error—also normalized by price variance—reflects unpredictability. High prediction error implies a more manipulated or erratic environment.
3. Adaptive Mechanism:
Both components are calculated using an adaptive smoothing window based on the Average True Range (ATR). This allows the indicator to respond proportionally to market volatility. During high volatility, the analysis window expands to avoid over-sensitivity; during calm periods, it contracts for better responsiveness.
4. Composite Output:
The two normalized metrics are averaged to form the final CMI value, which is then optionally smoothed further. The output is scaled between 0 and 1:
0 indicates a highly structured, orderly market.
1 indicates complete structural breakdown or randomness.
Suggested Interpretation:
CMI < 0.3: Market is clean and structured. Trend-following or breakout strategies may perform better.
CMI > 0.7: Market is structurally unstable. Choppy price action, fakeouts, or manipulative behavior may dominate.
CMI 0.3–0.7: Transitional zone. Caution or reduced risk may be warranted.
This indicator is designed to serve as a contextual filter, helping traders assess whether current market conditions are conducive to structured strategies, or if discretion and defense are more appropriate.
Osilatörler
VWAP Momentum and Volatility IndicatorVWAP Momentum and Volatility Indicator
Merges VWAP trend, momentum oscillators (RSI & Stochastic), volatility measures (ATR & Bollinger Bands) and an optional volume filter into one overlay to generate more reliable buy/sell signals.
1) Components & Rationale
VWAP (Session/Day/Week/Month): Shows the volume-weighted average price trend with selectable reset periods.
VWAP ±1/±2/±3 StdDev Bands: Highlight volatility expansions or contractions—price moves outside these bands can signal breakouts or reversals.
RSI (14): Confirms overbought (>70) and oversold (<30) momentum, reducing false entries.
Stochastic (14, SlowK=3, SlowD=3): Captures momentum shifts; used alongside RSI for stronger confirmation.
ATR (14): Measures absolute price movement to aid in risk sizing and contextualizing band widths.
Bollinger Bands (20, 2σ): Identifies “squeeze” (low volatility) and “expansion” phases.
Volume Filter (optional): Ensures signals are backed by above-average volume.
2) Default Settings
VWAP Reset: Session
StdDev Multiplier: 2.0
VWAP Lookback: 20 bars
RSI: 14 period, Overbought = 70, Oversold = 30
Stochastic: 14 period, SlowK = 3, SlowD = 3
ATR: 14 period
Bollinger Bands: 20 period, Multiplier = 2
Volume Filter: 10-bar SMA threshold at 1.5× average
Visuals: VWAP bands, signal markers, and info table enabled; table positioned top-right at small size.
3) How to Use
Add to chart: Select “VWAP Momentum and Volatility Indicator.”
Adjust inputs: Set reset period, band multiplier, momentum thresholds and volume filter to match your asset and timeframe.
Buy signal: Price crosses above VWAP + (RSI < 50 or Stochastic in oversold) + volume filter pass.
Sell signal: Price crosses below VWAP + (RSI > 50 or Stochastic in overbought) + volume filter pass.
Info table: Review VWAP status, distance (%), band region, RSI, Stochastic, ATR%, Bollinger width, squeeze/expansion, relative volume, and the most recent signal.
4) Warnings & Disclaimer
This indicator is provided for educational purposes only. Always backtest with real funding and volume data, apply your own risk management, and recognize that past performance does not guarantee future results. Use the settings and signals as part of a broader trading plan.
Funding Rate Strategy IndicatorDescription
Funding Rate Backtest Strategy uses smoothed funding‐rate dynamics to trigger long/short trades, enhanced by volume, session and daily‐limit filters, plus configurable profit-taking, stop-loss and trailing stops. It is designed for perpetual‐swap markets (e.g. BTCUSDT) where funding costs reflect market sentiment.
1. Strategy Logic & Components
Funding Rate Source
External: real exchange funding rate (e.g. Binance funding).
Custom: manual override value.
Simulate: sine‐wave test data between –3 and +3 to validate behavior.
Entry Conditions
LONG when fundingRate ≤ Long Threshold (default –2.0)
SHORT when fundingRate ≥ Short Threshold (default +2.0)
Volume Filter: requires a ≥ 5% increase vs prior bar.
4H Session Filter: only triggers on new 4-hour bars (optional).
Daily Cap: max 5 signals per calendar day (prevents overtrading).
Weekend Trading: on/off toggle for Saturday–Sunday.
Exit Conditions
Funding Normalization: exit LONG when fundingRate > –0.5; exit SHORT when fundingRate < +0.5.
Profit-Taking & Stop-Loss: default TP = 5%, SL = 3% of entry price.
Trailing Stop: optional 2% trailing (togglable).
2. Default Settings & Backtest Parameters
Account Size: $10,000
Position Sizing: 10% of equity per trade
Commission: 0.10% per side
Slippage: 0.05% per trade
Instrument & Timeframe: BTCUSDT perpetual, 1H bars, Jan 1 2022 – Dec 31 2023
Volume Increase: 5%
Session Filter: 4-hour bars only
Max Signals/Day: 5
Weekend Trading: Enabled
3. Backtest Results (Jan 2022–Dec 2023)
Total Trades: 142
Win Rate: 55.6%
Average R/R: 1 : 1.4
Max Drawdown: 14.8%
Net Return: +22.3%
These results assume realistic commission (0.1%) and slippage (0.05%). Past performance is not indicative of future results.
4. Default Properties Explained
Property Default Description
rateSourceChoice External Select funding‐rate data source
fundingRateLongThreshold –2.0 Funding ≤ –2% → LONG condition
fundingRateShortThreshold +2.0 Funding ≥ +2% → SHORT condition
volumeIncreasePercent 5.0 Min % volume increase vs prior bar
enableFourHourFilter true Only trigger on new 4H sessions
maxSignalsPerDay 5 Daily cap on entries
exitLongThreshold –0.5 Funding > –0.5% → exit LONG
exitShortThreshold +0.5 Funding < +0.5% → exit SHORT
takeProfitPercent 5.0 Fixed profit target in %
stopLossPercent 3.0 Fixed stop‐loss in %
useTrailingStop false Toggle trailing stop
trailingStopPercent 2.0 Trailing stop distance in %
allowWeekendTrading true Allow entries on Sat/Sun
5. How to Use
Add to Chart → search “Funding Rate Backtest.”
Configure Inputs → choose your funding‐rate feed, adjust thresholds, volume and session filters.
Position Sizing → defaults to 10% equity; adjust if desired.
Monitor Table & Signals → on‐chart shapes mark entries/exits; status table shows open P&L and signals count.
Risk Management → always verify commission/slippage settings; limit risk to sustainable levels (≤ 10% equity per trade).
6. Warnings & Disclaimer
This strategy is for educational purposes only. Real funding rates may differ—replace simulation or custom inputs with actual data. Always apply your own analysis and risk management. Past backtest performance does not guarantee future results.
Funding Rate Signal TableDescription
Funding Rate Signal Table computes a rolling “funding rate” value (simulated here as (close–open)/close), smooths it, and presents both a compact on-chart table and clear LONG/SHORT entry signals. It helps you spot when funding dynamics may favor long or short positions and visualizes the last signal’s price level.
1. Why This Mashup?
Funding Rate Trend: A smoothed funding rate highlights shifts in trader funding costs—extremely negative rates can signal bullish opportunity, while very positive rates can warn of bearish pressure.
Difference Filter: Optional “difference” check prevents signals on noisy small changes, requiring a meaningful move before confirming.
Table & Labels: Side-by-side display of current funding rate, prior value, absolute change and text signal makes interpretation immediate. Simultaneous price-level lines reinforce real-time trade reference.
2. Default Parameters & Data Assumptions
Funding Calculation: (close – open) / close * 100, smoothed by a 14-period SMA plus 3-period SMA.
Thresholds:
LONG if funding_rate < –0.01%
SHORT if funding_rate > 0.01%
Optional “difference” threshold of 0.002 (0.2%)
Visuals:
Table positioned top-right with ticker, timeframe, funding values, difference, and signal.
Labels sized Normal by default, drawn just above/below price with optional price text.
Dashed horizontal lines extend 200 bars to mark last LONG/SHORT price.
Note: Because Pine Script cannot natively access actual exchange funding data, this example simulates funding rate. Replace the raw_funding_rate formula with your real funding-feed series for accurate signals.
3. How to Use
Add to Chart → Select “Rolin Long – Funding Rate & Sinyal Tablosu.”
Adjust Settings → Open the indicator’s Inputs:
Period & Smoothing for your instrument’s data frequency.
Thresholds based on historical funding ranges you observe.
Enable “Difference” filter to reduce false triggers.
Toggle Price Levels if you prefer lines marking entry prices.
Interpret Table →
“Funding Rate”: smoothed value for current bar.
“Previous Funding”: last bar’s value.
“Difference”: absolute change.
“Signal”: “LONG ▲ Şartları” or “SHORT ▼ Şartları” when thresholds are met.
Watch for Labels → On a new bar close, a singular LONG or SHORT label appears at the bar where the condition first became true.
Plan Entries/Exits → Use the price-level lines and your own risk rules to size and time trades.
4. Warnings & Disclaimer
This indicator is for educational purposes only. Simulated funding rate may differ from real exchange fees. Always verify with actual funding data, apply your own risk management, and adjust commissions/slippage to your trading environment. Past indicator signals do not guarantee future performance.
Professional Multi-Indicator SystemDescription
Professional Multi-Indicator System merges several proven technical indicators into a single overlay, allowing you to monitor trend, momentum, volatility, and key price levels all at once. Below you’ll find why these components work together, default parameters, backtest results, usage recommendations, and important disclaimers.
1. Mashup Justification & Components
MACD: Detects trend direction and momentum shifts via fast/slow crossover and histogram analysis.
RSI: Filters overbought/oversold conditions and confirms momentum using a 50-level threshold.
Bollinger Bands: Captures volatility squeezes and band touches to signal potential breakouts or pullbacks.
Fibonacci Retracement: Automatically (or manually) draws key support/resistance levels at 23.6%, 38.2%, 50%, 61.8%, 78.6%, and 100%.
Combined Workflow:
Trend Confirmation (MACD + RSI)
Volatility Check (Bollinger Bands)
Level-Based Entries/Exits (Fibonacci)
This layered approach reduces false signals and increases overall reliability.
2. Default Settings
Account Size: $10,000 (example)
Commission: 0.1% per trade
Slippage: 0.05%
Test Instrument & Period: BTCUSDT 1H, Jan 1 2022 – Dec 31 2023
Risk per Trade: Maximum 5% of equity
Indicator Defaults:
MACD: 12 / 26 / 9 (optional confirmation)
RSI: 14 period, OB = 70, OS = 30 (optional confirmation)
Bollinger Bands: 20 period, ±2 σ (optional confirmation)
Fibonacci: 50 period, auto-trend detection on
Volume Filter: 20-period SMA, threshold = 1.5× average
Visuals: Modern labels, large icons, info table in top-right
3. Backtest Summary
Total Trades: 158
Win Rate: 58.2%
Average Risk/Reward: 1:1.6
Max Drawdown: 12.4%
Net Return: +24.7%
Note: Past performance does not guarantee future results. Adjust settings to your own instruments and timeframes.
4. How to Use
Add to Chart: Select “Professional Multi-Indicator System.”
Review Settings: Open Settings → Main, MACD, RSI, Bollinger, Volume, Fibonacci, Visuals.
Enable Confirmations: Turn on “confirmation” for each component to filter weak signals.
Wait for Strong Signal: Consider entries when signalStrength ≥ 3/5.
Manage Risk: Size positions ≤ 5% of your capital; factor in commission/slippage.
Exit Rules: Close on “Strong SELL” alert or your predefined stop-loss.
5. Warnings & Disclaimer
This indicator is for educational purposes only. Always apply your own analysis and risk management. Past performance is not indicative of future results. Update commission, slippage, and risk settings to match your trading environment.
[Pandora's Chambers] Apex-Flux NavigatorThe " Apex Flux Navigator FC" indicator, whose name alludes to the unveiling of hidden market forces, offers a rich visual representation of market pressure by combining volume-based pivot analysis with RSI, including a dynamic Fibonacci grid, balanced pressure lines, and highlighted boxes for quick readability. The term "Chambers" in its name refers to the way the indicator frames the balance of power between buyers and sellers within the space defined by two consecutive pivot lines, essentially creating visual chambers that encapsulate this ongoing struggle. The grid is built according to the 25%, 38.2%, 50%, 61.8%, and 75% levels, marking key support and resistance points. Crucially, this indicator allows you to spot pinpoint momentum divergences against volume, offering insights into potential trend reversals or continuations. The indicator also calculates cumulative buy/sell percentages since the formation of each pivot, displays an average Buy/Sell ratio for each point, uses a smart algorithm that analyzes the length of movement against speed, and draws backgrounds that outline liquidity zones based on Fibonacci ratios of volume and overbought/oversold areas (boxes) to clearly and legibly highlight buyer/seller pressure zones. Furthermore, the rapid identification of pressure zones and momentum shifts can assist in recognizing opportunities for quick scalping trades. Additionally, the width and spacing of the pressure lines visually represent the current market volatility and the difference in liquidity between buyers and sellers.
General Description
The indicator enables automatic identification of pivot points (highs and lows) based on buy/sell activity and TradingView RSI.
It draws vertical lines connecting the full pivot high to the full pivot low, creating a standard Fibonacci grid, and adds balanced pressure lines on the price sides with F--/F+/(F++) annotations corresponding to the degree of TradingView pressure.
How it Works
Pivot Identification – Uses ta.pivothigh and ta.pivotlow with the Pivot Sensitivity parameter to determine highs and lows.
Volume and RSI Collection – The f_addPivot function stores buy/sell volume according to the day's fluctuations and initial RSI; in each bar, the cumulative volume and RSI are updated to calculate a dynamic average.
Creation of Lines and Pressure Points – Calculates pressure percentages based on volume and displays them through dotted/solid lines and labels, including dynamic colors and backgrounds (boxes) for visual illustration using the TradingView “Pressure Lines” technique.
How to Interpret the Output
Dotted lines indicate Liquidity zones where the dominant side's volume is particularly strong and may mark areas that the price is drawn to in order to achieve equilibrium.
Labels with text (“B: xx% | RSI yy%”) display the buy/sell percentage and the average RSI since the pivot's creation together.
F--/F+/F++ annotations reflect a pressure quality scale using the f_getAnnotation function based on pressure percentages.
How to Use
Select “Add to chart” to attach the indicator to the chart.
Through the indicator's settings, you can change Pivot Sensitivity, Fibonacci Grid Length, RSI Period, and more.
Inputs and Settings
Pivot Sensitivity (default: 3)
Extend Pressure Lines (default: off)
RSI Period (default: 14)
Fibonacci Grid Length, Color, Offset
Colors and line styles for the reporting mode
Tips and Recommendations
Use a timeframe that reflects appropriate volatility (e.g., H4/D) to reduce noise; the shorter the timeframe, the more fluid the information the indicator presents.
To improve identification accuracy, combine with moving averages or additional Fibonacci tools.
Avoid automated trading based on the indicator alone – always require confirmation from an additional indicator.
Trade Smart – Let the Apex Flux Navigator FC guide you to significant market pressure levels!
RSI Run‑Length by ATTARSI Run‑Length by ATTA – The Next Generation of RSI
The RSI Run‑Length by ATTA indicator was developed to quantify not only the magnitude of price movements but also the continuity with which they occur. Instead of relying on point‑by‑point averages of gains and losses, it counts each sequence of consecutive gains (up‑run) and each sequence of consecutive losses (down‑run), applies Wilder’s RMA smoothing to these counts, and then computes the classic RSI formula on their ratio.
This approach significantly reduces market noise by giving greater weight to sustained trends, while simultaneously reducing the lag inherent in traditional methods. Rather than waiting for signals triggered by isolated fluctuations, RSI Run‑Length by ATTA detects turning points at the earliest stages of movement streaks and maintains precise, timely responsiveness.
Core Principles:
Run‑Length Counting: Measures trend depth without distortion from isolated spikes.
Wilder’s RMA on Counts: Provides statistical smoothing to suppress excessive volatility.
Classic RSI Formula: Applies the familiar RSI calculation to the smoothed run‑length ratio.
This mechanism enables early identification of momentum shifts and the construction of strategies based on stable sequences rather than sporadic gains. The simplicity of a single parameter (run‑length period – default 14) and the logical sequence of counting, smoothing, and ratio calculation make the tool both transparent and intuitive for technical traders and quantitative analysts alike.
Usage Instructions:
Select the run‑length period (commonly 14 bars).
Set overbought/oversold thresholds (recommended 70/30).
Overlay with complementary indicators (classic RSI, MACD, etc.) for confirmation.
I invite traders and analysts to incorporate RSI Run‑Length by ATTA into their indicator libraries to gain deeper, more actionable insights into price momentum.
RSI-EMA-Crossing with Donchian-Stop-LossThe Donchian RSI Indicator is a visual tool that combines momentum and trend analysis to identify high-quality long opportunities based on RSI crossovers, price action, and Donchian channel dynamics.
How It Works
Momentum Signal: A bullish RSI crossover is detected when the RSI crosses above its moving average.
Trend Filter: A signal is only valid if the crossover occurs while the price is above its moving average – filtering out entries against the prevailing trend.
Signal Candle: The high of the crossover candle is stored.
Entry Trigger: A valid signal occurs when a later candle closes above that signal high.
Stop-Loss (Visual Only)
The lower band of the Donchian Channel acts as a visual reference for a dynamic stop-loss level.
Features
Customizable RSI, Donchian Channel, and moving average lengths
Selectable MA types: SMA, EMA, WMA, VWMA, HMA
Signal candle highlighted (yellow background)
Entry points labeled on the chart
Price MA and Donchian Channel plotted
Trend filter improves signal quality by confirming upward bias
Use Case
Designed for swing and position traders
Optimized for use on daily or 4H charts
RSI Fibonacci LevelsThank for
Kadir Türok Özdamar - @kadirturokozdmr
Formula Purpose of Use
This formula combines the traditional RSI indicator with Fibonacci levels to create a special technical indicator that aims to identify potential support and resistance points:
Determines the historical RSI range of 144 periods (PEAK and DIP)
Calculates Fibonacci retracement levels within this range, and shows the direction of momentum by calculating the moving average of the RSI
This indicator can be used to identify potential reversal points, especially when the RSI is not in overbought (70+) or oversold (30-) areas.
Practical Use
Investors can use this indicator as follows:
1⃣When the RSI approaches one of the determined Fibonacci levels, it is considered a potential support/resistance area.
2⃣When the RSI approaches the DIP level, it can be interpreted as oversold, and when it approaches the PEAK level, it can be interpreted as overbought.
3⃣When the RSI crosses the SM (moving average) line upwards or downwards, it can be evaluated as a momentum change signal.
4⃣Fibonacci levels (especially M386, M500 and M618) can be monitored as important transition zones for the RSI.
With this indicator, we aim to develop the traditional RSI usage and produce more nuanced buy-sell signals.
Turkish :
Formula Purpose of Use
This formula combines the traditional RSI indicator with Fibonacci levels to create a special technical indicator that aims to identify potential support and resistance points:
Determines the historical RSI range of 144 periods (PEAK and DIP)
Calculates Fibonacci retracement levels within this range, and shows the direction of momentum by calculating the moving average of the RSI
This indicator can be used to identify potential reversal points, especially when the RSI is not in overbought (70+) or oversold (30-) areas.
Practical Use
Investors can use this indicator as follows:
1⃣When the RSI approaches one of the determined Fibonacci levels, it is considered a potential support/resistance area.
2⃣When the RSI approaches the DIP level, it can be interpreted as oversold, and when it approaches the PEAK level, it can be interpreted as overbought.
3⃣When the RSI crosses the SM (moving average) line upwards or downwards, it can be evaluated as a momentum change signal.
4⃣Fibonacci levels (especially M386, M500 and M618) can be monitored as important transition zones for the RSI.
With this indicator, we aim to develop the traditional RSI usage and produce more nuanced buy-sell signals.
C&B Auto MK5C&B Auto MK5.2ema BullBear
Overview
The C&B Auto MK5.2ema BullBear is a versatile Pine Script indicator designed to help traders identify bullish and bearish market conditions across various timeframes. It combines Exponential Moving Averages (EMAs), Relative Strength Index (RSI), Average True Range (ATR), and customizable time filters to generate actionable signals. The indicator overlays on the price chart, displaying EMAs, a dynamic cloud, scaled RSI levels, bull/bear signals, and market condition labels, making it suitable for swing trading, day trading, or scalping in trending or volatile markets.
What It Does
This indicator generates bull and bear signals based on the interaction of two EMAs, filtered by RSI thresholds, ATR-based volatility, a 50/200 EMA trend filter, and user-defined time windows. It adapts to market volatility by adjusting EMA lengths and RSI thresholds. A dynamic cloud highlights trend direction or neutral zones, with candlestick coloring in neutral conditions. Market condition labels (current and historical) provide real-time trend and volatility context, displayed above the chart.
How It Works
The indicator uses the following components:
EMAs: Two EMAs (short and long) are calculated on a user-selected timeframe (1, 5, 15, 30, or 60 minutes). Their crossover or crossunder triggers potential bull/bear signals. EMA lengths adjust based on volatility (e.g., 10/20 for volatile markets, 5/10 for non-volatile).
Dynamic Cloud: The area between the EMAs forms a cloud, colored green for bullish trends, red for bearish trends, or a user-defined color (default yellow) for neutral zones (when EMAs are close, determined by an ATR-based threshold). Users can widen the cloud for visibility.
RSI Filter: RSI is scaled to price levels and plotted on the chart (optional). Signals are filtered to ensure RSI is within volatility-adjusted bull/bear thresholds and not in overbought/oversold zones.
ATR Volatility Filter: An optional filter ensures signals occur during sufficient volatility (ATR(14) > SMA(ATR, 20)).
50/200 EMA Trend Filter: An optional filter restricts bull signals to bullish trends (50 EMA > 200 EMA) and bear signals to bearish trends (50 EMA < 200 EMA).
Time Filter: Signals are restricted to a user-defined UTC time window (default 9:00–15:00), aligning with active trading sessions.
Market Condition Labels: Labels above the chart display the current trend (Bullish, Bearish, Neutral) and optionally volatility (e.g., “Bullish Volatile”). Up to two historical labels persist for a user-defined number of bars (default 5) to show recent trend changes.
Visual Aids: Bull signals appear as green triangles/labels below the bar, bear signals as red triangles/labels above. Candlesticks in neutral zones are colored (default yellow).
The indicator ensures compatibility with standard chart types (e.g., candlestick or bar charts) to produce realistic signals, avoiding non-standard types like Heikin Ashi or Renko.
How to Use It
Add to Chart: Apply the indicator to a candlestick or bar chart on TradingView.
Configure Settings:
Timeframe: Choose a timeframe (1, 5, 15, 30, or 60 minutes) to match your trading style.
Filters:
Enable/disable the ATR volatility filter to focus on high-volatility periods.
Enable/disable the 50/200 EMA trend filter to align signals with the broader trend.
Enable the time filter and set custom UTC hours/minutes (default 9:00–15:00).
Cloud Settings: Adjust the cloud width, neutral zone threshold, color, and transparency.
EMA Colors: Use default trend-based colors or set custom colors for short/long EMAs.
RSI Display: Toggle the scaled RSI and its thresholds, with customizable colors.
Signal Settings: Toggle bull/bear labels and set signal colors.
Market Condition Labels: Toggle current/historical labels, include/exclude volatility, and adjust decay period.
Interpret Signals:
Bull Signal: A green triangle or “Bull” label below the bar indicates potential bullish momentum (EMA crossover, RSI above bull threshold, within time window, passing filters).
Bear Signal: A red triangle or “Bear” label above the bar indicates potential bearish momentum (EMA crossunder, RSI below bear threshold, within time window, passing filters).
Neutral Zone: Yellow candlesticks and cloud (if enabled) suggest a lack of clear trend; consider range-bound strategies or avoid trading.
Market Condition Labels: Check labels above the chart for real-time trend (Bullish, Bearish, Neutral) and volatility status to confirm market context.
Monitor Context: Use the cloud, RSI, and labels to assess trend strength and volatility before acting on signals.
Unique Features
Volatility-Adaptive EMAs: Automatically adjusts EMA lengths based on ATR to suit volatile or non-volatile markets, reducing manual configuration.
Neutral Zone Detection: Uses an ATR-based threshold to identify low-trend periods, helping traders avoid choppy markets.
Scaled RSI Visualization: Plots RSI and thresholds directly on the price chart, simplifying momentum analysis relative to price.
Flexible Time Filtering: Supports precise UTC-based trading windows, ideal for day traders targeting specific sessions.
Historical Market Labels: Displays recent trend changes (up to two) with a decay period, providing context for market shifts.
50/200 EMA Trend Filter: Aligns signals with the broader market trend, enhancing signal reliability.
Notes
Use on standard candlestick or bar charts to ensure accurate signals.
Test the indicator on a demo account to optimize settings for your market and timeframe.
Combine with other analysis (e.g., support/resistance, volume) for better decision-making.
The indicator is not a standalone system; use it as part of a broader trading strategy.
Limitations
Signals may lag in fast-moving markets due to EMA-based calculations.
Neutral zone detection may vary in extremely volatile or illiquid markets.
Time filters are UTC-based; ensure your platform’s timezone settings align.
This indicator is designed for traders seeking a customizable, trend-following tool that adapts to volatility and provides clear visual cues with robust filtering for bullish and bearish market conditions.
Volumetric Tensegrity🧮 Volumetric Tensegrity unifies two of the Leading Indicator suite's critical engines — ZVOL ( volume anomaly detection ) and OBVX ( directional conviction ). Originally designed as a structural economizer for traders navigating strict indicator limits (e.g. < 10 slots per chart), it was forced to evolve beyond that constraint simply to fulfill it, albeit with a difference. The fatal flaw of traditional fusion, where two metrics are blended mathematically, is that they lose scale integrity (i.e. meaning). VTense encodes optical tensegrity to scale the amplitude of the ZVOL histogram and the slope of the OBVX spread independently, so that expansion and direction may coexist without either dominating the frame.
🧬 Tensegrity , by definition, is an intelligent design principle where elements in compression are suspended within a network of continuous tension, forming a stable, self-supporting structure . Originally conceived in esoteric biomorphology (c.f. Da Vinci, Snelson, Casteneda), tensegrity balances force through opposition, not rigidity. Applied to financial markets, Volumetric Tensegrity captures this same principle: price compresses, volume expands, conviction builds or fades — yet structure holds through the interplay. The result is not a prediction engine, but a pressure field — one that visualizes where structure might bend, break, or rebound based on how volume breathes.
🗜️ Rather than layering multiple indicators and consuming precious chart space, VTense frees up room for complementary overlays like momentum mapping, liquidity tiers, or volatility phase detection — making it ideal for modular traders operating in tight technical real estate.
🧠 Core Logic - VTense separates and preserves two essential structural forces:
• ZVOL Histogram : A Z-score-based expansion map that measures current volume deviation from its historical average. It reveals buildup zones, dormant stretches, and breakout pressure — regardless of price behavior.
• OBVX Spread : A directional conviction curve that tracks the difference between On-Balance Volume and its volume-weighted fast trend. It shows whether the crowd is leaning in (accumulation/distribution) or backing off.
🔊 ZVOL controls the amplitude of the histogram, while OBVX controls the curvature and slope of the spread. Without sacrificing breathing behavior or analytical depth, VTense provides a compact yet dynamic lens to track both expansion pressure and directional bias within a single footprint.
🌊 Volumetric Tensegrity forecasts breakout readiness, trend fatigue, and compression zones by measuring the volatility within volume . Unlike traditional tools that track volatility of price, this indicator reveals when effort becomes unstable — signaling inflection points before price reacts. Designed to decode rhythm shifts at the volume level, it operates as a pre-ignition scanner that thrives on low-timeframe charts (15m and under) while scaling effectively to 1H for validation.
🪖 From Generals to Scouts
👀 When used jointly, ZVOL + OBVX act as the general : deep-field analysts confirming stress, commitment, or exhaustion. VTense , by contrast, functions as a scout — capturing subtle buildup and alignment before structure fully reveals itself. The indicator aims to be a literal vanguard, establishing a position that can be confirmed or flexibly abandoned when the higher authority arrives to evaluate.
🥂 Use the ZVOL + OBVX pair when :
• You need independent axis control and manual dissection
• You’re building long-form confluence setups
• You have more indicator slots than you need
🔎 Use VTense when :
• You need compact clarity across multiple instruments
• You’re prioritizing confluence _detection_ over granular separation
• You’re building efficient multi-layered systems under slot constraints
🏗️ Structural Behavior and Interpretation
🫁 Z VOL Respiration Histogram : Structural Effort vs Baseline
🔵 Compression Coil – volume volatility is low and stable; the market is coiling
🟢 Steady Rhythm – volume is healthy but unremarkable; balanced participation
🟡 Passive/Absorbed Effort – expansion failing to manifest; watch for reversal
🟠 Clean Expansion – actionable volatility rise backed by structure
🔴 Volatile Blowout – chaos, climax; likely end-phase or fakeout
⚖️ ZVOL Respiration measures how hard the crowd is pressing — not just that volume is rising, but how statistically abnormal the surge is. Because it is rescaled proportionally to OBVX, the amplitude of the histogram reflects structural urgency without overwhelming the visual field.
🖐️ OBVX Spread : Real-Time Directional Conviction Behind Price Moves
🔑 The curvature of the spread reveals not just directional bias but crowd temp o: sharp slopes = urgent transitions; gradual slopes = building structural shifts. Curvature is key: sharp OBVX slope = urgency; gentle arcs = controlled drift or indecision.
• Green Rising : Accumulation — upward pressure from real buyers
• Red Falling : Distribution — sell pressure, downward slope
• Flat Curves : Transitional → uncertainty, microstructure digestion
🎭 Synchronized vs Divergent Behavior
⏱️ Synchronized (high-confluence) : often precedes structural breakouts, with internal conviction clearly visible before price resolves.
• ZVOL expands (yellow/orange/red) and OBVX climbs steeply green = strong bullish pressure
• ZVOL expands while OBVX steepens red = growing sell-side intent
🪤 Divergent (conflict tension) : flags potential traps, fakeouts, and liquidity sweeps.
• ZVOL expands sharply, but OBVX flattens or opposes → reactive expansion without crowd commitment
⛔️ Latent Drift + Structural Holding Patterns : tensegrity in action — the market holds tension without directional release.
• ZVOL compresses (blue) + OBVX meanders near zero → structure is resting, building up energy
• After prolonged drift, expect violent asymmetry when balance finally breaks
📚 Phase Interpretation: Dynamic Structural Read
• 1️⃣ Quiet Coil : Histogram flat, OBVX flat → no urgency
• 2️⃣ Initial Pulse : Yellow bars, OBVX slope builds → actionable tension
• 3️⃣ Structural Breath : Synchronized expansion and slope → directional commitment
• 4️⃣ Disagreement : Spike in ZVOL, flattening OBVX → exhaustion risk or false signal
💡 Suggested Use
• Run on 15m charts for breakout anticipation and 1H for validation
• Pair with ZVOL + OBVX to confirm crowd conviction behind the tension phase
• Use as a rhythm filter for the suite's trend indicators (e.g., RDI , SUPeR TReND 2.718 , et. al.)
• Ideal during low-volume regimes to detect pressure buildup before triggers
🧏🏻 Volumetric Tensegrity doesn’t signal. It breathes , and listens to pressure shifts before they speak in price. As a scout, it lets you see structural posture before signals align — helping you front-run resolution with clarity, not prediction.
Triple Stoch and RSI (4 assets)4 Hour Green Dots -
This indicator looks at four different assets and shows when the RSI and 3 different stochastic RSI levels are all oversold.
You can optionally add Red dots when they are all overbought but doesn't seem to be as accurate.
The assets and levels are all customizable.
True Strength Index (TSI)%📌 Script Name: TSI Percentuale
This script is a custom True Strength Index (TSI) indicator that expresses momentum strength as a percentage from 0% to 100%, instead of the traditional TSI scale.
✅ What the Script Does
Calculates the standard TSI:
Uses double exponential smoothing of price changes and their absolute values.
Formula:
TSI_raw
=
100
×
DoubleSmoothed(ΔPrice)
DoubleSmoothed(|ΔPrice|)
TSI_raw=100×
DoubleSmoothed(|ΔPrice|)
DoubleSmoothed(ΔPrice)
Normalizes TSI to a percentile scale:
Over a user-defined lookback period, the script finds the lowest and highest TSI values.
It then rescales the current TSI to a value between 0% (minimum) and 100% (maximum).
50% represents neutral momentum (i.e., "flat").
Plots the result:
tsi_percent is plotted as a blue line.
Horizontal dashed/dotted lines are drawn at:
0% → strong downward momentum
50% → neutral
100% → strong upward momentum
⚙️ Inputs
Long Length: Long EMA smoothing period (default: 25)
Short Length: Short EMA smoothing period (default: 13)
Signal Length: (not used in this version, can be removed or extended)
Lookback Period: Number of bars to calculate min/max normalization (default: 100)
🧠 Why Use This Indicator
The classic TSI ranges around and can be hard to interpret.
This version makes TSI visually intuitive by converting it to percentile form, allowing easier comparison of momentum strength across time and instruments.
It’s particularly useful for defining zones like:
Above 70% = strong bullish
Below 30% = strong bearish
DDDDD: SMI Quad Sync📄DDDDD: SMI Quad Sync
A multi-timeframe momentum synchronization indicator using 4 Stochastic Oscillators with different lengths (9, 14, 40, 60) to detect collective oversold and overbought zones.
✅ Key Features:
Plots 4 stochastic lines with vertical offsets for better visual separation.
Generates a Long Signal (green square) when all 4 stochastics are below the oversold level.
Generates a Short Signal (red square) when all 4 stochastics are above the overbought level.
Use signals to confirm multi-timeframe momentum alignment or exhaustion.
🎯 How to Use:
Look for green square → potential LONG entry: signals multi-timeframe oversold condition.
Look for red square → potential SHORT entry: signals multi-timeframe overbought condition.
Combine with trend analysis, price action, or other confirmation for optimal entries.
📝 Notes:
The plotted stochastic lines are visually shifted (offset) for clarity; signals are computed from raw, unshifted values.
Designed for traders who prefer confluence across different stochastic lookback periods to improve confidence.
👉 Ideal for scalping, swing trading, or as a momentum filter in broader strategies.
Stochastic w/ Crossovers and Deadspace FilterThis is my extremely useful modification of the classic Stochastic indicator. It includes clear signals of crossovers and crossunders of the K/D lines.
Additionally, I added a "deadspace" filter to remove plotting of signals in the middle of the range, which tend to be misleading.
This can be incredibly useful to find entries and trends, especially when using 2 instances of this indicator at different lengths (such as one of 14,1,3 and another of 28,3,6).
The deadspace filter works based on the middle line, so a value of 20 will not plot any crossovers between 30-70.
EXODUS EXODUS by (DAFE) Trading Systems
EXODUS is a sophisticated trading algorithm built by Dskyz (DAFE) Trading Systems for competitive and competition purposes, designed to identify high-probability trades with robust risk management. this strategy leverages a multi-signal voting system, combining three core components—SPR, VWMO, and VEI—alongside ADX, choppiness filters, and ATR-based volatility gates to ensure trades are taken only in favorable market conditions. the algo uses a take-profit to stop-loss ratio, dynamic position sizing, and a strict voting mechanism requiring all signals to align before entering a trade.
EXODUS was not overfitted for any specific symbol. instead, it uses a generic tuned setting, making it versatile across various markets. while it can trade futures, it’s not currently set up for it but has the potential to do more with further development. visuals are intentionally minimal due to its competition focus, prioritizing performance over aesthetics. a more visually stunning version may be released in the future with enhanced graphics.
The Unique Core Components Developed for EXODUS
SPR (Session Price Recalibration)
SPR measures momentum during regular trading hours (RTH, 0930-1600, America/New_York) to catch session-specific trends.
spr_lookback = input.int(15, "SPR Lookback") this sets how many bars back SPR looks to calculate momentum (default 15 bars). it compares the current session’s price-volume score to the score 15 bars ago to gauge momentum strength.
how it works: a longer lookback smooths out the signal, focusing on bigger trends. a shorter one makes SPR more sensitive to recent moves.
how to adjust: on a 1-hour chart, 15 bars is 15 hours (about 2 trading days). if you’re on a shorter timeframe like 5 minutes, 15 bars is just 75 minutes, so you might want to increase it to 50 or 100 to capture more meaningful trends. if you’re trading a choppy stock, a shorter lookback (like 5) can help catch quick moves, but it might give more false signals.
spr_threshold = input.float (0.7, "SPR Threshold")
this is the cutoff for SPR to vote for a trade (default 0.7). if SPR’s normalized value is above 0.7, it votes for a long; below -0.7, it votes for a short.
how it works: SPR normalizes its momentum score by ATR, so this threshold ensures only strong moves count. a higher threshold means fewer trades but higher conviction.
how to adjust: if you’re getting too few trades, lower it to 0.5 to let more signals through. if you’re seeing too many false entries, raise it to 1.0 for stricter filtering. test on your chart to find a balance.
spr_atr_length = input.int(21, "SPR ATR Length") this sets the ATR period (default 21 bars) used to normalize SPR’s momentum score. ATR measures volatility, so this makes SPR’s signal relative to market conditions.
how it works: a longer ATR period (like 21) smooths out volatility, making SPR less jumpy. a shorter one makes it more reactive.
how to adjust: if you’re trading a volatile stock like TSLA, a longer period (30 or 50) can help avoid noise. for a calmer stock, try 10 to make SPR more responsive. match this to your timeframe—shorter timeframes might need a shorter ATR.
rth_session = input.session("0930-1600","SPR: RTH Sess.") rth_timezone = "America/New_York" this defines the session SPR uses (0930-1600, New York time). SPR only calculates momentum during these hours to focus on RTH activity.
how it works: it ignores pre-market or after-hours noise, ensuring SPR captures the main market action.
how to adjust: if you trade a different session (like London hours, 0300-1200 EST), change the session to match. you can also adjust the timezone if you’re in a different region, like "Europe/London". just make sure your chart’s timezone aligns with this setting.
VWMO (Volume-Weighted Momentum Oscillator)
VWMO measures momentum weighted by volume to spot sustained, high-conviction moves.
vwmo_momlen = input.int(21, "VWMO Momentum Length") this sets how many bars back VWMO looks to calculate price momentum (default 21 bars). it takes the price change (close minus close 21 bars ago).
how it works: a longer period captures bigger trends, while a shorter one reacts to recent swings.
how to adjust: on a daily chart, 21 bars is about a month—good for trend trading. on a 5-minute chart, it’s just 105 minutes, so you might bump it to 50 or 100 for more meaningful moves. if you want faster signals, drop it to 10, but expect more noise.
vwmo_volback = input.int(30, "VWMO Volume Lookback") this sets the period for calculating average volume (default 30 bars). VWMO weights momentum by volume divided by this average.
how it works: it compares current volume to the average to see if a move has strong participation. a longer lookback smooths the average, while a shorter one makes it more sensitive.
how to adjust: for stocks with spiky volume (like NVDA on earnings), a longer lookback (50 or 100) avoids overreacting to one-off spikes. for steady volume stocks, try 20. match this to your timeframe—shorter timeframes might need a shorter lookback.
vwmo_smooth = input.int(9, "VWMO Smoothing")
this sets the SMA period to smooth VWMO’s raw momentum (default 9 bars).
how it works: smoothing reduces noise in the signal, making VWMO more reliable for voting. a longer smoothing period cuts more noise but adds lag.
how to adjust: if VWMO is too jumpy (lots of false votes), increase to 15. if it’s too slow and missing trades, drop to 5. test on your chart to see what keeps the signal clean but responsive.
vwmo_threshold = input.float(10, "VWMO Threshold") this is the cutoff for VWMO to vote for a trade (default 10). above 10, it votes for a long; below -10, a short.
how it works: it ensures only strong momentum signals count. a higher threshold means fewer but stronger trades.
how to adjust: if you want more trades, lower it to 5. if you’re getting too many weak signals, raise it to 15. this depends on your market—volatile stocks might need a higher threshold to filter noise.
VEI (Velocity Efficiency Index)
VEI measures market efficiency and velocity to filter out choppy moves and focus on strong trends.
vei_eflen = input.int(14, "VEI Efficiency Smoothing") this sets the EMA period for smoothing VEI’s efficiency calc (bar range / volume, default 14 bars).
how it works: efficiency is how much price moves per unit of volume. smoothing it with an EMA reduces noise, focusing on consistent efficiency. a longer period smooths more but adds lag.
how to adjust: for choppy markets, increase to 20 to filter out noise. for faster markets, drop to 10 for quicker signals. this should match your timeframe—shorter timeframes might need a shorter period.
vei_momlen = input.int(8, "VEI Momentum Length") this sets how many bars back VEI looks to calculate momentum in efficiency (default 8 bars).
how it works: it measures the change in smoothed efficiency over 8 bars, then adjusts for inertia (volume-to-range). a longer period captures bigger shifts, while a shorter one reacts faster.
how to adjust: if VEI is missing quick reversals, drop to 5. if it’s too noisy, raise to 12. test on your chart to see what catches the right moves without too many false signals.
vei_threshold = input.float(4.5, "VEI Threshold") this is the cutoff for VEI to vote for a trade (default 4.5). above 4.5, it votes for a long; below -4.5, a short.
how it works: it ensures only strong, efficient moves count. a higher threshold means fewer trades but higher quality.
how to adjust: if you’re not getting enough trades, lower to 3. if you’re seeing too many false entries, raise to 6. this depends on your market—fast stocks like NQ1 might need a lower threshold.
Features
Multi-Signal Voting: requires all three signals (SPR, VWMO, VEI) to align for a trade, ensuring high-probability setups.
Risk Management: uses ATR-based stops (2.1x) and take-profits (4.1x), with dynamic position sizing based on a risk percentage (default 0.4%).
Market Filters: ADX (default 27) ensures trending conditions, choppiness index (default 54.5) avoids sideways markets, and ATR expansion (default 1.12) confirms volatility.
Dashboard: provides real-time stats like SPR, VWMO, VEI values, net P/L, win rate, and streak, with a clean, functional design.
Visuals
EXODUS prioritizes performance over visuals, as it was built for competitive and competition purposes. entry/exit signals are marked with simple labels and shapes, and a basic heatmap highlights market regimes. a more visually stunning update may be released later, with enhanced graphics and overlays.
Usage
EXODUS is designed for stocks and ETFs but can be adapted for futures with adjustments. it performs best in trending markets with sufficient volatility, as confirmed by its generic tuning across symbols like TSLA, AMD, NVDA, and NQ1. adjust inputs like SPR threshold, VWMO smoothing, or VEI momentum length to suit specific assets or timeframes.
Setting I used: (Again, these are a generic setting, each security needs to be fine tuned)
SPR LB = 19 SPR TH = 0.5 SPR ATR L= 21 SPR RTH Sess: 9:30 – 16:00
VWMO L = 21 VWMO LB = 18 VWMO S = 6 VWMO T = 8
VEI ES = 14 VEI ML = 21 VEI T = 4
R % = 0.4
ATR L = 21 ATR M (S) =1.1 TP Multi = 2.1 ATR min mult = 0.8 ATR Expansion = 1.02
ADX L = 21 Min ADX = 25
Choppiness Index = 14 Chop. Max T = 55.5
Backtesting: TSLA
Frame: Jan 02, 2018, 08:00 — May 01, 2025, 09:00
Slippage: 3
Commission .01
Disclaimer
this strategy is for educational purposes. past performance is not indicative of future results. trading involves significant risk, and you should only trade with capital you can afford to lose. always backtest and validate any strategy before using it in live markets.
(This publishing will most likely be taken down do to some miscellaneous rule about properly displaying charting symbols, or whatever. Once I've identified what part of the publishing they want to pick on, I'll adjust and repost.)
About the Author
Dskyz (DAFE) Trading Systems is dedicated to building high-performance trading algorithms. EXODUS is a product of rigorous research and development, aimed at delivering consistent, and data-driven trading solutions.
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
2025 Created by Dskyz, powered by DAFE Trading Systems. Trade smart, trade bold.
ATR Strength Index~~~~~~~ATRRSI~~~~~~~~~
Understanding the ATR Strength IndexThe "ATR Strength Index" (ATR SI) is a custom technical indicator derived by applying the calculation methodology of the Relative Strength Index (RSI) to the values of the Average True Range (ATR).
While the standard RSI measures the momentum of price changes, the ATR SI measures the momentum of volatility itself, as represented by the ATR.It is important to note that this is not a standard, widely recognised indicator like the traditional RSI or ATR.
It's a custom construction designed to provide a different perspective on market dynamics – specifically, the speed and magnitude of changes in volatility.
How it is Calculated
The calculation of the ATR Strength Index follows the same steps as the standard RSI, but the input data is the ATR value for each period, rather than the price.Let ATRi be the Average True Range value for the current period i.Let ATRi−1 be the Average True Range value for the previous period i−1.Calculate the period-over-period change in ATR:ΔATRi=ATRi−ATRi−1Separate ATR Gains and ATR Losses:If ΔATRi>0, then ATR,Gaini=ΔATRi and ATR,Lossi=0.If ΔATRi<0, then ATR,Gaini=0 and ATR,Lossi=∣ΔATRi∣.If ΔATRi=0, then ATR,Gaini=0 and ATR,Lossi=0.Calculate the Smoothed Average ATR Gain and Average ATR Loss over a specified lookback period (let's call this the "RSI Length" or n).
This typically uses a smoothing method similar to Wilder's original RSI calculation (a modified moving average or exponential moving average).Average,ATR,Gainn=Smoothed Average of ATR,Gain over n periodsAverage,ATR,Lossn=Smoothed Average of ATR,Loss over n periodsCalculate the ATR Relative Strength (ATR RS):ATR,RSn=Average,ATR,LossnAverage,ATR,GainnCalculate the ATR Strength Index:ATR,SIn=100−1+ATR,RSn100The resulting index oscillates between 0 and 100, just like the standard RSI.
How to Use It
Interpreting the ATR Strength Index focuses on the momentum of volatility rather than price momentum:High Values (e.g., above 70): Indicate that volatility (as measured by ATR) has been increasing rapidly over the chosen period.
This could suggest a market transitioning from a period of low volatility to high volatility, potentially preceding or accompanying strong directional price moves or increased choppiness.Low Values (e.g., below 30): Indicate that volatility has been decreasing rapidly.
This could suggest a market transitioning from high volatility to low volatility, potentially entering a period of consolidation or ranging price action.Midline (50): Represents a balance between increasing and decreasing volatility momentum.Divergence: You could potentially look for divergence between the ATR value itself and the ATR Strength Index. For example, if ATR is making higher highs but the ATR SI is making lower highs, it might suggest that while volatility is still increasing, the speed of that increase is slowing down. The interpretation and reliability of such divergence would need careful testing.
This indicator is best used as a supplementary tool to gain insight into the underlying volatility dynamics of the market, rather than as a primary signal generator for price direction.
It can help in understanding the current market environment – whether volatility is picking up or dying down – which can inform the suitability of different trading strategies (e.g., trend-following strategies might be more effective when volatility momentum is high, while range-bound strategies might suit periods of low volatility momentum).
Uniqueness
The ATR Strength Index is unique because it applies a momentum oscillator's logic (RSI) to a volatility indicator's output (ATR).Standard RSI: Focuses on the directional force of price movements.Standard ATR: Measures the amount of volatility, regardless of direction.ATR Strength Index: Measures the speed and direction of change in volatility.
It provides a perspective that neither the standard RSI nor ATR offers on their own – a quantified measure of how quickly the market's choppiness or range is expanding or contracting. This can be valuable for traders who incorporate volatility analysis into their decision-making process.In summary, the ATR Strength Index is a custom indicator that adapts the RSI calculation to measure the momentum of volatility, offering a unique view on market dynamics by showing how rapidly volatility is increasing or decreasing.
ADX Full [Titans_Invest]ADX Full
This is, without a doubt, the most complete ADX indicator available on TradingView — and quite possibly the most advanced in the world. We took the classic ADX structure and fully optimized it, preserving its essence while elevating its functionality to a whole new level. Every aspect has been enhanced — from internal logic to full visual customization. Now you can see exactly what’s happening inside the indicator in real time, with tags, flags, and informative levels. This indicator includes over 22 long entry conditions and 22 short entry conditions , covering absolutely every possibility the ADX can offer. Everything is transparent, adjustable, and ready to fit seamlessly into any professional trading strategy. This isn’t just another ADX — it’s the definitive ADX, built for traders who take the market seriously.
⯁ WHAT IS THE ADX❓
The Average Directional Index (ADX) is a technical analysis indicator developed by J. Welles Wilder. It measures the strength of a trend in a market, regardless of whether the trend is up or down.
The ADX is an integral part of the Directional Movement System, which also includes the Plus Directional Indicator (+DI) and the Minus Directional Indicator (-DI). By combining these components, the ADX provides a comprehensive view of market trend strength.
⯁ HOW TO USE THE ADX❓
The ADX is calculated based on the moving average of the price range expansion over a specified period (usually 14 periods). It is plotted on a scale from 0 to 100 and has three main zones:
Strong Trend: When the ADX is above 25, indicating a strong trend.
Weak Trend: When the ADX is below 20, indicating a weak or non-existent trend.
Neutral Zone: Between 20 and 25, where the trend strength is unclear.
⯁ ENTRY CONDITIONS
The conditions below are fully flexible and allow for complete customization of the signal.
______________________________________________________
🔹 CONDITIONS TO BUY 📈
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
🔹 +DI > -DI
🔹 +DI < -DI
🔹 +DI > ADX
🔹 +DI < ADX
🔹 -DI > ADX
🔹 -DI < ADX
🔹 ADX > Threshold
🔹 ADX < Threshold
🔹 +DI > Threshold
🔹 +DI < Threshold
🔹 -DI > Threshold
🔹 -DI < Threshold
🔹 +DI (Crossover) -DI
🔹 +DI (Crossunder) -DI
🔹 +DI (Crossover) ADX
🔹 +DI (Crossunder) ADX
🔹 +DI (Crossover) Threshold
🔹 +DI (Crossunder) Threshold
🔹 -DI (Crossover) ADX
🔹 -DI (Crossunder) ADX
🔹 -DI (Crossover) Threshold
🔹 -DI (Crossunder) Threshold
______________________________________________________
______________________________________________________
🔸 CONDITIONS TO SELL 📉
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
🔸 +DI > -DI
🔸 +DI < -DI
🔸 +DI > ADX
🔸 +DI < ADX
🔸 -DI > ADX
🔸 -DI < ADX
🔸 ADX > Threshold
🔸 ADX < Threshold
🔸 +DI > Threshold
🔸 +DI < Threshold
🔸 -DI > Threshold
🔸 -DI < Threshold
🔸 +DI (Crossover) -DI
🔸 +DI (Crossunder) -DI
🔸 +DI (Crossover) ADX
🔸 +DI (Crossunder) ADX
🔸 +DI (Crossover) Threshold
🔸 +DI (Crossunder) Threshold
🔸 -DI (Crossover) ADX
🔸 -DI (Crossunder) ADX
🔸 -DI (Crossover) Threshold
🔸 -DI (Crossunder) Threshold
______________________________________________________
______________________________________________________
🤖 AUTOMATION 🤖
• You can automate the BUY and SELL signals of this indicator.
______________________________________________________
______________________________________________________
⯁ UNIQUE FEATURES
______________________________________________________
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Plot Labels in the Graph Above: BUY/SELL
Automate and Monitor Signals/Alerts: BUY/SELL
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
______________________________________________________
📜 SCRIPT : ADX Full
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy!
______________________________________________________
o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
JuiceBox CRSI EnhancedJuiceBox “CRSI Enhanced” is a single-pane, zero-lag Connors RSI indicator supercharged with multi-theory lenses, Jurik smoothing, and multi-timeframe consensus.
1. Base Oscillator (JL-CRSI):
- Computes Connors RSI (3‐period price RSI, 2‐period streak RSI, 100-period percentile rank)
- Smooths it with a true Jurik Moving Average (configurable length & phase)
2. Sliding‐Window Divergence Filter:
- Detects classic price–indicator divergences over a recent look-back window
- Only lets signals fire when CRSI and price lows or highs diverge in the same direction
3. MTF Consensus (Ultra-product):
- For each lens, checks that at least 2 of {1m, 3m, 5m, 15m} agree on the same condition
- Ensures you see only the tightest, zero-lag multi-timeframe confirmation
4. Four “Lenses” (overlaid on the CRSI line):
Jerk (1ˢᵗ derivative) as a histogram, volume-weighted and ATR-scaled for adaptive sensitivity
Infinitesimal Divergence (2ⁿᵈ derivative) as a thin histogram, using a dynamic ε based on recent volatility
Zero-Cross markers (up/down labels) on the detrended CRSI midline, filtered by MTF consensus
Recurrence crosses, spotting 3-bar “W”/“M” micro-patterns that exceed a minimum amplitude and extend when volume surges
5. Classic RSI Reference Lines:
- 30, 50, 70 thresholds drawn with customizable solid, dashed or dotted styles
Fibonacci - RSI OscillatorIndicator Overview
The Fibonacci RSI Oscillator calculates the Relative Strength Index (RSI) based on a dynamically adjusting level derived from recent price action and a fixed Fibonacci ratio (0.236). This differs from standard RSI, which is calculated directly on the closing price. The objective is to measure momentum relative to a level that adapts to recent peaks and valleys.
Core Calculation Mechanism
Peak/Valley Tracking: The script identifies the highest high (state_peak) and lowest low (state_valley) since the last detected change in short-term directional bias (state_dir).
Dynamic Level Calculation: A level (state_dyn_level) is calculated using a fixed 0.236 Fibonacci ratio relative to the tracked peak and valley:
If bias is up: state_dyn_level = state_peak - (state_peak - state_valley) * 0.236
If bias is down: state_dyn_level = state_valley + (state_peak - state_valley) * 0.236
This level adjusts automatically when a new peak or valley is established in the current directional bias. If price crosses the dynamic level against the current bias, the bias flips, and the level recalculates.
Optional Source Smoothing: The calculated state_dyn_level can optionally be smoothed using a user-selected moving average (SMA, EMA, WMA, HMA, RMA) before the RSI calculation.
RSI Calculation: The standard RSI formula is applied to the (optionally smoothed) state_dyn_level series to produce the primary oscillator value (val_primary_osc).
Signal Line: A moving average (type and length configurable) is calculated on the val_primary_osc to generate the val_sig_line.
Key Features & Components
Dynamic Fibonacci Level: The core input for the RSI calculation, based on recent peaks/valleys and the 0.236 ratio.
Fibonacci Level RSI: The primary oscillator line representing the RSI of the dynamic level.
Signal Line: A moving average of the primary RSI line.
Overbought/Oversold Levels: User-defined threshold lines.
Optional Source Smoothing: Configurable MA smoothing applied to the dynamic level before RSI calculation.
Gradient RSI Color : Option to color the primary RSI line based on its value relative to OB/Mid/OS levels.
Zone & OB/OS Fills: Visual fills for the 0-50 / 50-100 zones and specific fills when the RSI enters OB/OS territory.
Background Gradient: Optional vertical background color gradient based on the RSI's position between 0 and 100.
Configurable Parameters: Inputs for lengths, MA types, OB/OS levels, colors, line widths, and feature toggles.
Visual Elements Explained
Fibonacci Level RSI Line: The main plotted oscillator (color/gradient/width configurable).
Signal Line: The moving average of the RSI line (color/width/MA type configurable).
OB/OS Lines: Horizontal lines plotted at the set OB/OS levels (color/width configurable).
Mid-Line (50): Horizontal line plotted at 50 (color/width configurable).
Zone Fills:
Background fill between 0-50 and 50-100 (colors configurable).
Conditional fill between the RSI line and the 50 line when RSI > OB level or RSI < OS level (colors configurable).
Background Gradient: Optional background coloring where transparency varies vertically with the RSI level (base colors and transparency range configurable).
Configuration Options
Users can adjust the following parameters in the indicator settings:
Smoothing: Enable/disable dynamic level smoothing; set length and MA type.
RSI: Set the RSI calculation length.
Signal Line: Set the signal line smoothing length and MA type.
Levels: Define Overbought and Oversold numeric thresholds.
Visuals: Configure colors and widths for the RSI line, signal line, OB/OS lines, mid-line, zone fills, and OB/OS fills.
Gradients: Enable/disable and configure colors for the RSI line gradient; enable/disable and configure colors/transparency for the background gradient.
Interpretation Notes
The oscillator reflects the momentum of the dynamic Fibonacci level, not directly the price. Divergences, OB/OS readings, and signal line crossovers should be interpreted in this context.
The behavior may differ from standard RSI, potentially offering a smoother output or highlighting different momentum patterns depending on market structure and volatility.
As with any indicator, signals should be used in conjunction with other analysis methods and risk management practices. It is not designed as a standalone trading system.
Risk Disclaimer:
Trading involves significant risk. This indicator is provided for analytical purposes only and does not constitute financial advice. Past performance is not indicative of future results. Use sound risk management practices and never trade with capital you cannot afford to lose.
Price OI Division Price OI Division Indicator
Overview
The Price OI Division indicator (`P_OI_D`) is a custom TradingView script designed to analyze the relationship between price momentum and open interest (OI) momentum. It visualizes the divergence between these two metrics using a modified MACD (Moving Average Convergence Divergence) approach, normalized to percentage values. The indicator is plotted as a histogram and two lines (MACD and Signal), with color-coded signals for easier interpretation.
Key Features
- Normalized Price MACD : Compares short-term and long-term price momentum.
- OI-Adjusted MACD : Incorporates open interest data to reflect market positioning.
- Divergence Histogram : Highlights the difference between price and OI momentum.
- Signal Line : Smoothed EMA of the divergence for trend confirmation.
- Threshold Lines : Horizontal reference lines at ±10% and 0 for quick visual analysis.
Interpretation Guide
- Bullish Signal :
Histogram turns red (positive & increasing).
MACD (red line) crosses above Signal (blue line).
Divergence above +10% indicates extreme bullish conditions.
- Bearish Signal :
Histogram turns green (negative & increasing).
MACD (lime line) crosses below Signal (maroon line).
Divergence below -10% indicates extreme bearish conditions.
- Neutral/Reversal :
Histogram fading (teal/pink) suggests weakening momentum.
Crossings near the Zero Line may signal trend shifts.
Usage Notes
Asset Compatibility : Works best with futures/perpetual contracts where OI data is available.
Timeframe : Suitable for all timeframes, but align `fastLength`/`slowLength` with your strategy.
Data Limitations : Relies on exchange-specific OI symbols (e.g., `BTC:USDT.P_OI`). Verify data availability for your asset.
Confirmation : Pair with volume analysis or support/resistance levels for higher accuracy.
Disclaimer
This indicator is for educational purposes only. Trading decisions should not be based solely on this tool. Always validate signals with additional analysis and risk management.
MTF Stochastic RSIOverview: MTF Stochastic RSI
is a momentum-tracking tool that plots the Stochastic RSI oscillator for up to four user-
defined timeframes on a single panel. It provides a compact yet powerful view of how
momentum is aligning or diverging across different timeframes, making it suitable for both
scalpers and swing traders looking for multi-timeframe confirmation.
What it does:
Calculates Stochastic RSI values using the RSI of price as the base input and applies
smoothing for stability.
Aggregates and displays the values for four customizable TF (e.g., 5min, 15min, 1h, 4h).
Highlights potential support and resistance zones in the oscillator space using adaptive zone
logic.
Optionally draws dynamic support/resistance zone lines in the oscillator space based on
historical turning points.
How it works:
Each timeframe uses the same RSI and Stoch calculation settings but runs independently via
the request.security() function.
Stochastic RSI is calculated by first applying the RSI to price, then applying a stochastic
formula on the RSI values, and finally smoothing the %K output.
Adaptive overbought and oversold thresholds adjust based on ATR-based volatility and simple
trend filtering (e.g., price vs EMA).
When a crossover above the oversold zone or a crossunder below the overbought zone
occurs, the script checks for proximity to previously stored zones and either adjusts or
records a new one.
These zones are stored and re-plotted as dotted support/resistance levels within the
oscillator space.
What it’s based on:
The indicator builds upon traditional Stochastic RSI by applying it to multiple timeframes in
parallel.
Zone detection logic is inspired by the idea of oscillator-based support/resistance levels.
Volatility-adjusted thresholds are based on ATR (Average True Range) to make the
overbought/oversold zones responsive to market conditions.
How to use it:
Look for alignment across timeframes (e.g., all four curves pushing into the overbought
region suggests strong trend continuation).
Reversal risk increases when one or more higher timeframes are diverging or showing signs of
cooling while lower timeframes are still extended.
Use the zone lines as soft support/resistance references within the oscillator—retests of
these zones can indicate strong reversal opportunities or continuation confirmation.
This script is provided for educational and informational purposes only. It does not constitute financial advice, trading recommendations, or an offer to buy or sell any financial instrument. Always perform your own due diligence, use proper risk management, and consult a qualified financial professional before making any trading decisions. Past performance does not guarantee future results. Use this tool at your own discretion and risk.
Power Law Global Liquidity Price Model & OscillatorDescription:
This Pine Script implements a predictive Bitcoin (BTC) price model derived from an observed power-law relationship between BTC price and Global Liquidity (specifically Global M2).
To clarify, the indicator doesn't show M2 directly as many indicators do, but uses an empirical observed relationship between BTC price and M2. This is an important difference from other Global Liquidity indicators and makes it very useful because it allows for making predictions on the future of Bitcoin price.
The model is based on the relationship BTC ~ GL^9.3, where GL represents Global M2, and the best correlation is achieved with an 85-period lead in GL, making it a leading indicator for BTC price movements. The observed correlation is higher than 0.92, giving high confidence in the model's validity. The 85-day lead was chosen by calculating the predictive rate of the model (how many times a positive/negative return in the model correlates with the price) with a given lead. The relationship between a chosen delay and predictive power has a maximum at 85 days.
Features:
BTC Price Model:
Calculates a BTC price model using the power-law relationship (BTC ~ GL^9.3) with an 85-period lead in Global Liquidity data.
The model is superimposed on the chart using forced overlay for clear visualization of the predicted BTC price trend relative to actual price.
Directional Oscillator:
Displayed in a lower panel, the oscillator compares the structural similarity between the actual BTC price and the GL-based price model.
Computes the win rate of the averaged BTC price (over a 1-year period) versus the price model to highlight structural alignment.
Projects future oscillator values based on the 85-period lead in the GL model, providing insight into potential price direction.
This feature is also very unique, and it is not present in most Global Liquidity indicators. The reason to choose the win rate is that this parameter doesn't depend on a precise scaling
between the BTC price and GL. This allows for better identification of changes in features between the 2 time series (for example, a downturn, a run up, peaks, bottoms, and similar).
Purpose:
This script serves as a predictive tool for traders and analysts by leveraging the leading relationship between Global Liquidity and BTC price. The overlay model and oscillator provide both a visual and quantitative framework to anticipate BTC price trends and assess structural alignment with global economic indicators.
The indicator allows for early identification of bottoms, peaks, and possible local bull or bear runs.
Usage Notes:
This indicator works best when used with the "All Time History" BTCUSD index.
The 85-period lead in GL allows for forward-looking projections, making this tool suitable for strategic planning.
The oscillator aids in confirming the structural validity of the model, enhancing confidence in its projections.