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.
M-oscillator
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.
Stablecoin Supply Ratio [Alpha Extract]Stablecoin Supply Ratio Indicator
The Stablecoin Supply Ratio (SSR) indicator compares Bitcoin's market capitalization to the aggregate supply of major stablecoins, offering insights into relative purchasing power and liquidity. This tool helps traders:
✔ Assess Bitcoin's buying power relative to the available stablecoin liquidity.
✔ Detect periods of capital inflow or outflow from stablecoins.
✔ Identify market sentiment shifts based on stablecoin reserves.
🔶 CALCULATION
The indicator aggregates the supply of key stablecoins and compares it to Bitcoin's market cap:
Stablecoin Aggregation
• Inputs:
USDT, USDC, DAI, USDD (daily closing values).
BUSD Market Cap (Glassnode data).
• Total Stablecoin Supply:
Sum of the listed stablecoins' market caps.
Stablecoin Supply Ratio (SSR)
• Formula:
SSR = Bitcoin Market Cap / Total Stablecoin Supply
• Normalized SSR:
Normalized by dividing SSR by its 200-day SMA.
Bollinger Bands
• Bands are applied to the normalized SSR using a configurable moving average type and 2 standard deviations.
Example Calculation:
ssr = btcmc / stablecoin_liq
ratio = ssr / ta.sma(ssr, 200)
basis = ta.sma(ratio, 200)
dev = 2 * ta.stdev(ratio, 200)
upper = basis + dev
lower = basis - dev
🔶 DETAILS
Visual Features:
• Normalized SSR:
Plotted as a light green line.
• Upper Band:
Red line indicating SSR overbought zone.
• Lower Band:
Green line signaling SSR oversold zone.
Interpretation:
• High SSR: Indicates stablecoin reserves are low relative to Bitcoin's market cap, reducing stablecoin buying power.
• Low SSR: Suggests high stablecoin liquidity relative to Bitcoin's market cap, increasing potential buying pressure.
• Band Crosses: Movements beyond the upper or lower bands may signal sentiment extremes.
🔶 EXAMPLES
Market insights include:
• Capital Outflows: SSR rising into the upper band may reflect decreasing stablecoin reserves, potentially signaling a liquidity drain.
• Capital Inflows: SSR dropping near the lower band could indicate growing stablecoin reserves, potentially fueling Bitcoin demand.
🔶 SETTINGS
Customization Options:
• MA Type: Choose between SMA, EMA, WMA, SMMA, and VWMA for band calculation.
• Period: Adjust the 200-day smoothing period.
• Deviation Multiplier: Modify the standard deviation multiplier (default: 2).
The Stablecoin Supply Ratio indicator is a valuable tool for traders monitoring liquidity dynamics and stablecoin trends to anticipate Bitcoin market moves and capital flows.
[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.
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.
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
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.
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
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🤖 AUTOMATION 🤖
• You can automate the BUY and SELL signals of this indicator.
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⯁ UNIQUE FEATURES
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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
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📜 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
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.
Dual-Phase Trend Regime Oscillator (Zeiierman)█ Overview
Trend Regime: Dual-Phase Oscillator (Zeiierman) is a volatility-sensitive trend classification tool that dynamically switches between two oscillators, one optimized for low volatility, the other for high volatility.
By analyzing standard deviation-based volatility states and applying correlation-derived oscillators, this indicator reveals not only whether the market is trending but also what kind of trend regime it is in —Bullish or Bearish —and how that regime reacts to market volatility.
█ Its Uniqueness
Most trend indicators assume a static market environment; they don't adjust their logic when the underlying volatility shifts. That often leads to false signals in choppy conditions or late entries in trending phases.
Trend Regime: Dual-Phase Oscillator solves this by introducing volatility-aware adaptability. It switches between a slow, stable oscillator in calm markets and a fast, reactive oscillator in volatile ones, ensuring the right sensitivity at the right time.
█ How It Works
⚪ Volatility State Engine
Calculates returns-based volatility using standard deviation of price change
Smooths the current volatility with a moving average
Builds a volatility history window and performs median clustering to determine typical "Low" and "High" volatility zones
Dynamically assigns the chart to one of two internal volatility regimes: Low or High
⚪ Dual Oscillators
In Low Volatility, it uses a Slow Trend Oscillator (longer lookback, smoother)
In High Volatility, it switches to a Fast Trend Oscillator (shorter lookback, responsive)
Both oscillators use price-time correlation as a measure of directional strength
The output is normalized between 0 and 1, allowing for consistent interpretation
⚪ Trend Regime Classification
The active oscillator is compared to a neutral threshold (0.5)
If above: Bullish Regime, if below: Bearish Regime, else: Neutral
The background and markers update to reflect regime changes visually
Triangle markers highlight bullish/bearish regime shifts
█ How to Use
⚪ Identify Current Trend Regime
Use the background color and chart table to immediately recognize whether the market is trending up or down.
⚪ Trade Regime Shifts
Use triangle markers (▲ / ▼) to spot fresh regime entries, which are ideal for confirming breakouts within trends.
⚪ Pullback Trading
Look for pullbacks when the trend is in a stable condition and the slow oscillator remains consistently near the upper or lower threshold. Watch for moments when the fast oscillator retraces back toward the midline, or slightly above/below it — this often signals a potential pullback entry in the direction of the prevailing trend.
█ Settings Explained
Length (Slow Trend Oscillator) – Used in calm conditions. Longer = smoother signals
Length (Fast Trend Oscillator) – Used in volatile conditions. Shorter = more responsive
Volatility Refit Interval – Controls how often the system recalculates Low/High volatility levels
Current Volatility Period – Lookback used for immediate volatility measurement
Volatility Smoothing Length – Applies an SMA to the raw volatility to reduce noise
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Trend Following Bundle [ActiveQuants]The Trend Following Bundle indicator is a comprehensive toolkit designed to equip traders with a suite of essential technical analysis tools focused on identifying , confirming , and capitalizing on market trends . By bundling popular indicators like Moving Averages , MACD , Supertrend , ADX , ATR , OBV , and the Choppiness Index into a single script, it streamlines chart analysis and enhances strategy development.
This bundle operates on the principle that combining signals from multiple, complementary indicators provides a more robust view of market trends than relying on a single tool. It integrates:
Trend Direction: Moving Averages, Supertrend.
Momentum: MACD.
Trend Strength: ADX.
Volume Pressure: On Balance Volume (OBV).
Volatility: Average True Range (ATR).
Market Condition Filter: Choppiness Index (Trend vs. Range).
By allowing users to selectively enable, customize, and view these indicators (potentially across different timeframes), the bundle facilitates nuanced and layered trend analysis.
█ KEY FEATURES
All-in-One Convenience: Access multiple core trend-following indicators within a single TradingView script slot.
Modular Design: Easily toggle each individual indicator (MAs, MACD, Supertrend, etc.) On or Off via the settings menu to customize your chart view.
Extensive Customization: Fine-tune parameters (lengths, sources, MA types, colors, etc.) for every included indicator to match your trading style and the specific asset.
Multi-Timeframe (MTF) Capability: Configure each indicator component to analyze data from a different timeframe than the chart's, allowing for higher-level trend context.
Integrated Alerts: Pre-built alert conditions for key events like Moving Average crossovers , MACD signals , Supertrend flips , and Choppiness Index threshold crosses . Easily set up alerts through TradingView's alert system.
When configuring your alerts in TradingView, pay close attention to the trigger option:
- Setting it to " Only Once " will trigger the alert the first time the condition is met, which might happen during an unclosed bar (intra-bar). This alert instance will then cease.
- Setting it to " Once Per Bar Close " will trigger the alert only after a bar closes if the condition was met on that finalized bar. This ensures signals are based on confirmed data and allows the alert to potentially trigger again on subsequent closing bars if the condition persists or reoccurs. Use this option for signals based on confirmed, closed-bar data.
MA Smoothing & Bands (Optional): Apply secondary smoothing or Bollinger Bands directly to the Fast and Slow Moving Averages for advanced analysis.
█ USER INPUTS
Fast MA:
On/Off: Enables/Disables the Fast Moving Average plot and related smoothing/bands.
Type: Selects the primary calculation type (SMA, EMA, SMMA (RMA), WMA, VWMA). Default: EMA.
Source: Input data for the MA calculation (e.g., close, open, hl2). Default: close.
Length: Lookback period for the primary MA calculation. Default: 9.
Color: Sets the color of the primary Fast MA line. Default: Yellow.
Line Width: Sets the thickness of the primary Fast MA line. Default: 2.
Smoothing Type: Selects secondary smoothing type applied to the primary MA (e.g., None, SMA, EMA) or adds Bollinger Bands (SMA + Bollinger Bands). Default: None.
Smoothing Length: Lookback period for the secondary smoothing MA or the basis MA for Bollinger Bands. Relevant only if Smoothing Type is not " None ". Default: 10.
BB StdDev: Standard deviation multiplier for Bollinger Bands. Relevant only if Smoothing Type is " SMA + Bollinger Bands ". Default: 2.0.
Timeframe: Sets a specific timeframe for the MA calculation. Default: Chart.
Wait TF Close: If a timeframe is set, waits for that timeframe's bar to close before plotting, preventing repainting. Default: true.
Slow MA:
On/Off: Enables/Disables the Slow Moving Average plot and related smoothing/bands.
Type: Selects the primary calculation type (SMA, EMA, SMMA (RMA), WMA, VWMA). Default: EMA.
Source: Input data for the MA calculation (e.g., close, open, hl2). Default: close.
Length: Lookback period for the primary MA calculation. Default: 9.
Color: Sets the color of the primary Slow MA line. Default: Yellow.
Line Width: Sets the thickness of the primary Slow MA line. Default: 2.
Smoothing Type: Selects secondary smoothing type applied to the primary MA (e.g., None, SMA, EMA) or adds Bollinger Bands (SMA + Bollinger Bands). Default: None.
Smoothing Length: Lookback period for the secondary smoothing MA or the basis MA for Bollinger Bands. Relevant only if Smoothing Type is not " None ". Default: 10.
BB StdDev: Standard deviation multiplier for Bollinger Bands. Relevant only if Smoothing Type is " SMA + Bollinger Bands ". Default: 2.0.
Timeframe: Sets a specific timeframe for the MA calculation. Default: Chart.
Wait TF Close: If a timeframe is set, waits for that timeframe's bar to close before plotting, preventing repainting. Default: true.
MACD:
On/Off: Enables/Disables the MACD plots (MACD line, Signal line, Histogram).
Fast Length: Lookback period for the fast MA in MACD calculation. Default: 12.
Slow Length: Lookback period for the slow MA in MACD calculation. Default: 26.
Source: Input data for the MACD MAs. Default: close.
Signal Smoothing: Lookback period for the Signal Line MA. Default: 9.
Oscillator MA Type: Calculation type for Fast and Slow MAs (SMA, EMA). Default: EMA.
Signal Line MA Type: Calculation type for Signal Line MA (SMA, EMA). Default: EMA.
MACD Color: Color of the MACD line. Default: #2962FF.
MACD Signal Color: Color of the Signal line. Default: #FF6D00.
Timeframe: Sets a specific timeframe for the MACD calculation. Default: Chart.
Wait TF Close: If a timeframe is set, waits for that timeframe's bar to close. Default: true.
On Balance Volume (OBV):
On/Off: Enables/Disables the OBV plot and its related MAs/Bands.
Type (MA Smoothing): Selects MA type for smoothing OBV (None, SMA, EMA, etc.) or SMA + Bollinger Bands. Default: None.
Length (MA Smoothing): Lookback period for the OBV smoothing MA. Default: 14.
BB StdDev: Standard deviation multiplier for Bollinger Bands if selected. Default: 2.0.
Color: Color of the main OBV line. Default: #2962FF.
Timeframe: Sets a specific timeframe for the OBV calculation. Default: Chart.
Wait TF Close: If a timeframe is set, waits for that timeframe's bar to close. Default: true.
ADX:
On/Off: Enables/Disables the ADX plot.
ADX Smoothing: Lookback period for the ADX smoothing component. Default: 14.
DI Length: Lookback period for the Directional Movement (+DI/-DI) calculation. Default: 14.
Color: Color of the ADX line. Default: Red.
Timeframe: Sets a specific timeframe for the ADX calculation. Default: Chart.
Wait TF Close: If a timeframe is set, waits for that timeframe's bar to close. Default: true.
ATR:
On/Off: Enables/Disables the ATR plot.
Length: Lookback period for the ATR calculation. Default: 14.
Smoothing: Selects the calculation type for ATR (SMMA (RMA), SMA, EMA, WMA). Default: SMMA (RMA).
Color: Color of the ATR line. Default: #B71C1C.
Timeframe: Sets a specific timeframe for the ATR calculation. Default: Chart.
Wait TF Close: If a timeframe is set, waits for that timeframe's bar to close. Default: true.
Supertrend:
On/Off: Enables/Disables the Supertrend plot and background fill.
ATR Length: Lookback period for the ATR calculation within Supertrend. Default: 10.
Factor: Multiplier for the ATR value used to calculate the Supertrend bands. Default: 3.0.
Up Trend Color: Color for the Supertrend line and background during an uptrend. Default: Green.
Down Trend Color: Color for the Supertrend line and background during a downtrend. Default: Red.
Timeframe: Sets a specific timeframe for the Supertrend calculation. Default: Chart.
Wait TF Close: If a timeframe is set, waits for that timeframe's bar to close. Default: true.
Choppiness Index:
On/Off: Enables/Disables the Choppiness Index plot and bands.
Length: Lookback period for the Choppiness Index calculation. Default: 14.
Offset: Shifts the plot left or right. Default: 0.
Color: Color of the Choppiness Index line. Default: #2962FF.
Timeframe: Sets a specific timeframe for the CI calculation. Default: Chart.
Wait TF Close: If a timeframe is set, waits for that timeframe's bar to close. Default: true.
█ STRATEGY EXAMPLES
The following strategy examples are provided for illustrative and educational purposes only to demonstrate how indicators within this bundle could be combined. They do not constitute financial advice or trading recommendations. Always conduct your own thorough research and backtesting before implementing any trading strategy.
Here are a few ways the indicators in this bundle can be combined:
1. MA Crossover with Multi-Factor Confirmation
Goal: Enter trends early with confirmation from momentum and trend strength, while filtering out choppy conditions.
Setup: Enable Fast MA (e.g., 9 EMA), Slow MA (e.g., 50 EMA), MACD, ADX, and Choppiness Index.
Entry (Long):
- Price > Slow MA (Establishes broader uptrend context).
- Fast MA crosses above Slow MA OR Price crosses above Fast MA.
- MACD Histogram > 0 (Confirms bullish momentum).
- ADX > 20 or 25 (Indicates sufficient trend strength).
- Choppiness Index < 61.8 (Filters out excessively choppy markets).
Entry (Short): Reverse logic (except for ADX and Choppiness Index).
Management: Consider using the Supertrend or an ATR multiple for stop-loss placement.
Image showing a chart with 2:1 long and short trades, highlighting a candle disqualified for a long entry due to ADX below 20.
2. Supertrend Breakout Strategy
Goal: Use Supertrend for primary signals and stops, confirming with volume and trend strength.
Setup: Enable Supertrend, Slow MA, ADX, and OBV.
Entry (Long):
- Supertrend line turns green and price closes above it.
- Price > Slow MA (Optional filter for alignment with larger trend).
- ADX is rising or above 20 (Confirms trending conditions).
- OBV is generally rising or breaks a recent resistance level (Confirms volume supporting the move).
Entry (Short): Reverse logic (except for ADX and OBV).
Management: Initial stop-loss placed just below the green Supertrend line (for longs) or above the red line (for shorts). Trail stop as Supertrend moves.
Image showing a chart with a 2:1 long trade, one candle disqualified for a short entry, and another disqualified for a long entry.
3. Trend Continuation Pullbacks
Goal: Enter established trends during pullbacks to value areas defined by MAs or Supertrend.
Setup: Enable Slow MA, Fast MA (or Supertrend), MACD, and ADX.
Entry (Long):
- Price is consistently above the Slow MA (Strong uptrend established).
- ADX > 25 (Confirms strong trend).
- Price pulls back towards the Fast MA or the green Supertrend line.
- MACD Histogram was decreasing during the pullback but turns positive again OR MACD line crosses above Signal line near the MA/Supertrend level (Indicates momentum resuming).
Entry (Short): Reverse logic (except for ADX) during a confirmed downtrend.
Management: Stop-loss below the recent swing low or the Slow MA/Supertrend level.
Image showing a chart with 2:1 long and short trades, where price pulls back to the fast MA and the MACD histogram changes color, indicating shifts in momentum during the pullbacks.
█ CONCLUSION
The Trend Following Bundle offers a powerful and flexible solution for traders focused on trend-based strategies. By consolidating essential indicators into one script with deep customization, multi-timeframe analysis, and built-in alerts, it simplifies the analytical workflow and allows for the development of robust, multi-conditional trading systems. Whether used for confirming entries, identifying trend strength, managing risk, or filtering market conditions, this bundle provides a versatile foundation for technical analysis.
█ IMPORTANT NOTES
⚠ Parameter Tuning: Indicator settings (lengths, factors, thresholds) are not one-size-fits-all. Adjust them based on the asset being traded, its typical volatility, and the timeframe you are analyzing for optimal performance. Backtesting is crucial .
⚠ Multi-Timeframe Use: Using the Timeframe input allows for powerful analysis but be mindful of potential lag, especially if Wait TF Close is disabled. Signals based on higher timeframes will update only when that higher timeframe bar closes (if Wait TF Close is enabled).
⚠ Confirmation is Key: While the bundle provides many tools, avoid relying on a single indicator's signal. Use combinations to build confluence and increase the probability of successful trades.
⚠ Chart Clarity: With many indicators available, only enable those relevant to your current strategy to avoid overwhelming your chart. Use the On/Off toggles frequently.
⚠ Confirmed Bars Only: Like most TradingView indicators, signals and plots are finalized on the close of the bar. Be cautious acting on intra-bar signals which may change before the bar closes.
█ RISK DISCLAIMER
Trading involves substantial risk of loss and is not suitable for every investor. The Trend Following Bundle indicator provides technical analysis tools for educational and informational purposes only; it does not constitute financial advice or a recommendation to buy or sell any asset. Indicator signals identify potential patterns based on historical data but do not guarantee future price movements or profitability. Always conduct your own thorough analysis, use multiple sources of information, and implement robust risk management practices before making any trading decisions. Past performance is not indicative of future results.
📊 Happy trading! 🚀
COT3 - Flip Strength Index - Invincible3This indicator uses the TradingView COT library to visualize institutional positioning and potential sentiment or trend shifts. It compares the long% vs short% of commercial and non-commercial traders for both Pair A and Pair B, helping traders identify trend strength, market overextension, and early reversal signals.
🔷 COT RSI
The COT RSI normalizes the net positioning difference between non-commercial and commercial traders over (N=13, 26, and 52)-week periods. It ranges from 0 to 100, highlighting when sentiment is at bullish or bearish extremes.
COT RSI (N)= ((NC - C)−min)/(max-min) x100
🟡 COT Index
The COT Index tracks where the current non-commercial net position lies within its 1-year and 3-year historical range. It reflects institutional accumulation or distribution phases.
Strength represents the magnitude of that positioning bias, visualized through normalized RSI-style metrics.
COT Index (N)= (NC net)/(max-min) x100
🔁 Flip Detection
Flip refers to the crossovers between long% and short%, indicating a change in directional bias among trader groups. When long positions exceed shorts (or vice versa), it signals a possible market flip in sentiment or trend.
For example, Pair B commercial flip is calculated as:
Long% = (Long/Open Interest)×100
Short% = (Short/Open Interest)×100
Flip = Long%−Short%
A bullish flip occurs when long% overtakes short%, and vice versa for a bearish flip. These flips often precede price trend changes or confirm sentiment breakouts.
Flip captures how far current positioning deviates from historical norms — highlighting periods of institutional overconfidence or exhaustion, often leading to significant market turns.
This combination offers a multi-layered edge for identifying when smart money is flipping direction, and whether that flip has strong conviction or is likely to fade.
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Schaff Trend Cycle (STC) - t0rdn3Schaff Trend Cycle (STC)
By t0rdn3 (original STC by , now with more descriptive naming)
Description
The Schaff Trend Cycle (STC) is a momentum-based oscillator that combines the speed of a fast EMA crossover with cyclical normalization. Developed by Doug Schaff, it identifies market turning points more responsively than MACD or RSI.
How It Works
1. EMA Difference : Calculates the difference between two EMAs of the source series (default: close).
2. Cycle Percentage : Normalizes that difference to a 0–100 range over the cycle period.
3. Smoothing : Applies exponential smoothing twice—first to the cycle percentage, then to its normalized cycles—to reduce noise.
4. Final STC Line : Produces a smoothed oscillator oscillating between 0 and 100.
Alerts
- "STC turned down above 75" : Fires once when STC makes a local peak above the upper threshold ( 75 ).
- "STC turned up below 25" : Fires once when STC makes a local trough below the lower threshold ( 25 ).
Inputs
Cycle Period : 12 — Lookback in bars for normalization
Fast EMA Length : 26 — Period of the fast EMA
Slow EMA Length : 50 — Period of the slow EMA
Smoothing Factor : 0.5 — Exponential smoothing coefficient (0–1)
Usage
Readings above 75 indicate an overbought cycle; readings below 25 indicate an oversold cycle. Crossings of the 50 midline can confirm trend direction:
- STC rising through 50 → bullish shift
- STC falling through 50 → bearish shift
Combine STC with price action or other trend filters to improve signal quality. You can adjust the cycle period and EMA lengths to match different timeframes or instruments.
Hippo Battlefield - Bulls VS Bears 20 bars## Hippo Battlefield – Bulls VS Bears (20 Bars)
**What it is**
A multi-dimensional momentum-and-sentiment oscillator that combines classic Bull/Bear Power with ATR- or peak-normalization, then layers on RSI and MACD-derived metrics into:
1. **A colored bar series** showing net Bull+Bear Power strength over the last 20 bars,
2. **A dynamic table** of each of those 20 BBP values (grouped into four 5-bar “quartals”), with symbols, per-bar change, and rolling averages, and
3. **A composite “Weighted BBP” histogram** blending normalized RSI, MACD, and BBP into a single view.
---
### Key Inputs
- **Length (EMA)** – look-back for the underlying EMA (default 60)
- **Normalization Length** – look-back window for peak-normalization (default 60)
- **Use ATR for Norm.** – toggle ATR-based normalization vs. highest-abs(BBP)
- **Show Tables** – toggle the bottom-right 21×11 grid of raw and average BBP values
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### What You See
#### 1. Colored Bars (Overlay = false)
- Bars are colored by normalized BBP intensity:
- Extreme Bull (≥+10): deep blue
- Strong Bull (+5 to +10): green/yellow
- Weak Bull (+0 to +5): dark green
- Weak Bear (–0 to –5): dark red
- Strong Bear (–5 to –10): pink/red
- Extreme Bear (<–10): magenta
#### 2. Bottom-Right Table (20 Bars of Data)
- Divided into four columns (0–4, 5–9, 10–14, 15–19 bars ago) and one “average” row.
- Each cell shows:
1. Bar index (1–20),
2. Normalized BBP value (to four decimals),
3. Direction symbol (↑/↓/=),
4. Bar-to-bar change (± value),
5. A separator “|”.
- At the very bottom, each column’s 5-bar average is displayed as “Avg: X.XXXX” with a dot marker.
#### 3. Top-Center Mini-Table
- When ≥20 bars have elapsed, shows the date at 20 bars ago and the average BBP across the full 20-bar window.
#### 4. Normalized RSI Line
- Rescales the classic 14-period RSI into a –20…+20 band to align with BBP.
#### 5. MACD Lines (Hidden) & Composite Histogram
- MACD and signal lines are calculated but not plotted by default.
- A “Weighted BBP” histogram combines:
- 20% normalized RSI,
- 20% average of (MACD + signal + normalized BBP),
- 60% normalized BBP
- Plotted as columns, color-coded by strength using the same palette as the main bars.
#### 6. Middle Reference Line
- A horizontal zero line to anchor over/under-zero readings.
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### How to Use It
- **Trend confirmation**: Strong blue/green bars alongside a rising histogram suggest bull conviction; strong reds/magentas signal bear dominance.
- **Divergence spotting**: Watch for price making new highs/lows while BBP or the histogram fails to follow.
- **Quartal analysis**: The 5-bar group averages can reveal whether recent momentum is accelerating or waning.
- **Cross-indicator weighting**: Because RSI, MACD, and raw BBP all feed into the final histogram, you get a smoothed, blended view of momentum shifts.
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**Tip:** Tweak the EMA and normalization length to suit your preferred timeframe (e.g. shorter for intraday scalps, longer for swing trades). Enable/disable the table if you prefer a cleaner pane.
Rate of Change HistogramExplanation of Modifications
Converting ROC to Histogram:
Original ROC: The ROC is calculated as roc = 100 * (source - source ) / source , plotted as a line oscillating around zero.
Modification: Instead of plotting roc as a line, it’s now plotted as a histogram using style=plot.style_columns. This makes the ROC values visually resemble the MACD histogram, with bars extending above or below the zero line based on momentum.
Applying MACD’s Four-Color Scheme:
Logic: The histogram’s color is determined by:
Above Zero (roc >= 0): Bright green (#26A69A) if ROC is rising (roc > roc ), light green (#B2DFDB) if falling (roc < roc ).
Below Zero (roc < 0): Bright red (#FF5252) if ROC is falling (roc < roc ), light red (#FFCDD2) if rising (roc > roc ).
Implementation: Used the exact color logic and hex codes from the MACD code, applied to the ROC histogram. This highlights momentum ebbs (falling ROC, fading waves) and flows (rising ROC, strengthening waves).
Removing Signal Line:
Unlike the previous attempt, no signal line is added. The histogram is purely the ROC value, ensuring it directly reflects price change momentum without additional smoothing, making it faster and more responsive to pulse waves, as you indicated ROC performs better than other oscillators.
Alert Conditions:
Added alerts to match the MACD’s logic, triggering when the ROC histogram crosses the zero line:
Rising to Falling: When roc >= 0 and roc < 0, signaling a potential wave peak (e.g., end of Wave 3 or C).
Falling to Rising: When roc <= 0 and roc > 0, indicating a potential wave bottom (e.g., start of Wave 1 or rebound).
These alerts help identify transitions in 3-4 wave pulse patterns.
Plotting:
Histogram: Plotted as columns (plot.style_columns) with the four-color scheme, directly representing ROC momentum.
Zero Line: Kept the gray zero line (#787B86) for reference, consistent with the MACD.
Removed ROC Line/Signal Line: Since you want the ROC to act as the histogram itself, no additional lines are plotted.
Inputs:
Retained the original length (default 9) and source (default close) inputs for consistency.
Removed signal-related inputs (e.g., signal_length, sma_signal) as they’re not needed for a pure ROC histogram.
How This ROC Histogram Works for Wave Pulses
Wave Alignment:
Above Zero (Bullish Momentum): Positive ROC bars indicate flows (e.g., impulse Waves 1, 3, or rebounds in Wave B/C). Bright green bars show accelerating momentum (strong pulses), while light green bars suggest fading momentum (potential wave tops).
Below Zero (Bearish Momentum): Negative ROC bars indicate ebbs (e.g., corrective Waves 2, 4, A, or C). Bright red bars show increasing bearish momentum (strong pullbacks), while light red bars suggest slowing declines (potential wave bottoms).
3-4 Wave Pulses:
In a 3-wave A-B-C correction: Wave A (down) shows bright red bars (falling ROC), Wave B (up) shows bright/light green bars (rising ROC), and Wave C (down) shifts back to red bars.
In a 4-wave consolidation: Alternating green/red bars highlight the rhythmic ebbs and flows as momentum oscillates.
Timing:
Zero-line crossovers mark wave transitions (e.g., from Wave 2 to Wave 3).
Color changes (e.g., bright to light green) signal momentum shifts within waves, helping identify pulse peaks/troughs.
Advantages Over MACD:
The ROC histogram is more responsive than the MACD histogram because ROC directly measures price change percentage, while MACD relies on moving average differences, which introduce lag. This makes the ROC histogram better for capturing rapid 3-4 wave pulses, as you noted.
Example Usage
For a stock with 3-4 wave pulses on a 5-minute chart:
Wave 1 (Flow): ROC rises above zero, histogram turns bright green (rising momentum), indicating a strong bullish pulse.
Wave 2 (Ebb): ROC falls below zero, histogram shifts to bright red (falling momentum), signaling a corrective pullback.
Wave 3 (Flow): ROC crosses back above zero, histogram becomes bright green again, confirming a powerful pulse.
Wave 4 (Ebb): ROC dips slightly, histogram turns light green (falling momentum above zero) or light red (rising momentum below zero), indicating consolidation.
Alerts trigger on zero-line crosses (e.g., from Wave 2 to Wave 3), helping time trades.
Settings Recommendations
Default (length=9): Works well for most time frames, balancing sensitivity and smoothness.
Intraday Pulses: Use length=5 or length=7 for faster signals on 5-minute or 15-minute charts.
Daily Charts: Try length=12 or length=14 for broader wave cycles.
Testing: Apply to a stock with clear wave patterns (e.g., tech stocks like AAPL or TSLA) and adjust length to match the pulse frequency you observe.
Notes
Confirmation: Pair the ROC histogram with price action (e.g., Fibonacci retracements, support/resistance) to validate wave counts, as momentum oscillators can be noisy in choppy markets.
Divergences: Watch for divergences (e.g., price makes a higher high, but ROC histogram bars are lower) to spot wave reversals, especially at Wave 3 or C ends.
Comparison to MACD: The ROC histogram is faster and more direct, making it ideal for short-term pulse waves, but it may be more volatile, so use with technical levels for precision.
Gold/Silver RatioOverview
This indicator displays the Gold/Silver Ratio by dividing the price of gold (XAUUSD) by the price of silver (XAGUSD) on the same timeframe. It is a widely used tool in macroeconomic and precious metals analysis, helping traders and investors evaluate the relative value of gold compared to silver.
📈 What it does
Plots the ratio between gold and silver prices as a line on the chart.
Displays two key horizontal levels:
Overbought level at 90 (dashed red line).
Oversold level at 70 (dashed green line).
Highlights the chart background to show extreme conditions:
Red shading when the ratio exceeds 90 (gold is likely overvalued relative to silver).
Green shading when the ratio drops below 70 (silver is likely overvalued relative to gold).
🧠 How to Use
When the ratio exceeds 90, it suggests that gold may be overbought or silver may be undervalued. Historically, these have been good times to consider shifting exposure from gold to silver.
When the ratio falls below 70, it may indicate silver is overbought or gold is undervalued.
This tool is best used in conjunction with technical analysis, macroeconomic trends, or RSI/Bollinger Bands applied to the ratio.
⚙️ Inputs
This version of the script uses OANDA's XAUUSD and XAGUSD pairs for spot gold and silver prices. You may edit the request.security() calls to change data sources (e.g., FXCM, FOREXCOM, or CFD tickers from your broker).
✅ Best For:
Macro traders
Commodity investors
Ratio and spread traders
Long-term portfolio reallocators
RSI Full Forecast [Titans_Invest]RSI Full Forecast
Get ready to experience the ultimate evolution of RSI-based indicators – the RSI Full Forecast, a boosted and even smarter version of the already powerful: RSI Forecast
Now featuring over 40 additional entry conditions (forecasts), this indicator redefines the way you view the market.
AI-Powered RSI Forecasting:
Using advanced linear regression with the least squares method – a solid foundation for machine learning - the RSI Full Forecast enables you to predict future RSI behavior with impressive accuracy.
But that’s not all: this new version also lets you monitor future crossovers between the RSI and the MA RSI, delivering early and strategic signals that go far beyond traditional analysis.
You’ll be able to monitor future crossovers up to 20 bars ahead, giving you an even broader and more precise view of market movements.
See the Future, Now:
• Track upcoming RSI & RSI MA crossovers in advance.
• Identify potential reversal zones before price reacts.
• Uncover statistical behavior patterns that would normally go unnoticed.
40+ Intelligent Conditions:
The new layer of conditions is designed to detect multiple high-probability scenarios based on historical patterns and predictive modeling. Each additional forecast is a window into the price's future, powered by robust mathematics and advanced algorithmic logic.
Full Customization:
All parameters can be tailored to fit your strategy – from smoothing periods to prediction sensitivity. You have complete control to turn raw data into smart decisions.
Innovative, Accurate, Unique:
This isn’t just an upgrade. It’s a quantum leap in technical analysis.
RSI Full Forecast is the first of its kind: an indicator that blends statistical analysis, machine learning, and visual design to create a true real-time predictive system.
⯁ SCIENTIFIC BASIS LINEAR REGRESSION
Linear Regression is a fundamental method of statistics and machine learning, used to model the relationship between a dependent variable y and one or more independent variables 𝑥.
The general formula for a simple linear regression is given by:
y = β₀ + β₁x + ε
β₁ = Σ((xᵢ - x̄)(yᵢ - ȳ)) / Σ((xᵢ - x̄)²)
β₀ = ȳ - β₁x̄
Where:
y = is the predicted variable (e.g. future value of RSI)
x = is the explanatory variable (e.g. time or bar index)
β0 = is the intercept (value of 𝑦 when 𝑥 = 0)
𝛽1 = is the slope of the line (rate of change)
ε = is the random error term
The goal is to estimate the coefficients 𝛽0 and 𝛽1 so as to minimize the sum of the squared errors — the so-called Random Error Method Least Squares.
⯁ LEAST SQUARES ESTIMATION
To minimize the error between predicted and observed values, we use the following formulas:
β₁ = /
β₀ = ȳ - β₁x̄
Where:
∑ = sum
x̄ = mean of x
ȳ = mean of y
x_i, y_i = individual values of the variables.
Where:
x_i and y_i are the means of the independent and dependent variables, respectively.
i ranges from 1 to n, the number of observations.
These equations guarantee the best linear unbiased estimator, according to the Gauss-Markov theorem, assuming homoscedasticity and linearity.
⯁ LINEAR REGRESSION IN MACHINE LEARNING
Linear regression is one of the cornerstones of supervised learning. Its simplicity and ability to generate accurate quantitative predictions make it essential in AI systems, predictive algorithms, time series analysis, and automated trading strategies.
By applying this model to the RSI, you are literally putting artificial intelligence at the heart of a classic indicator, bringing a new dimension to technical analysis.
⯁ VISUAL INTERPRETATION
Imagine an RSI time series like this:
Time →
RSI →
The regression line will smooth these values and extend them n periods into the future, creating a predicted trajectory based on the historical moment. This line becomes the predicted RSI, which can be crossed with the actual RSI to generate more intelligent signals.
⯁ SUMMARY OF SCIENTIFIC CONCEPTS USED
Linear Regression Models the relationship between variables using a straight line.
Least Squares Minimizes the sum of squared errors between prediction and reality.
Time Series Forecasting Estimates future values based on historical data.
Supervised Learning Trains models to predict outputs from known inputs.
Statistical Smoothing Reduces noise and reveals underlying trends.
⯁ WHY THIS INDICATOR IS REVOLUTIONARY
Scientifically-based: Based on statistical theory and mathematical inference.
Unprecedented: First public RSI with least squares predictive modeling.
Intelligent: Built with machine learning logic.
Practical: Generates forward-thinking signals.
Customizable: Flexible for any trading strategy.
⯁ CONCLUSION
By combining RSI with linear regression, this indicator allows a trader to predict market momentum, not just follow it.
RSI Full Forecast is not just an indicator — it is a scientific breakthrough in technical analysis technology.
⯁ Example of simple linear regression, which has one independent variable:
⯁ In linear regression, observations ( red ) are considered to be the result of random deviations ( green ) from an underlying relationship ( blue ) between a dependent variable ( y ) and an independent variable ( x ).
⯁ Visualizing heteroscedasticity in a scatterplot against 100 random fitted values using Matlab:
⯁ The data sets in the Anscombe's quartet are designed to have approximately the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but are graphically very different. This illustrates the pitfalls of relying solely on a fitted model to understand the relationship between variables.
⯁ The result of fitting a set of data points with a quadratic function:
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🔮 Linear Regression: PineScript Technical Parameters 🔮
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Forecast Types:
• Flat: Assumes prices will remain the same.
• Linreg: Makes a 'Linear Regression' forecast for n periods.
Technical Information:
ta.linreg (built-in function)
Linear regression curve. A line that best fits the specified prices over a user-defined time period. It is calculated using the least squares method. The result of this function is calculated using the formula: linreg = intercept + slope * (length - 1 - offset), where intercept and slope are the values calculated using the least squares method on the source series.
Syntax:
• Function: ta.linreg()
Parameters:
• source: Source price series.
• length: Number of bars (period).
• offset: Offset.
• return: Linear regression curve.
This function has been cleverly applied to the RSI, making it capable of projecting future values based on past statistical trends.
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⯁ WHAT IS THE RSI❓
The Relative Strength Index (RSI) is a technical analysis indicator developed by J. Welles Wilder. It measures the magnitude of recent price movements to evaluate overbought or oversold conditions in a market. The RSI is an oscillator that ranges from 0 to 100 and is commonly used to identify potential reversal points, as well as the strength of a trend.
⯁ HOW TO USE THE RSI❓
The RSI is calculated based on average gains and losses over a specified period (usually 14 periods). It is plotted on a scale from 0 to 100 and includes three main zones:
• Overbought: When the RSI is above 70, indicating that the asset may be overbought.
• Oversold: When the RSI is below 30, indicating that the asset may be oversold.
• Neutral Zone: Between 30 and 70, where there is no clear signal of overbought or oversold conditions.
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⯁ ENTRY CONDITIONS
The conditions below are fully flexible and allow for complete customization of the signal.
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🔹 CONDITIONS TO BUY 📈
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• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
📈 RSI Conditions:
🔹 RSI > Upper
🔹 RSI < Upper
🔹 RSI > Lower
🔹 RSI < Lower
🔹 RSI > Middle
🔹 RSI < Middle
🔹 RSI > MA
🔹 RSI < MA
📈 MA Conditions:
🔹 MA > Upper
🔹 MA < Upper
🔹 MA > Lower
🔹 MA < Lower
📈 Crossovers:
🔹 RSI (Crossover) Upper
🔹 RSI (Crossunder) Upper
🔹 RSI (Crossover) Lower
🔹 RSI (Crossunder) Lower
🔹 RSI (Crossover) Middle
🔹 RSI (Crossunder) Middle
🔹 RSI (Crossover) MA
🔹 RSI (Crossunder) MA
🔹 MA (Crossover) Upper
🔹 MA (Crossunder) Upper
🔹 MA (Crossover) Lower
🔹 MA (Crossunder) Lower
📈 RSI Divergences:
🔹 RSI Divergence Bull
🔹 RSI Divergence Bear
📈 RSI Forecast:
🔹 RSI (Crossover) MA Forecast
🔹 RSI (Crossunder) MA Forecast
🔹 RSI Forecast 1 > MA Forecast 1
🔹 RSI Forecast 1 < MA Forecast 1
🔹 RSI Forecast 2 > MA Forecast 2
🔹 RSI Forecast 2 < MA Forecast 2
🔹 RSI Forecast 3 > MA Forecast 3
🔹 RSI Forecast 3 < MA Forecast 3
🔹 RSI Forecast 4 > MA Forecast 4
🔹 RSI Forecast 4 < MA Forecast 4
🔹 RSI Forecast 5 > MA Forecast 5
🔹 RSI Forecast 5 < MA Forecast 5
🔹 RSI Forecast 6 > MA Forecast 6
🔹 RSI Forecast 6 < MA Forecast 6
🔹 RSI Forecast 7 > MA Forecast 7
🔹 RSI Forecast 7 < MA Forecast 7
🔹 RSI Forecast 8 > MA Forecast 8
🔹 RSI Forecast 8 < MA Forecast 8
🔹 RSI Forecast 9 > MA Forecast 9
🔹 RSI Forecast 9 < MA Forecast 9
🔹 RSI Forecast 10 > MA Forecast 10
🔹 RSI Forecast 10 < MA Forecast 10
🔹 RSI Forecast 11 > MA Forecast 11
🔹 RSI Forecast 11 < MA Forecast 11
🔹 RSI Forecast 12 > MA Forecast 12
🔹 RSI Forecast 12 < MA Forecast 12
🔹 RSI Forecast 13 > MA Forecast 13
🔹 RSI Forecast 13 < MA Forecast 13
🔹 RSI Forecast 14 > MA Forecast 14
🔹 RSI Forecast 14 < MA Forecast 14
🔹 RSI Forecast 15 > MA Forecast 15
🔹 RSI Forecast 15 < MA Forecast 15
🔹 RSI Forecast 16 > MA Forecast 16
🔹 RSI Forecast 16 < MA Forecast 16
🔹 RSI Forecast 17 > MA Forecast 17
🔹 RSI Forecast 17 < MA Forecast 17
🔹 RSI Forecast 18 > MA Forecast 18
🔹 RSI Forecast 18 < MA Forecast 18
🔹 RSI Forecast 19 > MA Forecast 19
🔹 RSI Forecast 19 < MA Forecast 19
🔹 RSI Forecast 20 > MA Forecast 20
🔹 RSI Forecast 20 < MA Forecast 20
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🔸 CONDITIONS TO SELL 📉
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• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
📉 RSI Conditions:
🔸 RSI > Upper
🔸 RSI < Upper
🔸 RSI > Lower
🔸 RSI < Lower
🔸 RSI > Middle
🔸 RSI < Middle
🔸 RSI > MA
🔸 RSI < MA
📉 MA Conditions:
🔸 MA > Upper
🔸 MA < Upper
🔸 MA > Lower
🔸 MA < Lower
📉 Crossovers:
🔸 RSI (Crossover) Upper
🔸 RSI (Crossunder) Upper
🔸 RSI (Crossover) Lower
🔸 RSI (Crossunder) Lower
🔸 RSI (Crossover) Middle
🔸 RSI (Crossunder) Middle
🔸 RSI (Crossover) MA
🔸 RSI (Crossunder) MA
🔸 MA (Crossover) Upper
🔸 MA (Crossunder) Upper
🔸 MA (Crossover) Lower
🔸 MA (Crossunder) Lower
📉 RSI Divergences:
🔸 RSI Divergence Bull
🔸 RSI Divergence Bear
📉 RSI Forecast:
🔸 RSI (Crossover) MA Forecast
🔸 RSI (Crossunder) MA Forecast
🔸 RSI Forecast 1 > MA Forecast 1
🔸 RSI Forecast 1 < MA Forecast 1
🔸 RSI Forecast 2 > MA Forecast 2
🔸 RSI Forecast 2 < MA Forecast 2
🔸 RSI Forecast 3 > MA Forecast 3
🔸 RSI Forecast 3 < MA Forecast 3
🔸 RSI Forecast 4 > MA Forecast 4
🔸 RSI Forecast 4 < MA Forecast 4
🔸 RSI Forecast 5 > MA Forecast 5
🔸 RSI Forecast 5 < MA Forecast 5
🔸 RSI Forecast 6 > MA Forecast 6
🔸 RSI Forecast 6 < MA Forecast 6
🔸 RSI Forecast 7 > MA Forecast 7
🔸 RSI Forecast 7 < MA Forecast 7
🔸 RSI Forecast 8 > MA Forecast 8
🔸 RSI Forecast 8 < MA Forecast 8
🔸 RSI Forecast 9 > MA Forecast 9
🔸 RSI Forecast 9 < MA Forecast 9
🔸 RSI Forecast 10 > MA Forecast 10
🔸 RSI Forecast 10 < MA Forecast 10
🔸 RSI Forecast 11 > MA Forecast 11
🔸 RSI Forecast 11 < MA Forecast 11
🔸 RSI Forecast 12 > MA Forecast 12
🔸 RSI Forecast 12 < MA Forecast 12
🔸 RSI Forecast 13 > MA Forecast 13
🔸 RSI Forecast 13 < MA Forecast 13
🔸 RSI Forecast 14 > MA Forecast 14
🔸 RSI Forecast 14 < MA Forecast 14
🔸 RSI Forecast 15 > MA Forecast 15
🔸 RSI Forecast 15 < MA Forecast 15
🔸 RSI Forecast 16 > MA Forecast 16
🔸 RSI Forecast 16 < MA Forecast 16
🔸 RSI Forecast 17 > MA Forecast 17
🔸 RSI Forecast 17 < MA Forecast 17
🔸 RSI Forecast 18 > MA Forecast 18
🔸 RSI Forecast 18 < MA Forecast 18
🔸 RSI Forecast 19 > MA Forecast 19
🔸 RSI Forecast 19 < MA Forecast 19
🔸 RSI Forecast 20 > MA Forecast 20
🔸 RSI Forecast 20 < MA Forecast 20
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🤖 AUTOMATION 🤖
• You can automate the BUY and SELL signals of this indicator.
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⯁ UNIQUE FEATURES
______________________________________________________
Linear Regression: (Forecast)
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
Linear Regression (Forecast)
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
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📜 SCRIPT : RSI Full Forecast
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy!
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o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
Future Candle Reversal Projection (Mastersinnifty)Overview
This tool identifies potential future market reversal zones by dynamically projecting pivot-based swing patterns forward in time. Unlike traditional ZigZag indicators that only reflect past movements, this indicator anticipates probable future turning points based on historical swing periodicity.
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Key Features
- Forward Projections: Calculates and projects future swing zones based on detected pivot distances.
- Customizable Detection: Adjust the ZigZag depth for different trading styles (scalping, swing, position).
- Dynamic Updates: Real-time recalibration as new pivots form.
- Clean Visual Markers: Projects reversal estimates as intuitive labels and dotted lines.
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How it Works
The indicator identifies significant swing highs and lows using a user-defined ZigZag depth setting. It measures the time (bars) and price characteristics of the latest swing movement. Using this pattern, it projects forward estimated reversal points at consistent intervals. Midpoint price levels between the last high and low are used for each future projection.
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Who Can Benefit
- Intraday and swing traders seeking advanced planning zones.
- Technical analysts relying on pattern periodicity.
- Traders who wish to combine projected reversal markers with their own risk management strategies.
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Disclaimer
This tool is an analytical and educational utility. It does not predict markets with certainty. Always combine it with your own analysis and risk management. Past behavior does not guarantee future results.
