Elite Energy Alpha MatrixThe Elite Energy Alpha Matrix indicator provides comprehensive analysis of the energy sector, focusing on the complex relationships between crude oil benchmarks, natural gas, energy-related ETFs, and the performance dynamics across various energy sub-sectors.
The indicator tracks multiple energy price data sources including WTI crude oil, Brent crude, natural gas, and oil ETFs, enabling detailed monitoring of price relationships and divergences within the energy complex.
Key analytical components include:
• Correlation analysis between major energy benchmarks
• Multi-timeframe examination of energy price relationships
• Sector rotation detection within energy sub-sectors including integrated oil majors, exploration and production companies, oilfield services, refiners, pipelines, and renewable energy
• Performance monitoring across different energy market segments
The indicator provides a structured framework for analyzing the internal dynamics of the energy sector, identifying periods of alignment or divergence between different energy price instruments, and monitoring relative performance across energy sub-sectors.
This approach enables users to assess the consistency of price movements across the energy complex and identify situations where different components of the energy market are exhibiting divergent behavior, which can provide insight into the underlying drivers affecting the sector.2.6s
볼래틸리티
ES-VIX Daily Price Bands - Inner bands (80% and 50%)ES-VIX Daily Price Bands
This indicator plots dynamic intraday price bands for ES futures based on real-time volatility levels measured by the VIX (CBOE Volatility Index). The bands evolve throughout the trading day, providing volatility-adjusted price targets.
Formulas:
Upper Band = Daily Low + (ES Price × VIX ÷ √252 ÷ 100)
Lower Band = Daily High - (ES Price × VIX ÷ √252 ÷ 100)
The calculation uses the square root of 252 (trading days per year) to convert annualized VIX volatility into an expected daily move, then scales it as a percentage adjustment from the current day's extremes.
Features:
Real-time band calculation that updates throughout the trading session
Upper band (green) extends from the current day's low
Lower band (red) contracts from the current day's high
Inner upper band (green) at 50% of expected move
Inner lower band (red) at 50% of expected move
Middle Inner upper band (green) at 80% of expected move
Middle Inner lower band (red) at 80% of expected move
Shaded zone between bands for visual clarity
Information table displaying:
Current ES price and VIX level
Running daily high and low
Current upper and lower band values
kira 3 mins scalp3-min Strict Scalping HA + PSAR + RSI + 1:2 RR
Purpose: 3-minute scalping using Heikin Ashi candles, Parabolic SAR, and RSI with strict entry rules and automatic 1:2 risk:reward.
Logic:
Entry: 3rd consecutive HA candle with no wick (bullish for buy, bearish for sell)
Filters:
Buy: PSAR below candle + RSI > 50
Sell: PSAR above candle + RSI < 50
SL & TP:
Buy SL: lowest low of last 3 candles
Buy TP: entry + 2×(entry−SL)
Sell SL: highest high of last 3 candles
Sell TP: entry − 2×(SL−entry)
Signals: Triangles plotted on chart; alerts available
Use: Apply on 3-min chart. Enter on 3rd candle meeting conditions; follow SL/TP for 1:2 RR.
ES-VIX Daily Price BandsES-VIX Daily Price Bands
This indicator plots dynamic intraday price bands for ES futures based on real-time volatility levels measured by the VIX (CBOE Volatility Index). The bands evolve throughout the trading day, providing volatility-adjusted price targets.
Formulas:
Upper Band = Daily Low + (ES Price × VIX ÷ √252 ÷ 100)
Lower Band = Daily High - (ES Price × VIX ÷ √252 ÷ 100)
The calculation uses the square root of 252 (trading days per year) to convert annualized VIX volatility into an expected daily move, then scales it as a percentage adjustment from the current day's extremes.
Features:
Real-time band calculation that updates throughout the trading session
Upper band (green) extends from the current day's low
Lower band (red) contracts from the current day's high
Shaded zone between bands for visual clarity
Information table displaying:
Current ES price and VIX level
Running daily high and low
Current upper and lower band values
Vibha Jha TQQQ Clean Buy/Sell📈 Vibha Jha TEQQ Hybrid Strategy — Buy/Sell Signals
This script replicates the high-performance buy/sell methodology of Vibha Jha, one of the top money-manager performers in the U.S. Investing Championship (USIC). Her hybrid system generated triple-digit returns in both 2020 and 2021, and strong follow-up performance in 2023–2024 through a strict, rules-based combination of:
✔ CANSLIM-style market leadership tracking
✔ Position-trading fundamentals
✔ Rules-based swing trading using TQQQ/QQQ
✔ Tight entries & disciplined sells
✔ Market-timed exposure based on follow-through days, 21-EMA, and distribution clusters
🚀 What This Indicator Does
This indicator plots clean BUY and SELL signals based on Vibha’s core rule set:
BUY Signals
Three consecutive higher highs AND higher lows (her famous “3-day up” rule)
Strong up-day with rising volume
Designed to catch early trend reversals and early-stage rally attempts
SELL Signals
Two closes below the 21-day EMA
Three consecutive down days
Distribution cluster (4+ distribution days in the last 6 bars)
Captures exhaustion, weakening trend, and institutional selling
🧠 Why This Works
Vibha’s system is built on the reality that:
🔹 Markets give early warning before reversing
🔹 Momentum shifts appear before fundamentals
🔹 Distribution clusters precede pullbacks
🔹 3-day up patterns often kick off powerful rallies
🔹 TQQQ/QQQ respond clearly to technical signals
This indicator applies those insights directly to your chart—stocks, crypto, indices, or leveraged ETFs.
LazyTradeLazyTrade is a clean, high-confidence trend-following indicator built on TradingView’s non-repainting SuperTrend V6 engine. It adds intelligent RSI confirmation, profit-tracking labels, trend-flip markers, and optional background shading to highlight momentum shifts. Designed for intraday and swing traders who want fast, reliable signals without chart clutter.
Features:
• Non-repainting Buy/Sell signals
• Smart RSI confirmation (Aggressive / Standard / Conservative)
• Auto P&L between opposite signals
• Trend-flip circles and transparent background zones
• Clean visual structure optimized for daily and leveraged ETF trading
A simple, intuitive tool that keeps you aligned with the dominant trend—no noise, no over-complication.
ES-VIX Daily Price Bands - Inner bandsES-VIX Daily Price Bands
This indicator plots dynamic intraday price bands for ES futures based on real-time volatility levels measured by the VIX (CBOE Volatility Index). The bands evolve throughout the trading day, providing volatility-adjusted price targets.
Formulas:
Upper Band = Daily Low + (ES Price × VIX ÷ √252 ÷ 100)
Lower Band = Daily High - (ES Price × VIX ÷ √252 ÷ 100)
The calculation uses the square root of 252 (trading days per year) to convert annualized VIX volatility into an expected daily move, then scales it as a percentage adjustment from the current day's extremes.
Features:
Real-time band calculation that updates throughout the trading session
Upper band (green) extends from the current day's low
Lower band (red) contracts from the current day's high
Inner upper band (green) at 50% of expected move
Inner lower band (red) at 50% of expected move
Shaded zone between bands for visual clarity
Information table displaying:
Current ES price and VIX level
Running daily high and low
Current upper and lower band values
Average True Range (ATR)Strategy Name: ATR Trend-Following System with Volatility Filter & Dynamic Risk Management
Short Name: ATR Pro Trend System
Current Version: 2025 Edition (fully tested and optimized)Core ConceptA clean, robust, and highly profitable trend-following strategy that only trades when three strict conditions are met simultaneously:Clear trend direction (price above/below EMA 50)
Confirmed trend strength and trailing stop (SuperTrend)
Sufficient market volatility (current ATR(14) > its 50-period average)
This combination ensures the strategy stays out of choppy, low-volatility ranges and only enters during high-probability, trending moves with real momentum.Key Features & ComponentsComponent
Function
Default Settings
EMA 50
Primary trend filter
50-period exponential
SuperTrend
Dynamic trailing stop + secondary trend confirmation
Period 10, Multiplier 3.0
ATR(14) with RMA
True volatility measurement (Wilder’s original method)
Length 14
50-period SMA of ATR
Volatility filter – only trade when current ATR > average ATR
Length 50
Background coloring
Visual position status: light green = long, light red = short, white = flat
–
Entry markers
Green/red triangles at the exact entry bar
–
Dynamic position sizing
Fixed-fractional risk: exactly 1% of equity per trade
1.00% risk
Stop distance
2.5 × ATR(14) – fully adaptive to current volatility
Multiplier 2.5
Entry RulesLong: Close > EMA 50 AND SuperTrend bullish AND ATR(14) > SMA(ATR,50)
Short: Close < EMA 50 AND SuperTrend bearish AND ATR(14) > SMA(ATR,50)
Exit RulesPosition is closed automatically when SuperTrend flips direction (acts as volatility-adjusted trailing stop).
Money ManagementRisk per trade: exactly 1% of current account equity
Position size is recalculated on every new entry based on current ATR
Automatically scales up in strong trends, scales down in low-volatility regimes
Performance Highlights (2015–Nov 2025, real backtests)CAGR: 22–50% depending on market
Max Drawdown: 18–28%
Profit Factor: 1.89–2.44
Win Rate: 57–62%
Average holding time: 10–25 days (daily timeframe)
Best Markets & TimeframesExcellent on: Bitcoin, S&P 500, Nasdaq-100, DAX, Gold, major Forex pairs
Recommended timeframes: 4H, Daily, Weekly (Daily is the sweet spot)
NQ-VIX Expected Move LTF LevelsNQ -VIX LTF Price Bands
This indicator plots dynamic intraday price bands for NQ futures based on real-time volatility levels measured by the VIX (CBOE Volatility Index). The bands evolve throughout the trading day, providing volatility-adjusted price targets.
Formulas:
Upper Band = (Input TF Open) + (NQ Price × VIX x √(Input TF ÷ (23h in min) ) ÷ 100
Lower Band = Daily Open - (NQ Price × VIX x √(Input TF ÷ (23h in min) ) ÷ 100
The calculation uses the square root of Input TF ÷ (23h in min) to convert annualized VIX volatility into an expected TF move, then scales it as a percentage adjustment from the current TF input's open.
Features:
Real-time band calculation that updates throughout the trading session
Upper band (green) extends from the current TF's open
Lower band (red) contracts from the current TF's open
Inner upper band (green) at 50% of expected move
Inner lower band (red) at 50% of expected move
Middle Inner upper band (green) at 80% of expected move
Middle Inner lower band (red) at 80% of expected move
Information table displaying:
Current input TF
Current NQ price and VIX level
Current input TF Open
Expected move
Fast Autocorrelation Estimator█ Overview:
The Fast ACF and PACF Estimation indicator efficiently calculates the autocorrelation function (ACF) and partial autocorrelation function (PACF) using an online implementation. It helps traders identify patterns and relationships in financial time series data, enabling them to optimize their trading strategies and make better-informed decisions in the markets.
█ Concepts:
Autocorrelation, also known as serial correlation, is the correlation of a signal with a delayed copy of itself as a function of delay.
This indicator displays autocorrelation based on lag number. The autocorrelation is not displayed based over time on the x-axis. It's based on the lag number which ranges from 1 to 30. The calculations can be done with "Log Returns", "Absolute Log Returns" or "Original Source" (the price of the asset displayed on the chart).
When calculating autocorrelation, the resulting value will range from +1 to -1, in line with the traditional correlation statistic. An autocorrelation of +1 represents a perfect correlation (an increase seen in one time series leads to a proportionate increase in the other time series). An autocorrelation of -1, on the other hand, represents a perfect inverse correlation (an increase seen in one time series results in a proportionate decrease in the other time series). Lag number indicates which historical data point is autocorrelated. For example, if lag 3 shows significant autocorrelation, it means current data is influenced by the data three bars ago.
The Fast Online Estimation of ACF and PACF Indicator is a powerful tool for analyzing the linear relationship between a time series and its lagged values in TradingView. The indicator implements an online estimation of the Autocorrelation Function (ACF) and the Partial Autocorrelation Function (PACF) up to 30 lags, providing a real-time assessment of the underlying dependencies in your time series data. The Autocorrelation Function (ACF) measures the linear relationship between a time series and its lagged values, capturing both direct and indirect dependencies. The Partial Autocorrelation Function (PACF) isolates the direct dependency between the time series and a specific lag while removing the effect of any indirect dependencies.
This distinction is crucial in understanding the underlying relationships in time series data and making more informed decisions based on those relationships. For example, let's consider a time series with three variables: A, B, and C. Suppose that A has a direct relationship with B, B has a direct relationship with C, but A and C do not have a direct relationship. The ACF between A and C will capture the indirect relationship between them through B, while the PACF will show no significant relationship between A and C, as it accounts for the indirect dependency through B. Meaning that when ACF is significant at for lag 5, the dependency detected could be caused by an observation that came in between, and PACF accounts for that. This indicator leverages the Fast Moments algorithm to efficiently calculate autocorrelations, making it ideal for analyzing large datasets or real-time data streams. By using the Fast Moments algorithm, the indicator can quickly update ACF and PACF values as new data points arrive, reducing the computational load and ensuring timely analysis. The PACF is derived from the ACF using the Durbin-Levinson algorithm, which helps in isolating the direct dependency between a time series and its lagged values, excluding the influence of other intermediate lags.
█ How to Use the Indicator:
Interpreting autocorrelation values can provide valuable insights into the market behavior and potential trading strategies.
When applying autocorrelation to log returns, and a specific lag shows a high positive autocorrelation, it suggests that the time series tends to move in the same direction over that lag period. In this case, a trader might consider using a momentum-based strategy to capitalize on the continuation of the current trend. On the other hand, if a specific lag shows a high negative autocorrelation, it indicates that the time series tends to reverse its direction over that lag period. In this situation, a trader might consider using a mean-reversion strategy to take advantage of the expected reversal in the market.
ACF of log returns:
Absolute returns are often used to as a measure of volatility. There is usually significant positive autocorrelation in absolute returns. We will often see an exponential decay of autocorrelation in volatility. This means that current volatility is dependent on historical volatility and the effect slowly dies off as the lag increases. This effect shows the property of "volatility clustering". Which means large changes tend to be followed by large changes, of either sign, and small changes tend to be followed by small changes.
ACF of absolute log returns:
Autocorrelation in price is always significantly positive and has an exponential decay. This predictably positive and relatively large value makes the autocorrelation of price (not returns) generally less useful.
ACF of price:
█ Significance:
The significance of a correlation metric tells us whether we should pay attention to it. In this script, we use 95% confidence interval bands that adjust to the size of the sample. If the observed correlation at a specific lag falls within the confidence interval, we consider it not significant and the data to be random or IID (identically and independently distributed). This means that we can't confidently say that the correlation reflects a real relationship, rather than just random chance. However, if the correlation is outside of the confidence interval, we can state with 95% confidence that there is an association between the lagged values. In other words, the correlation is likely to reflect a meaningful relationship between the variables, rather than a coincidence. A significant difference in either ACF or PACF can provide insights into the underlying structure of the time series data and suggest potential strategies for traders. By understanding these complex patterns, traders can better tailor their strategies to capitalize on the observed dependencies in the data, which can lead to improved decision-making in the financial markets.
Significant ACF but not significant PACF: This might indicate the presence of a moving average (MA) component in the time series. A moving average component is a pattern where the current value of the time series is influenced by a weighted average of past values. In this case, the ACF would show significant correlations over several lags, while the PACF would show significance only at the first few lags and then quickly decay.
Significant PACF but not significant ACF: This might indicate the presence of an autoregressive (AR) component in the time series. An autoregressive component is a pattern where the current value of the time series is influenced by a linear combination of past values at specific lags.
Often we find both significant ACF and PACF, in that scenario simply and AR or MA model might not be sufficient and a more complex model such as ARMA or ARIMA can be used.
█ Features:
Source selection: User can choose either 'Log Returns' , 'Absolute Returns' or 'Original Source' for the input data.
Autocorrelation Selection: User can choose either 'ACF' or 'PACF' for the plot selection.
Plot Selection: User can choose either 'Autocorrelarrogram' or 'Historical Autocorrelation' for plotting the historical autocorrelation at a specified lag.
Max Lag: User can select the maximum number of lags to plot.
Precision: User can set the number of decimal points to display in the plot.
ES-VIX Expected Move - Open basedES-VIX Daily Price Bands
This indicator plots dynamic intraday price bands for ES futures based on real-time volatility levels measured by the VIX (CBOE Volatility Index). The bands evolve throughout the trading day, providing volatility-adjusted price targets.
Formulas:
Upper Band = Daily Open + (ES Price × VIX ÷ √252 ÷ 100)
Lower Band = Daily Open - (ES Price × VIX ÷ √252 ÷ 100)
The calculation uses the square root of 252 (trading days per year) to convert annualized VIX volatility into an expected daily move, then scales it as a percentage adjustment from the current day's open.
Features:
Real-time band calculation that updates throughout the trading session
Upper band (green) extends from the current day's open
Lower band (red) contracts from the current day's open
Inner upper band (green) at 50% of expected move
Inner lower band (red) at 50% of expected move
Middle Inner upper band (green) at 80% of expected move
Middle Inner lower band (red) at 80% of expected move
Information table displaying:
Current ES price and VIX level
Daily Open
Expected move
MFM – Light Context HUD (Minimal)Overview
MFM Light Context HUD is the free version of the Market Framework Model. It gives you a fast and clean view of the current market regime and phase without signals or chart noise. The HUD shows whether the asset is in a bullish or bearish environment and whether it is in a volatile, compression, drift, or neutral phase. This helps you read structure at a glance.
Asset availability
The free version works only on a selected list of five assets.
Supported symbols are
SP:SPX
TVC:GOLD
BINANCE:BTCUSD
BINANCE:ETHUSDT
OANDA:EURUSD
All other assets show a context banner only.
How it works
The free version uses fixed settings based on the original MFM model. It calculates the regime using a higher timeframe RSI ratio and identifies the current phase using simplified momentum conditions. The chart stays clean. Only a small HUD appears in the top corner. Full visual phases, ratio logic, signals, and auto tune are part of the paid version.
The free version shows the phase name only. It does not display colored phase zones on the chart.
Phase meaning
The Market Framework Model uses four structural phases to describe how the market
behaves. These are not signals but context layers that show the underlying environment.
Volatile (Phase 1)
The market is in a fast, unstable or directional environment. Price can move aggressively with
stronger momentum swings.
Compression (Phase 2)
The market is in a contracting state. Momentum slows and volatility decreases. This phase
often appears before expansion, but it does not predict direction.
Drift (Phase 3)
The market moves in a more controlled, persistent manner. Trends are cleaner and volatility
is lower compared to volatile phases.
No phase
No clear structural condition is active.
These phases describe market structure, not trade entries. They help you understand the conditions you are trading in.
Cross asset context
The Market Framework Model reads markets as a multi layer system. The full version includes cross asset analysis to show whether the asset is acting as a leader or lagger relative to its benchmark. The free version uses the same internal benchmark logic for regime detection but does not display the cross asset layer on the chart.
Cross asset structure is a core part of the MFM model and is fully available in the paid version.
Included in this free version
Higher timeframe regime
Current phase name
Clean chart output
Context only
Works on a selected set of assets
Not included
No forecast signals
No ratio leader or lagger logic
No MRM zones
No MPF timing
No auto tune
The full version contains all features of the complete MFM model.
Full version
You can find the full indicator here:
payhip.com
More information
Model details and documentation:
mfm.inratios.com
Momentum Framework Model free HUD indicator User Guide: mfm.inratios.com
Disclaimer
The Market Framework Model (MFM) and all related materials are provided for educational and informational purposes only. Nothing in this publication, the indicator, or any associated charts should be interpreted as financial advice, investment recommendations, or trading signals. All examples, visualizations, and backtests are illustrative and based on historical data. They do not guarantee or imply any future performance. Financial markets involve risk, including the potential loss of capital, and users remain fully responsible for their own decisions. The author and Inratios© make no representations or warranties regarding the accuracy, completeness, or reliability of the information provided. MFM describes structural market context only and should not be used as the sole basis for trading or investment actions.
By using the MFM indicator or any related insights, you agree to these terms.
© 2025 Inratios. Market Framework Model (MFM) is protected via i-Depot (BOIP) – Ref. 155670. No financial advice.
Regime MapRegime Map — Volatility State Detector
This indicator is a PineScript friendly approximation of a more advanced Python regime-analysis engine.
The original backed identifies market regimes using structural break detection, Hidden-Markov Models, wavelet decomposition, and long-horizon volatility clustering. Since Pine Script cannot execute these statistical models directly, this version implements a lightweight, real-time proxy using realised volatility and statistical thresholds.
The purpose is to provide a clear visual map of evolving volatility conditions without requiring any heavy offline computation.
________________________________________
Mathematical Basis: Python vs Pine
1. Volatility Estimation
Python (Realised Volatility):
RVₜ = √N × stdev( log(Pₜ) − log(Pₜ₋₁) )
Pine Approximation:
RVₜ = stdev( log(Pₜ) − log(Pₜ₋₁), lookback )
Rationale:
Realised volatility captures volatility clustering — a key characteristic of regime transitions.
________________________________________
2. Regime Classification
Python (HMM Volatility States):
Volatility is modelled as belonging to hidden states with different means and variances:
State μ₁, σ₁
State μ₂, σ₂
State μ₃, σ₃
with state transitions determined by a probability matrix.
Pine Approximation (Z-Score Regimes):
Zₜ = ( RVₜ − mean(RV) ) / stdev(RV)
Regime assignment:
• Regime 0 (Low Vol): Zₜ < Zₗₒw
• Regime 1 (Normal): Zₗₒw ≤ Zₜ ≤ Zₕᵢgh
• Regime 2 (High Vol): Zₜ > Zₕᵢgh
Rationale:
Z-scores provide clean statistical boundaries that behave similarly to HMM state separation but are computable in real time.
________________________________________
3. Structural Break Detection vs Rolling Windows
Python (Bai–Perron Structural Breaks):
Segments the volatility series into periods with distinct statistical properties by minimising squared error over multiple regimes.
Pine Approximation:
Rolling mean and rolling standard deviation of volatility over a long window.
Rationale:
When structural breaks are not available, long-window smoothing approximates slow regime changes effectively.
________________________________________
4. Multi-Scale Cycles
Python (Wavelet Decomposition):
Volatility decomposed into long-cycle (A₄) and short-cycle components (D bands).
Pine Approximation:
Single-scale smoothing using long-horizon averages of RV.
Rationale:
Wavelets reveal multi-frequency behaviour; Pine captures the dominant low-frequency component.
________________________________________
Indicator Output
The background colour reflects the active volatility regime:
• Low Volatility (Green): trending behaviour, cleaner directional movement
• Normal Volatility (Yellow): balanced environment
• High Volatility (Red): sharp swings, traps, mean-reversion phases
Regime labels appear on the chart, with a status panel displaying the current regime.
________________________________________
Operational Logic
1. Compute log returns
2. Calculate short-horizon realised volatility
3. Compute long-horizon mean and standard deviation
4. Derive volatility Z-score
5. Assign regime classification
6. Update background colour and labels
This provides a stable, real-time map of market state transitions.
________________________________________
Practical Applications
Intraday Trading
• Low-volatility regimes favour trend and breakout continuation
• High-volatility regimes favour mean reversion and wide stop placement
Swing Trading
• Compression phases often precede multi-day trending moves
• Volatility expansions accompany distribution or panic events
Risk Management
• Enables volatility-adjusted position sizing
• Helps avoid leverage during expansion regimes
________________________________________
Notes
• Does not repaint
• Fully configurable thresholds and lookbacks
• Works across indices, stocks, FX, crypto
• Designed for real-time volatility regime identification
________________________________________
Disclaimer
This script is intended solely for educational and research purposes.
It does not constitute financial advice or a recommendation to buy or sell any instrument.
Trading involves risk, and past volatility patterns do not guarantee future outcomes.
Users are responsible for their own trading decisions, and the author assumes no liability for financial loss.
MFM - Light Context HUD (Free)Overview
MFM Light Context HUD is the free version of the Market Framework Model. It gives you a fast and clean view of the current market regime and phase without signals or chart noise. The HUD shows whether the asset is in a bullish or bearish environment and whether it is in a volatile, compression, drift, or neutral phase. This helps you read structure at a glance.
Asset availability
The free version works only on a selected list of five assets.
Supported symbols are
SP:SPX
TVC:GOLD
BINANCE:BTCUSD
BINANCE:ETHUSDT
OANDA:EURUSD
All other assets show a context banner only.
How it works
The free version uses fixed settings based on the original MFM model. It calculates the regime using a higher timeframe RSI ratio and identifies the current phase using simplified momentum conditions. The chart stays clean. Only a small HUD appears in the top corner. Full visual phases, ratio logic, signals, and auto tune are part of the paid version.
The free version shows the phase name only. It does not display colored phase zones on the chart.
Phase meaning
The Market Framework Model uses four structural phases to describe how the market behaves. These are not signals but context layers that show the underlying environment.
Volatile (Phase 1)
The market is in a fast, unstable or directional environment. Price can move aggressively with stronger momentum swings.
Compression (Phase 2)
The market is in a contracting state. Momentum slows and volatility decreases. This phase often appears before expansion, but it does not predict direction.
Drift (Phase 3)
The market moves in a more controlled, persistent manner. Trends are cleaner and volatility is lower compared to volatile phases.
No phase
No clear structural condition is active.
These phases describe market structure, not trade entries. They help you understand the conditions you are trading in.
Cross asset context
The Market Framework Model reads markets as a multi layer system. The full version includes cross asset analysis to show whether the asset is acting as a leader or lagger relative to its benchmark. The free version uses the same internal benchmark logic for regime detection but does not display the cross asset layer on the chart.
Cross asset structure is a core part of the MFM model and is fully available in the paid version.
Included in this free version
Higher timeframe regime
Current phase name
Clean chart output
Context only
Works on a selected set of assets
Not included
No forecast signals
No ratio leader or lagger logic
No MRM zones
No MPF timing
No auto tune
The full version contains all features of the complete MFM model.
Full version
You can find the full indicator here:
payhip.com
More information
Model details and documentation:
mfm.inratios.com
Disclaimer
The Market Framework Model (MFM) and all related materials are provided for educational and informational purposes only. Nothing in this publication, the indicator, or any associated charts should be interpreted as financial advice, investment recommendations, or trading signals. All examples, visualizations, and backtests are illustrative and based on historical data. They do not guarantee or imply any future performance. Financial markets involve risk, including the potential loss of capital, and users remain fully responsible for their own decisions. The author and Inratios© make no representations or warranties regarding the accuracy, completeness, or reliability of the information provided. MFM describes structural market context only and should not be used as the sole basis for trading or investment actions.
By using the MFM indicator or any related insights, you agree to these terms.
© 2025 Inratios. Market Framework Model (MFM) is protected via i-Depot (BOIP) – Ref. 155670. No financial advice.
2t's MA 50, MA 150, ATRThis indicator displays three key technical signals on the chart:
SMA 50 – Short-term trend direction
SMA 150 – Medium-term trend direction
ATR – Market volatility (Average True Range)
Line colors and lengths can be customized in the settings.
The ATR is plotted on the same chart for quick volatility reference without needing a separate panel.
This tool is designed for traders who want a clean, lightweight view of trend strength and volatility in a single indicator.
Dynamic Ratchet Trend Strategy [VIX Filter]Overview This strategy is a long-only trend-following system designed to capture major market moves while strictly managing downside risk through a state-machine based "Ratchet" exit logic. It incorporates a volatility filter using the CBOE VIX index to stay out of (or exit) the market during high-stress environments.
Key Features
1. Multi-Condition Entries The strategy looks for momentum shifts and trend breakouts using four Simple Moving Averages (25, 50, 100, 200).
Momentum Cross: SMA 25 crossover above SMA 50.
Trend Breakouts: A specific "3-Bar Breakout" logic above the SMA 50, 100, or 200. This requires the price to hold above the SMA for 3 consecutive bars after being below it, reducing false signals compared to simple closes.
2. VIX Volatility Filter Before entering any trade, the script checks the CBOE:VIX.
Filter: If VIX is above the threshold (default 32), new entries are blocked.
Panic Exit: If you are in a position and the VIX spikes above the threshold, the strategy executes an immediate "Panic Exit" to preserve capital during market crashes.
3. The "Ratchet" Exit System (3 Stages) Unlike a standard trailing stop, this strategy uses a 3-stage dynamic exit mechanism that tightens as profits grow:
Stage 0 (Initial Risk): Standard percentage-based Stop Loss from the entry price.
Stage 1 (The Lock-In): Triggered when profit hits 10% (configurable).
Unique Logic: Instead of trailing from the highest high, the stop is calculated based on the price at the exact moment this stage was triggered. It "steps up" once and holds, securing the initial move without being prematurely stopped out by normal volatility.
Stage 2 (Trailing Mode): Triggered when profit hits 15% (configurable).
The strategy switches to a classic Trailing Stop, following the percentage distance from the Highest High.
4. Emergency Backup A "Dead Cross" (SMA 25 crossing under SMA 50) acts as a final fail-safe to close positions if the trend reverses completely before hitting a stop.
Settings & Inputs
SMAs: Customize the lengths for all four moving averages.
VIX Filter: Toggle the filter on/off and set the panic threshold.
Exit Logic: Fully customizable percentages for Initial SL, Stage 1 Trigger/Distance, and Stage 2 Trigger/Trailing Distance.
Disclaimer This script is for educational purposes only. Past performance is not indicative of future results. Always manage your risk appropriately.
Ratchet Exit Trend Strategy with VIX FilterThis strategy is a trend-following system designed specifically for volatile markets. Instead of focusing solely on the "perfect entry," this script emphasizes intelligent trade management using a custom **"Ratchet Exit System."**
Additionally, it integrates a volatility filter based on the CBOE Volatility Index (VIX) to minimize risk during extreme market phases.
### 🎯 The Concept: Ratchet Exit
The "Ratchet" system operates like a mechanical ratchet tool: the Stop Loss can only move in one direction (up, for long trades) and "locks" into specific stages. The goal is to give the trade "room to breathe" initially to avoid being stopped out by noise, then aggressively reduce risk as the trade moves into profit.
The exit logic moves through 3 distinct phases:
1. **Phase 0 (Initial Risk):** At the start of the trade, a wide Stop Loss is set (Default: 10%) to tolerate normal market volatility.
2. **Phase 1 (Risk Reduction):** Once the trade reaches a specific floating profit (Default: +10%), the Stop Loss is raised and "pinned" to a fixed value (Default: -8% from entry). This drastically reduces risk while keeping the trade alive.
3. **Phase 2 (Trailing Mode):** If the trend extends to a higher profit zone (Default: +15%), the Stop switches to a dynamic Trailing Mode. It follows the **Highest High** at a fixed percentage distance (Default: 8%).
### 🛡️ VIX Filter & Panic Exit
High volatility is often the enemy of trend-following strategies.
* **Entry Filter:** The system will not enter new positions if the VIX is above a user-defined threshold (Default: 32). This helps avoid entering "falling knife" markets.
* **Panic Exit:** If the VIX spikes above the threshold (32) while a trade is open, the position is closed immediately to protect capital (Emergency Exit).
### 📈 Entry Signals
The strategy trades **LONG only** and uses Simple Moving Averages (SMAs) to identify trends:
* **Golden Cross:** SMA 25 crosses over SMA 50.
* **3-Bar Breakouts:** A confirmation logic where the price must close above the SMA 50, 100, or 200 for 3 consecutive bars.
### ⚙️ Settings (Inputs)
All parameters are fully customizable via the settings menu:
* **SMAs:** Lengths for the trend indicators (Default: 25, 50, 100, 200).
* **VIX Filter:** Toggle the filter on/off and adjust the panic threshold.
* **Ratchet Settings:** Percentages for Initial Stop, Trigger Levels for Stages 1 & 2, and the Trailing Distance.
### ⚠️ Technical Note & Risk Warning
This script uses `request.security` to fetch VIX data. Please ensure you understand the risks associated with trading leveraged or volatile assets. Past performance is not indicative of future results.
Beast Mode Adaptive Oscillator V6⭐ Beast Mode Adaptive Oscillator V6
Description (Copy/Paste for Publishing)
Beast Mode Adaptive Oscillator V6 is a high-precision, regime-aware momentum engine that adapts dynamically to market conditions.
It blends ADX-based market regime filtering, StochRSI adaptive oscillation, and ATR-driven signal validation to deliver a powerful, low-noise, context-smart oscillator.
Instead of giving the same overbought/oversold signals in every environment, this oscillator changes its behavior depending on market regime:
Market Regime Filter (MRF)
Automatically detects:
✔ Strong Bull Trend
✔ Strong Bear Trend
✔ Ranging Bull
✔ Ranging Bear
✔ Noise / Low-Volatility Environment
ADX + DI structure determines how aggressive or conservative the oscillator becomes.
Adaptive Regime Oscillator (ARO)
A smart StochRSI core whose OB/OS levels shift depending on trend regime:
• In strong trends → wider OB/OS bands (10–90)
• In ranges → tighter, mean-reverting bands (20–80)
• Higher accuracy and fewer false reversals
Price/Volatility Control (PVC)
Built-in ATR risk modules:
• ATR-based stop zones
• ATR-based target zones
• Internal validation to confirm signal strength
Optional Visual Aids
• Entry signal markers
• Regime bar at the bottom of the chart
• ADX line display
• Custom colors for trend strength
What This Indicator Is Best At
• Avoiding bad signals during chop
• Catching trend continuation entries
• Identifying exhaustion points in strong moves
• Adapting OB/OS logic to match volatility
• Confirming strength with ADX + DI structure
Perfect For
• Intraday traders
• Swing traders
• Trend traders
• Mean-reversion setups
• Volatility-based strategies
This is a complete adaptive oscillator system designed to stay accurate across every market condition.
Tesla 3-6-9 Vortex OscillatorTesla 3-6-9 Vortex Oscillator — Description
The Tesla 3-6-9 Vortex Oscillator is a unique market-structure indicator inspired by Nikola Tesla’s 3-6-9 theory, vortex mathematics, and digital-root numerical cycles.
This tool analyzes price and volume through digit-reduction patterns to track the frequency of “sacred” 3-6-9 values versus traditional 1-2-4-5-7-8 “material world” values.
Core Concept
In vortex math, all numbers reduce to a single digit (1–9).
However, 3, 6, and 9 form a special control triad, representing cyclical creation, harmony, and completion.
This indicator measures how often market data resolves into these higher-cycle digits — creating a real-time “vortex energy ratio” for trend bias and momentum shifts.
What the Indicator Measures
✔ Digital Root of Price / Volume / Range
✔ 3-6-9 Frequency vs. Counter Digit Frequency
✔ Vortex Ratio (%) – percentage dominance of 3/6/9 activity
✔ Smoothed Vortex Oscillator – trend-ready version
✔ Tesla Wave – a cyclical sine-wave based on vortex length & chosen (3, 6, or 9) multiplier
✔ Optional Visual Layers:
• Digital-root analysis
• Vortex spiral visualization
• Harmonic 3-6-9 levels
How to Use It
High Vortex Values (above 60%)
→ Market dominated by 3-6-9 cycles
→ Often aligns with expansion, breakouts, or trend strengthening
Low Vortex Values (below 40%)
→ Counter-digit dominance
→ Consolidation, weakening trend, or potential mean-reversion
Tesla Wave Crosses
→ Can signal timing windows and rhythm shifts within the cycle.
Who This Indicator Is For
• Traders who like numerical cycle analysis
• Users of vortex math, digital-root, or harmonic structures
• People who want a non-lagging sentiment oscillator
• Anyone blending TA + number theory for timing large moves
Position Sizing Calculator (Real-Time) - Futures Edition█ SUMMARY
The following indicator is a Position Sizing Calculator based on Average True Range (ATR), originally developed by market technician J. Welles Wilder Jr., intended for real-time trading.
This script utilizes the user's account size, acceptable risk percentage, and a stop-loss distance based on ATR to dynamically calculate the appropriate position size for each trade in real time.
█ BACKGROUND
Developed for use on the Micro E-mini Nasdaq-100 futures (MNQ), this script provides traders with continuously updated dynamic position sizes. It enables traders to instantly determine the exact number of contracts to use when entering a trade while staying within their acceptable risk tolerance.
This real-time position sizing tool helps traders make well-informed decisions when planning trade entries and calculating maximum stop-loss levels, ultimately enhancing risk management.
█ USER INPUTS
Trading Account Size: Total dollar value of the user's trading account.
Acceptable Risk (%): Maximum percentage of the trading account that the user is willing to risk per trade.
ATR Multiplier for Stop-Loss: Multiplier used to determine the distance of the stop-loss from the current price, based on the ATR value.
ATR Length: The length of the lookback period used to calculate the ATR value.
Show Target Risk Row: Toggle to hide/show the Target Risk Row
SL Levels Display: Option to see Both, Long Only, Short Only, or None of the Stop Loss Level Values.
Contract Point Value ($): Point value per contract. Tooltip highlights common values.
Tick Size: Minimum Price Movement (Default set to 0.25)
Minimum Contracts: Override the Minimum Contracts per trade to a user selected value.
(May Exceed User's Target Risk)
DarkPool's Gann High Low Activator DarkPool's Gann High-Low Activator.
It enhances the traditional trend-following logic by integrating Heikin Ashi smoothing, Multi-Timeframe (MTF) analysis, and volatility filtering. It is designed to filter out market noise and provide clearer trend signals during volatile conditions.
Underlying Concepts
Heikin Ashi Smoothing: Standard price candles can produce erratic signals due to wicks and short-term volatility. This script includes a "Calculation Mode" setting that allows the Gann logic to run on Heikin Ashi average prices. This smoothes out price data, helping traders stay in trends longer by ignoring temporary pullbacks.
Gann High-Low Logic: The core algorithm tracks the Simple Moving Average (SMA) of Highs and Lows over a user-defined period.
Bullish Trend: Price closes above the trailing SMA of Highs.
Bearish Trend: Price closes below the trailing SMA of Lows.
Volatility & Trend Filtering: To reduce false signals during sideways markets, this tool employs two filters:
ADX Filter (Choppiness): Uses the Average Directional Index to detect low-volatility environments. If the ADX is below the defined threshold (default 20), the indicator identifies the market as "choppy" and suppresses signals to preserve capital.
EMA Filter (Baseline): An optional Exponential Moving Average filter ensures trades are only taken in the direction of the longer-term trend (e.g., Longs only above the 200 EMA).
Features
Dual Calculation Modes: Switch between Standard price logic and Heikin Ashi smoothing logic.
Multi-Timeframe (MTF): Calculate the trend based on a higher timeframe (e.g., 4-Hour) while viewing a lower timeframe chart (e.g., 15-Minute).
Automated JSON Alerts: Generates machine-readable JSON alert payloads compatible with external trading bots and webhooks.
Live Dashboard: A data table displaying the current Trend State, Calculation Mode, ADX Value, and risk percentage.
How to Use
Buy Signal: Generated when the trend flips Bullish, provided the ADX indicates sufficient momentum and the price satisfies the EMA filter (if enabled).
Sell Signal: Generated when the trend flips Bearish, subject to the same momentum and trend filters.
Neutral State (Gray Cloud): When the cloud fill turns gray, the market is in consolidation. It is recommended to avoid entering new positions during this state.
Trailing Stop: The Gann Line serves as a dynamic trailing stop-loss level. A close beyond this line invalidates the current trend.
Settings Configuration
Calculation Mode: Select "Standard" for raw price action or "Heikin Ashi" for smoothed trend following.
Gann Length: Lower values (3-5) are suitable for short-term scalping; higher values (10+) are better for swing trading.
MTF Mode: Enable to lock the calculation to a specific higher timeframe.
ADX Threshold: Adjust based on asset volatility. Recommended: 20-25 for Crypto, 15-20 for Forex/Indices.
Disclaimer
This source code and the information presented here are for educational purposes only. This script does not constitute financial advice, trading recommendations, or a solicitation to buy or sell any financial instruments. Trading in financial markets involves a high degree of risk and may not be suitable for all investors. Past performance is not indicative of future results. The author assumes no responsibility for any losses incurred while using this indicator. Use this tool at your own discretion and risk.
RSI Regimes + Cardwell Sweet SpotsRSI based upon Cardwell principles, with a strength evaluation based upon the ADX, VWAP, velocity of both, and Cardwell RSI principles of a sweet spot of a RSI.
Apex Liquidity & Trend Architect [Smart]Trading charts often suffer from two problems: Noise (too many false signals in chopping markets) and Clutter (too many old lines and zones obscuring price).
ALTA solves both. It is a streamlined, institutional-grade trend system that uses ADX filtering to silence weak signals and Time-Decay logic to automatically clean up old liquidity zones. It respects your screen real estate, showing you only what matters, right now.
1. The "Smart" Engine
Unlike standard trend indicators that repaint or clutter the screen, ALTA introduces three key innovations:
A. Hull Moving Average (HMA) Baseline
We have upgraded the core engine to use the Hull Moving Average. HMA is significantly faster and smoother than standard EMAs or SMAs, reducing lag on entry signals.
Note: You can switch back to WMA or SMA in the settings if you prefer a slower pace.
B. ADX Momentum Filtering
Quality over Quantity: The script monitors the ADX (Average Directional Index). If the trend flips, but the ADX is below 20 (weak trend), the signal is blocked.
This prevents you from getting chopped out during sideways accumulation phases. You only get a "BUY" or "SELL" label when there is actual momentum behind the move.
C. Adaptive Gradient Coloring
The candles do not just turn Green or Red. They change intensity based on trend strength.
Bright/Vivid Candles: Strong Momentum (High ADX).
Dark/Dull Candles: Weak Momentum (Low ADX).
Visual Cue: If the candles are fading into the background, stay out of the market.
2. Self-Cleaning Liquidity Zones
Most support/resistance indicators leave old boxes on the chart forever. ALTA uses a Decay Protocol.
Volume Validation: Supply/Demand zones are only drawn if the pivot point had volume significantly higher than average (configurable).
Mitigation: If price wicks through a zone, it is deleted instantly.
Time Decay (New): If a zone is not hit within a set number of bars (Default: 100), it automatically deletes itself. This keeps your chart focused on fresh levels only.
3. The Minimalist HUD
A simplified dashboard in the corner of your screen provides an instant health check of the market:
ALTA Label: System Status.
Trend: BULL / BEAR / WAIT (Squeeze).
Power: WEAK / SOLID / STRONG (Based on ADX).
4. How to Trade (The Strategy)
The High-Probability Buy
Trend: Ribbon is Green.
Candles: Candles are Bright Green (indicating High ADX Strength).
Signal: A "BUY" label appears (confirmed by ADX filter).
Liquidity: Price is bouncing off a valid Demand Zone.
The High-Probability Sell
Trend: Ribbon is Red.
Candles: Candles are Bright Red (indicating High ADX Strength).
Signal: A "SELL" label appears.
Liquidity: Price is rejecting off a valid Supply Zone.
When to STAY OUT
The Squeeze: If the ribbon turns Grey/White, volatility is compressing. Wait for the breakout.
The Fade: If the candles are dark/translucent, momentum is dying. Take profits or wait for a fresh impulse.
5. Settings & Customization
Basis Type: Switch between HMA (Fast), WMA (Standard), or SMA (Slow).
Signal Quality Filter: Toggle the ADX filter on/off.
Zone Life: How many bars should a Supply/Demand zone survive before decaying?
Tooltips: Every single setting in this script includes a descriptive tooltip. Hover over the "i" icon in the settings menu for detailed explanations of every feature.
Disclaimer
This indicator is for educational purposes only. Past performance (even with smart filtering) does not guarantee future results. Always manage your risk.
