Trojan Cycle: Dip & Profit Hunter📉 Crypto is changing. Your signals should too.
This script doesn’t try to outguess price — it helps you track capital rotation and flow behavior in alignment with the evolving macro structure of the digital asset market.
Trojan Cycle: Dip & Profit Hunter is a signal engine built to support and validate the capital rotation models outlined in the Trojan Cycle and Synthetic Rotation theses — available via RWCS_LTD’s published charts
It is not a classic “buy low, sell high” tool. It is a structural filter that uses price/volume statistics to surface accumulation zones, synthetic traps, and macro context shifts — all aligned with the institutionalization of crypto post-2024.
🧠 Purpose & Value
Crypto no longer follows the retail-led, halving-driven pattern of 2017 or 2021.
Instead, institutional infrastructure, regulatory filters, and equity-market Trojan horses define the new path of capital.
This tool helps you visualize that path by interpreting behavior through statistical imbalances and real-time momentum signals.
Use it to:
Track where capital is accumulating or exiting
Identify signals consistent with true cycle rotation (vs. synthetic traps)
Validate your macro view with real-time statistical context
🔍 How It Works
The engine combines four signal layers:
1. Z-Score Logic
- Measures how far price and volume have deviated from their mean
- Detects dips, blowoffs, and exhaustion zones
2. Percentile Logic
- Compares current price and volume to historical rank distribution
- Flags statistically rare conditions (e.g. bottom 10% price, top 90% volume)
3. Combined Context Engine
- Integrates both models to generate one of 36 unique output states
- Each state provides a labeled market context (e.g., 🟢 Confluent Buy, 🔴 Confluent Sell, 🧨 Synthetic Trap )
4. Momentum Spread & Divergence
- Measures whether price is leading volume (trap risk) or volume is leading price (accumulation)
- Outputs intuitive momentum context with emoji-coded alerts
📋 What You See
🧠 Contextual Table UI with key Z-Scores, percentiles, signals, and market commentary
🎯 Emoji-coded signals to quickly grasp high-probability setups or risk zones
🌊 Optional overlays: price/volume divergence, momentum spread
🎨 Visual table customization (size, position) and chart highlights for signal clarity
🔔 Alert System
✅ Single dynamic alert using alert() that only fires when signal context changes
Prevents alert fatigue and allows clean webhook/automation integration
🧭 Use Cases
For macro cycle traders: Track where we are in the Trojan Cycle using statistical context
For thesis explorers: Use the 36-output signal map to match against your rotation thesis
For capital rotation watchers: Identify structural setups consistent with ETF-driven or compliance-filtered flow
For narrative skeptics: Avoid synthetic altseason traps where volume lags or flow dries up
🧪 Suggested Pairing for Thesis Validation
To use this tool as part of a thesis-confirmation framework , pair it with:
BTC.D — Bitcoin Dominance
ETH/BTC — Ethereum strength vs. Bitcoin
TOTALE100/ETH — Altcoin strength relative to ETH
RWCS_LTD’s published charts and macro cycle models
🏁 Final Note
Crypto has matured. So should your signals.
This tool doesn’t try to game the next 2 candles. It helps you understand the current phase in a compliance-filtered, institutionalized rotation model.
It’s not built for hype — it’s built for conviction.
Explore the thesis → Validate the structure → Trade with clarity.
🚨 Disclaimer
This script is not financial advice. It is an analytical tool designed to support market structure research and rotation thesis validation. Use this as part of a broader framework including technical structure, dominance charts, and macro data.
Statistics
Alpha Spread Indicator Panel - [AlphaGroup.Live]Alpha Spread Indicator Panel –
This sub-panel plots the OLS spread between two assets, normalized into percent .
• Green area = spread above zero (Buy Leg1 / Sell Leg2)
• Red area = spread below zero (Sell Leg1 / Buy Leg2)
• The white line shows the exact % deviation of the spread from its fitted baseline
• Optional ±1% and ±2% guides give clear statistical thresholds
Because it’s expressed in percent relative to midprice , the scale remains consistent even if absolute prices change over years.
⚠️ Important: This panel is designed to be used together with the overlay chart:
👉 Alpha Spread Indicator Chart –
Pre-selected asset pairs included:
EURUSD / GBPUSD
AUDUSD / NZDUSD
USDJPY / USDCHF
USDCAD / USDNOK
EURJPY / GBPJPY
AUDJPY / NZDJPY
XAUUSD / XAGUSD
WTI (USOIL) / Brent (UKOIL)
NatGas / Crude
HeatingOil / RBOB
Corn / Wheat
Platinum / Palladium
XOM / CVX
KO / PEP
V / MA
JPM / BAC
NVDA / AMD
BHP / RIO
SHEL / BP
SPY / QQQ
Want more institutional-grade setups? Get our 100 Trading Strategies eBook free at:
alphagroup.live
Tags: pairs-trading, spread-trading, statistical-arbitrage, ols-regression, zscore, mean-reversion, arbitrage, quant, hedge, alphagroup
Size & LeverageSize and Leverage calculator for trading, using market orders. It will calculate maximum possible leverage by default in order to prioritize capital efficiency. If you wish to use manual leverage you need to manually enter it in the settings. The script rounds both auto leverage and size to your liking. Entry price is always last price. Size is the actual size you need to input, adjusted to your leverage, cost means the margin required to open the trade. I made this indicator as a binance futures user.
Calculadora de posicion)Position Size Calculator is a simple tool that helps traders instantly know how many contracts or lots to use based on their risk.
Just set your account size, risk percentage, and stop loss distance — the calculator does the rest.
Stay disciplined, control your risk, and trade with confidence.
Crypto Position Size CalculatorPosition Size Calculator for Crypto.
This indicator uses the current price and a selected stop loss to calculate your position size without having to work it out elsewhere!
Simply set your account size, desired risk percentage and stop loss level and it will work out how many lots and the dollar value of your desired position.
Hope you enjoy!
Alpha Spread Indicator Chart - [AlphaGroup.Live]Alpha Spread Indicator Chart –
This overlay plots the two legs of a pair trade directly on the price chart .
• Leg1 is shown in teal
• Leg2 (fitted) is shown in orange
• The green/red filled area shows the distance (spread) between the two
The spread is calculated using OLS regression fitting , which keeps Leg2 scaled to Leg1 so the overlay always sticks to the chart’s price axis. When the fill turns green , the model suggests Buy Leg1 / Sell Leg2; when it turns red , it suggests Sell Leg1 / Buy Leg2.
Optional Z-Score bands help visualize statistical stretch from the mean.
⚠️ Important: To use this tool properly, you also need to install the companion script:
👉 Alpha Spread Indicator Panel –
Pre-selected asset pairs included:
EURUSD / GBPUSD
AUDUSD / NZDUSD
USDJPY / USDCHF
USDCAD / USDNOK
EURJPY / GBPJPY
AUDJPY / NZDJPY
XAUUSD / XAGUSD
WTI (USOIL) / Brent (UKOIL)
NatGas / Crude
HeatingOil / RBOB
Corn / Wheat
Platinum / Palladium
XOM / CVX
KO / PEP
V / MA
JPM / BAC
NVDA / AMD
BHP / RIO
SHEL / BP
SPY / QQQ
Ready to take your trading further? Download our free eBook with 100 trading strategies at:
alphagroup.live
Tags: pairs-trading, spread-trading, statistical-arbitrage, ols-regression, zscore, mean-reversion, arbitrage, quant, hedge, alphagroup
VSA Highlight & Relative Strength of Volume [odnac]This is a TradingView indicator combining VSA (Volume Spread Analysis) signals with a relative strength of volume visualization.
The indicator has two main parts:
1. VSA Volume Highlight:
Detects common VSA signals, including Stopping Volume, Buying Climax, No Supply, No Demand, Test, Up-thrust, Shakeout, Demand Absorption, and Supply Absorption.
Supports a trend filter using a user-selectable moving average type (SMA, EMA, WMA, or VWMA) and length.
Calculates spread and volume moving averages to determine wide/narrow spreads and high/low volume relative to the averages.
Determines relative bar positions (close near high, close near low, or mid-close) to categorize VSA signals.
Optionally colors the background based on the detected VSA signal.
Supports alerts for each VSA signal type.
2. Relative Strength of Volume:
Splits total volume into buying and selling components based on the candle’s high, low, and close.
Buying volume is calculated as volume times the proportion of the candle’s close above the low.
Selling volume is calculated as volume times the proportion of the candle’s close below the high.
Plots buying and selling volume as colored columns in the pane.
Plots total volume in the status line colored according to the dominant side (buying or selling).
Inputs include:
Toggle visibility for each VSA signal.
Trend filter options (type and length).
Volume and spread moving average lengths and multipliers for high/low volume and wide/narrow spread detection.
Thresholds for close positions near high or low, and for identifying Buying Climax.
Opacity for VSA volume highlights.
The indicator is designed to help traders visually identify key volume patterns and analyze buying and selling pressure in the market.
AndrologQuartileAndrologQuartile
This indicator is based on the assumption that if a candle closes in the upper or lower quartile of its range, the next candle often tends to take out the high or low of that candle.
The script does two things:
It calculates and displays live statistics on how often this condition occurs and how often it is successful.
It highlights candles that meet the quartile condition so you can track them in real time.
It is most meaningful to use this indicator on higher timeframes (from 1h upwards).
You can also set an alert: once configured, the alert will always trigger for the timeframe that was active at the moment of setup.
Usage tip:
Click the statistics panel in the top right corner to adjust settings and alerts.
Adjustable parameters:
Quartiles: Default values are 25% and 75%.
Min Distance: Defines how far the high/low must be from the candle’s close (in %) to be considered relevant. A smaller value is applied automatically on intraday timeframes under 5 minutes.
Custom Support & Resistance Levels (Manual Input)This indicator lets you plot your own support levels (and can be extended for resistance) directly on the chart by entering them as comma-separated values.
📌 Supports manual input for multiple price levels.
📊 Lines are extended across the chart for clear visualization.
🎨 Dynamic coloring:
Green if the current price is above the level.
Red if the current price is below the level.
🧹 Old lines are automatically cleared to avoid clutter.
This tool is ideal if you:
Prefer to mark your own key zones instead of relying only on auto-detected levels.
Want clean and simple visualization of critical price areas.
👉 Coming soon: Resistance levels input (commented in the code, can be enabled).
ATR by Session Library [1CG]Library "ATRxSession"
This library shows you how big the bars usually are during a trading session. It looks only at the times you choose (like New York or London hours), measures the “true range” of every bar in that session, then finds the average for that session. It keeps the last N sessions and gives you their overall average, so you can quickly see how much the market typically moves per bar during your chosen session.
Call getSessionAtr(timezone, session, sessionCount) from your script, and it will return a single number: the average per-bar volatility during the chosen session, based on the last N completed sessions. This makes it easy to plug session-specific volatility into your own indicators or strategies.
getSessionAtr(_timezone, _session, _sessionCount)
getSessionAtr - Computes a session-aware ATR over completed sessions.
Parameters:
_timezone (string) : (string) - Timezone string to evaluate session timing.
_session (string) : (string) - Session time range string (e.g., "0930-1600").
_sessionCount (int) : (int) - Number of past completed sessions to include in the rolling average.
Returns: (float) - The average ATR across the last N completed sessions, or na if not enough data.
Gott's Copernican Trend PredictorThe Gott's Copernican Trend Predictor predicts trend duration using the Copernican Principle - Based on astrophysicist Richard Gott's temporal prediction method.
I had the idea to create this indicator after reading the book The Doomsday Calculation by William Poundstone.
Background & Theory
This indicator implements J. Richard Gott III's Copernican Principle - a statistical method that famously predicted the fall of the Berlin Wall and the duration of Broadway shows with remarkable accuracy.
The Copernican Principle Explained
Named after Copernicus who showed that Earth is not at the center of the universe, this principle assumes that you are not observing something at a special moment in time. When you observe a trend at any random point, you're statistically more likely to be seeing it during the "middle portion" of its lifetime rather than at its very beginning or end.
The Mathematics
Gott's formula provides a 95% confidence interval for how much longer a trend will continue:
Minimum remaining duration = Current Age ÷ 39
Maximum remaining duration = Current Age × 39
The factor of 39 comes from statistical analysis where:
There's only a 2.5% chance you're observing in the first 1/40th of the trend's life
There's only a 2.5% chance you're observing in the last 1/40th of the trend's life
This gives us 95% confidence that the trend will last between Age/39 and Age×39
How It Works
Trend Detection
The indicator uses dual moving averages (default: 50 & 200 period) to identify trend changes:
Bullish Cross: Fast MA crosses above Slow MA → Uptrend begins
Bearish Cross: Fast MA crosses below Slow MA → Downtrend begins
Real-Time Predictions
Once a trend is detected, the indicator continuously calculates:
Trend Age: How long the current trend has been active
Gott's 95% CI: Statistical range for remaining trend duration
Projected End Dates: Calendar dates when the trend might end
How to Use
Setup
Add the indicator to any timeframe (works on minutes, hours, days, weeks)
Customize MA periods and type (SMA, EMA, WMA)
Choose table position and font size for optimal viewing
Interpretation
Example: If a trend is 100 hours old:
Minimum duration: 100 ÷ 39 = ~3 more hours
Maximum duration: 100 × 39 = ~3,900 more hours
95% confidence: The trend will end between these times
This indicator might be useful for swing traders, trend followers, and quantitative analysts.
Coca-Cola example:
Coca-Cola's chart shows an uptrend spanning 810 weeks, approximately 15.5 years. According to Gott's Copernican Principle, this trend age generates a 95% confidence interval predicting the trend will continue for a minimum of 20 weeks and a maximum of 31,590 weeks.
On the other hand, a shorter trend age produces a proportionally smaller minimum duration and different risk profile in terms of statistical continuation probability. For this reason, more recent trends (and more recent companies) are likely to remain in trend for shorter.
VSA Signals [odnac]This indicator applies Volume Spread Analysis (VSA) concepts to highlight important supply and demand events directly on the chart. It automatically detects common VSA patterns using price spread, relative volume, and candle structure, with optional trend filtering for higher accuracy.
Features:
Stopping Volume (SV): Signals potential end of a downtrend when heavy buying appears.
Buying Climax (BC): Indicates exhaustion of an uptrend with heavy volume near the top.
No Supply (NS): Weak selling pressure, often a bullish sign in an uptrend.
No Demand (ND): Weak buying interest, often a bearish sign in a downtrend.
Test: Low-volume test bar probing for supply.
Up-thrust (UT): Failed breakout with long upper wick, often a bearish trap.
Shakeout: Bear trap with high-volume wide down bar closing low.
Demand Absorption (DA): Demand absorbing heavy selling pressure.
Supply Absorption (SA): Supply absorbing heavy buying pressure.
Additional Options:
Background highlights for detected signals.
Configurable moving average (SMA, EMA, WMA, VWMA) as a trend filter.
Adjustable multipliers for volume and spread sensitivity.
Legend table for quick reference of signals and meanings.
Alerts available for all signals.
This tool is designed to help traders spot professional accumulation and distribution activity and to improve trade timing by recognizing supply/demand imbalances in the market.
Weekly High/Low Day StatsThis TradingView Pine Script (v5) analyzes weekly highs and lows to identify on which day of the week (Monday → Friday) they most frequently occur.
🔎 How it works:
Tracks the weekly highest high and lowest low.
At the end of each week, it records the day of the week when the high and low were set.
Keeps historical data for the last 100 weeks (adjustable).
Displays a table showing:
How many times each day marked the weekly high or weekly low.
The corresponding percentage distribution.
🎯 Use case:
Helps traders understand the weekly timing tendency
Reveals which day is statistically more likely to set the weekly high or weekly low.
Useful for weekly planning and strategies that rely on market structure and timing (e.g., ICT concepts like the "High/Low of the Week").
Realized Volatility (StdDev of Returns, %)📌 Realized Volatility (StdDev of Returns, %)
This indicator measures realized volatility directly from price returns, instead of the common but misleading approach of calculating standard deviation around a moving average.
🔹 How it works:
Computes close-to-close log returns (the most common way volatility is measured in finance).
Calculates the standard deviation of these returns over a chosen lookback period (default = 200 bars).
Converts results into percentages for easier interpretation.
Provides three key volatility measures:
Daily Realized Vol (%) – raw standard deviation of returns.
Annualized Vol (%) – scaled by √250 trading days (market convention).
Horizon Vol (%) – volatility over a custom horizon (default = 5 days, i.e. weekly).
🔹 Why use this indicator?
Shows true realized volatility from historical returns.
More accurate than measuring deviation around a moving average.
Useful for traders analyzing risk, position sizing, and comparing realized vs implied volatility.
⚠️ Note:
It is best used on the Daily Chart!
By default, this uses log returns (which are additive and standard in quant finance).
If you prefer, you can easily switch to simple % returns in the code.
Volatility estimates depend on your chosen lookback length and may vary across timeframes.
Atr avg monthly by PanzerDisplay average ATR for 6 and 12 completed months in a text information table on the chart.
These values are handy for calculating options strategies.
Table can be display on several positions on chart.
Daily Seasonality Strength + PredictionDaily Seasonality Strength + Prediction
Seasonality Strength:
This indicator measures seasonality strength by comparing predicted seasonal returns with actual returns, using the inverse of MSE (higher values mean stronger seasonality).
This script is for informational and educational purposes only. It does not constitute financial, investment, or trading advice. I am not a financial advisor. Any decisions you make based on this indicator are your own responsibility. Always do your own research and consult with a qualified financial professional before making any investment decisions.
Past performance is no guarantee of future results. The value of the instruments may fluctuate and is not guaranteed
Daily Seasonality Strength + Prediction TableDaily Seasonality Strength + Prediction Table
Return Estimates:
This indicator uses historical price data to calculate average returns for each day (of the week or month) and uses these to predict the next day’s return.
Seasonality Strength:
It measures seasonality strength by comparing predicted returns with actual returns, using the inverse of MSE (higher values mean stronger seasonality).
supports up to 10 assets
This script is for informational and educational purposes only. It does not constitute financial, investment, or trading advice. I am not a financial advisor. Any decisions you make based on this indicator are your own responsibility. Always do your own research and consult with a qualified financial professional before making any investment decisions.
Past performance is no guarantee of future results. The value of the instruments may fluctuate and is not guaranteed
ICT Midnight PDH PDLPara marcar rango Midnight to Midnight (NYMO).
También para marcar rangos horarios que tu quieras.
Mutanabby_AI | ATR+ | Trend-Following StrategyThis document presents the Mutanabby_AI | ATR+ Pine Script strategy, a systematic approach designed for trend identification and risk-managed position entry in financial markets. The strategy is engineered for long-only positions and integrates volatility-adjusted components to enhance signal robustness and trade management.
Strategic Design and Methodological Basis
The Mutanabby_AI | ATR+ strategy is constructed upon a foundation of established technical analysis principles, with a focus on objective signal generation and realistic trade execution.
Heikin Ashi for Trend Filtering: The core price data is processed via Heikin Ashi (HA) methodology to mitigate transient market noise and accentuate underlying trend direction. The script offers three distinct HA calculation modes, allowing for comparative analysis and validation:
Manual Calculation: Provides a transparent and deterministic computation of HA values.
ticker.heikinashi(): Utilizes TradingView's built-in function, employing confirmed historical bars to prevent repainting artifacts.
Regular Candles: Allows for direct comparison with standard OHLC price action.
This multi-methodological approach to trend smoothing is critical for robust signal generation.
Adaptive ATR Trailing Stop: A key component is the Average True Range (ATR)-based trailing stop. ATR serves as a dynamic measure of market volatility. The strategy incorporates user-defined parameters (
Key Value and ATR Period) to calibrate the sensitivity of this trailing stop, enabling adaptation to varying market volatility regimes. This mechanism is designed to provide a dynamic exit point, preserving capital and locking in gains as a trend progresses.
EMA Crossover for Signal Generation: Entry and exit signals are derived from the interaction between the Heikin Ashi derived price source and an Exponential Moving Average (EMA). A crossover event between these two components is utilized to objectively identify shifts in momentum, signaling potential long entry or exit points.
Rigorous Stop Loss Implementation: A critical feature for risk mitigation, the strategy includes an optional stop loss. This stop loss can be configured as a percentage or fixed point deviation from the entry price. Importantly, stop loss execution is based on real market prices, not the synthetic Heikin Ashi values. This design choice ensures that risk management is grounded in actual market liquidity and price levels, providing a more accurate representation of potential drawdowns during backtesting and live operation.
Backtesting Protocol: The strategy is configured for realistic backtesting, employing fill_orders_on_standard_ohlc=true to simulate order execution at standard OHLC prices. A configurable Date Filter is included to define specific historical periods for performance evaluation.
Data Visualization and Metrics: The script provides on-chart visual overlays for buy/sell signals, the ATR trailing stop, and the stop loss level. An integrated information table displays real-time strategy parameters, current position status, trend direction, and key price levels, facilitating immediate quantitative assessment.
Applicability
The Mutanabby_AI | ATR+ strategy is particularly suited for:
Cryptocurrency Markets: The inherent volatility of assets such as #Bitcoin and #Ethereum makes the ATR-based trailing stop a relevant tool for dynamic risk management.
Systematic Trend Following: Individuals employing systematic methodologies for trend capture will find the objective signal generation and rule-based execution aligned with their approach.
Pine Script Developers and Quants: The transparent code structure and emphasis on realistic backtesting provide a valuable framework for further analysis, modification, and integration into broader quantitative models.
Automated Trading Systems: The clear, deterministic entry and exit conditions facilitate integration into automated trading environments.
Implementation and Evaluation
To evaluate the Mutanabby_AI | ATR+ strategy, apply the script to your chosen chart on TradingView. Adjust the input parameters (Key Value, ATR Period, Heikin Ashi Method, Stop Loss Settings) to observe performance across various asset classes and timeframes. Comprehensive backtesting is recommended to assess the strategy's historical performance characteristics, including profitability, drawdown, and risk-adjusted returns.
I'd love to hear your thoughts, feedback, and any optimizations you discover! Drop a comment below, give it a like if you find it useful, and share your results.
NQ Stats Mean ReversionBased off of Multi-timeframe support by keypoems, modified to be anchored on a HTF and added a dynamic label to give current SD level with chance of reversion
Marcius Studio® - Cross-Asset Correlator™Cross-Asset Correlator™ — a pair-trading strategy that identifies correlation breakdowns between two assets and captures profit opportunities from market inefficiencies.
The strategy enters trades when the correlation drops below a set threshold and closes positions once correlation recovers.
The main concept is to exploit temporary divergence between two assets by going long the stronger one and short the weaker one, aiming to profit when their correlation reverts.
Important : This script illustrates asset correlation concepts for educational purposes only. It's not for live trading—requires adjustments and offers no performance guarantees. Always apply risk management.
TradingView Limitation
By default, TradingView’s built-in Strategy interface does not support backtesting with two different assets .
To overcome this, the script is implemented as an indicator with a fully custom backtesting engine that calculates PnL, trades, and performance statistics directly on the chart.
Idea
Markets move in clusters : altcoins follow BTC, memecoins track Solana, L2 projects mirror Ethereum. But correlations aren’t perfect—temporary divergences create pricing inefficiencies.
The logic:
When an asset lags or overshoots its usual correlation, it’s a mispricing opportunity.
Trade the reversion: buy undervalued divergence, sell overextended convergence.
The market eventually corrects, but the inefficiency window allows profit before realignment.
OKX Signal Bot Integration
This script includes a built-in interface for OKX Signal Bot .
It can generate structured JSON alerts (ENTER / EXIT, long / short) and directly manage trades on OKX exchange .
This allows seamless automation of correlation-based strategies without manual order execution.
Note : The OKX Signal Bot (for demo use only) assists with alerts & trade management but does not ensure profits. You are fully responsible for your trades—always apply risk management.
Strategy Parameters
Symbol 1 / Symbol 2 : trading instruments to be analyzed.
SMA Period : smoothing period for price averages.
Correlation Period : number of bars used to calculate correlation coefficient.
Upper Correlation Threshold : level above which trades are closed.
Lower Correlation Threshold : level below which new trades are opened.
percentage_investment (%) : allocation per entry signal (used for OKX integration).
Example Settings OKX:FARTCOINUSDT.P / OKX:PENGUUSDT.P
Timeframe : 1H
SMA Period : 60
Correlation Period : 25
Upper Threshold : 0.9
Lower Threshold : 0.1
percentage_investment : 10%
How the Code Works
Retrieves closing prices of two selected assets.
Calculates correlation coefficient and moving averages.
When correlation breaks below the lower threshold, the script opens a pair trade (long/short depending on SMA relation).
When correlation recovers above the upper threshold, all open trades are closed.
Real-time alerts are generated in JSON format for OKX bots (ENTER/EXIT signals).
Built-in backtesting engine tracks PnL, trades, and statistics (7d / 30d / total).
Visual labels mark entries, exits, and PnL results directly on the chart.
Disclaimer
Trading involves risk — always do your own research (DYOR) and seek professional financial advice. We are not responsible for any potential financial losses.
Marcius Studio® - Trend Detector™Trend Detector™ — is an advanced trend detection indicator that combines statistical Z-Score analysis with a simplified ADF stationarity test .
It is designed to help traders identify strong directional moves while filtering out noise and false signals.
Unlike traditional moving average crossovers or momentum oscillators, this tool evaluates both trend direction and trend strength , giving you a clear visual overview of market conditions.
Important! This indicator is intended for educational and informational purposes . It does not guarantee future performance and should be used together with proper risk management.
Idea
Markets spend 70–80% of the time in consolidation and only 20–30% in trending phases . The key to profitable trading is spotting when a major trend shift begins. Trend Detector™ was built exactly for this purpose — to filter noise and highlight true trend reversals.
How It Works
Calculates the Z-Score of price to detect extreme deviations from the mean.
Applies a simplified ADF t-Statistic test to confirm trend validity.
Uses an ATR-based ribbon for clean visualization of bullish/bearish phases.
Generates Buy/Sell signals when trend switches are confirmed.
Displays an Info Panel with real-time metrics: Z-Score, ADF t-Stat, Trend Strength (0–100), ATR % of price.
Features
Trend Ribbon : visually highlights bullish, bearish, or neutral phases.
Confirmation Filter : avoids false flips by requiring multiple bars of validation.
Strength Score : quantifies how powerful the current trend is.
Signal Markers : “BUY” and “SELL” alerts appear directly on the chart.
Customizable Alerts : get notified when new uptrends or downtrends are detected.
Recommendations
Works well on swing trading timeframes (1H, 4H, Daily).
Use in combination with support/resistance zones or volume profile tools for higher accuracy.
The higher the Trend Strength Score , the more reliable the trend continuation.
Indicator Settings
Analysis Period : number of bars for Z-Score & ADF test.
ATR Length : used for ribbon visualization.
Min Bars to Confirm Trend : filters false trend flips.
Show/Hide options for Ribbon, Signals, and Info Panel.
Example Settings
Timeframe : 1H or 4H
Analysis Period : 20
ATR Length : 14
Min Confirmation Bars : 2–3
Disclaimer
Trading and investing involve risk — always do your own research (DYOR) and seek professional advice. We are not responsible for any financial losses.