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Hurst-Based Trend Persistence w/Poisson Prediction

Created by garysebastianbrowniii

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Hurst-Based Trend Persistence w/Poisson Prediction chart preview

Hurst-Based Trend Persistence w/Poisson Prediction

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A statistically-driven trend oscillator that combines Hurst exponent analysis and Poisson probability to measure trend persistence, strength, and potential reversals.

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UNDERSTAND THE TOOL

How it works

The indicator calculates the Hurst exponent over a rolling window to determine trend persistence. It uses color-coding to represent bullish (green) or bearish (red) conditions.

A Poisson probability model estimates the likelihood of trend reversals by analyzing historical trend durations. The oscillator line reflects whether price movements are trending, mean-reverting, or random. A gray dashed line at zero helps traders quickly assess market behavior

Why it may be useful

This signal provides traders with a sophisticated, probability-weighted view of market trends. By integrating fractal market theory with statistical modeling, it offers insights beyond traditional trend indicators.

The Hurst exponent helps identify whether markets are momentum-driven or mean-reverting. The color-coded trend detection and Poisson reversal projections give traders a nuanced understanding of potential price movements and trend sustainability

When to explore it

The indicator is most effective in markets with clear directional movements, such as strong bull or bear markets. It works best on timeframes that allow sufficient data for statistical analysis, typically daily or weekly charts.

Traders should use it to confirm trend strength, anticipate potential reversals, and avoid counter-trend trades. It's particularly useful in less volatile markets where trend persistence can be more reliably predicted

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CHECK THE DETAILS

What we’ve verified

Access, alerts and repainting behaviour have not been independently verified for this indicator. Check the creator’s current publication and settings.

General descriptions and classifications are recovered research. Verified details above identify the specific checks we have completed. Check the creator’s current publication for later changes.