fractvol

Name	fractvol JSON
Version	0.1.0 JSON
	download
home_page	None
Summary	Fractal Volatility Signatures for detecting market regimes using multifractal analysis.
upload_time	2025-08-03 03:23:17
maintainer	None
docs_url	None
author	None
requires_python	None
license	MIT
keywords	finance volatility fractal hurst regime quant trading
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
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            # fractvol – Fractal Volatility Signatures

Detect hidden market regimes using **multifractal scaling** and **Hurst dynamics**.  
`fractvol` brings advanced physics-based time series analysis to finance.

```python
import fractvol as fv
import yfinance as yf

data = yf.download("SPY")['Close'].pct_change().dropna()

# Rolling fractal analysis
hursts = fv.rolling_hurst(data, window=100)

# Detect regime shifts
sigs = [fv.fractal_signature(data[i:i+200]) for i in range(0, len(data)-200, 50)]
regimes = fv.detect_regime_change(sigs)

# Predict volatility spikes
risk_score = fv.predict_volatility_spark(data)

# Visualize
fv.plot_multifractal(data[-150:])

            

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