Metadata-Version: 2.4
Name: fracjax
Version: 0.1.0
Summary: High-Performance Fractal & Econophysics Tools for Financial Time Series using JAX (GPU-Accelerated)
Author-email: Mohammad Korivand <korivandmohammadb@gmail.com>
License: MIT License
        
        Copyright (c) 2025 Mohammad Korivand
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
Project-URL: Homepage, https://github.com/Mohamma0022/fracjax
Project-URL: Bug Tracker, https://github.com/Mohamma0022/fracjax/issues
Keywords: finance,fractal,jax,econophysics,hurst,wavelet,trading
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Office/Business :: Financial :: Investment
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Development Status :: 4 - Beta
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: jax>=0.4.0
Requires-Dist: jaxlib>=0.4.0
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: scipy
Requires-Dist: tqdm
Dynamic: license-file

# FracJax 🚀

**High-Performance Fractal & Econophysics Tools for Financial Time Series using JAX.**

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Python](https://img.shields.io/badge/python-3.9+-blue.svg)](https://www.python.org/downloads/)
[![JAX](https://img.shields.io/badge/backend-JAX-green.svg)](https://github.com/google/jax)

FracJax is a production-grade Python library designed for quantitative finance and econophysics. It leverages **Google JAX** to perform heavy fractal and multifractal analysis on financial time series with **GPU acceleration**, achieving speeds up to **300x faster** than standard CPU-based libraries (like `nolds` or `hurst`).

> **Key Feature:** FracJax combines modern statistical robustness (Theil-Sen Estimator) with fractal theory (DFA, Wavelet Leaders) to extract noise-free, lag-free market regime signals.

---

## ⚡ Why FracJax?

| Feature | Standard Libs (`nolds`/`hurst`) | FracJax |
| :--- | :--- | :--- |
| **Backend** | CPU (NumPy) | **GPU/TPU (JAX)** |
| **Speed (1M points)** | ~5-10 Minutes | **~1 Second** |
| **Regression** | Least Squares (Sensitive to noise) | **Theil-Sen (Robust to outliers)** |
| **Microscope** | Monofractal only | **Multifractal (Wavelet Leaders)** |
| **Stability** | Fails on short windows (<100) | **Stable on short windows** |

---

## 📦 Features

FracJax calculates 10+ advanced market features across multiple dimensions:

### 1. Fractal & Memory (The "Market Microscope")
* **DFA (Detrended Fluctuation Analysis):** Robust long-term memory estimation (Trend vs. Mean Reversion).
* **Wavelet Leaders:** Multifractal singularity spectrum analysis (Detects structural shocks).
* **Higuchi Fractal Dimension:** Measures market roughness and complexity.

### 2. Microstructure & Liquidity
* **Rolling CVD Proxy:** Estimates aggressive buy/sell pressure from OHLCV.
* **Amihud Illiquidity:** Measures price impact per unit of volume.

### 3. Volatility & Risk
* **GARCH(1,1) Forecast:** Forward-looking volatility prediction.
* **Realized Semivariance (RSV):** Downside-specific volatility measure.
* **Hill Estimator:** Tail risk and fat-tail index estimation.

### 4. Information Theory & Inter-market
* **Permutation Entropy:** Measures time-series chaos and unpredictability.
* **Cointegration Z-Score:** Robust spread analysis between asset pairs.
* **Lead-Lag Mutual Information:** Measures non-linear information flow between assets (using Gaussian KDE).

---

## 🛠 Installation


```bash

pip install fracjax .
```
---
### 🚀 Quick Start
FracJax provides a high-level API create_market_microscope that JIT-compiles kernels for maximum speed.

```Python

import numpy as np
from fracjax import create_market_microscope

# Generate dummy price data (Random Walk)
prices = np.cumsum(np.random.randn(10000)) + 1000

# 1. Initialize Kernels (Compiles once)
# Method options: 'dfa', 'wavelet', 'higuchi', 'garch', 'cvd', etc.
calc_dfa = create_market_microscope(
    method='dfa', 
    window_size=100, 
    batch_size=4096
)

calc_wavelet = create_market_microscope(
    method='wavelet', 
    window_size=100,
    max_level=4
)

# 2. Run on Data (Ultra Fast)
hurst_dfa = calc_dfa(prices)
hurst_wavelet = calc_wavelet(prices)

print(f"DFA Signal (Last): {hurst_dfa[-1]:.4f}")
```
---

### 📊 Visual Showcase
FracJax reveals the hidden anatomy of the market. Below is a dashboard generated using FracJax on 7 years of Forex data (60-day zoom):

(Note: Replace this link with your actual image path after uploading)

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### 🤝 Contributing
Contributions are welcome! Please ensure any PRs maintain JAX functional purity (no side effects) and include type hints.

---

### 📄 License
This project is licensed under the MIT License - see the LICENSE file for details.

---
