python package for DFA (Detrended Fluctuation Analysis) and related algorithms
Markowitzify will implement a variety of portfolio and stock/cryptocurrency analysis methods to optimize portfolios or trading strategies. The two primary classes are "portfolio" and "stonks."
Epileptic Seizure Recognition System, In this project wavelet transform and Hurst exponent are used as an input of SVM, LSTM , Random Forest Models.
A mathematical framework for measuring the dynamics of consciousness. The framework uses a composite index of scale-free temporal organisation, cross-frequency organisation, and metastability.
Python library for DFA, Hurst exponent, and fluctuation analysis of time series.
Computational Finance Lecture for MSc in AI, at University of Southampton
High-Performance Fractal & Econophysics Tools for Financial Time Series using JAX (GPU-Accelerated).
fractalVideoGuard
Hurst value as a result of data smoothing
6-month learning journey from basic math to multifractal analysis (MF-DFA) of financial markets
Algorithmic trading bot for Roostoo Hackathon 2026 — Hurst Exponent regime filter + non-parametric mean-reversion strategy on TRX/USD
Bloomberg-style markets terminal — 4-tier data failover (Yahoo · CoinGecko · Stooq · Alpha Vantage) · Yang-Zhang / Garman-Klass volatility · Autocorrelation / Partial Autocorrelation · Hurst exponent · Carhart 4-factor with Newey-West HAC · Probabilistic / Deflated Sharpe · walk-forward cross-validation · decile Information Coefficient.
Quantum vs Classical, Autoregressive vs Reconstructive Encoder/Decoder Architectures on Non-Stationary Time-Series: Loss Landscapes and Latent Complexities with and without Recurrence
Ratio mean-reversion testing for asset pairs. Hurst exponent + ADF + walk-forward backtest.
Institutional-grade quantitative finance calculator — Black-Scholes · Greeks · IV Solver · Avellaneda-Stoikov HFT · Kelly Criterion · GARCH · Hurst · OU Process · Ghana Cocoa Derivatives. Expo React Native (iOS · Android · Web).
Tests if EUR/USD daily moves are as random as coin flips using Monte Carlo and statistical tests (runs, Markov chains, Ljung–Box, Hurst, entropy). Results show returns look random, but volatility clusters, revealing structure beyond pure chance.
Small CLI utility used to evaluate Hurst Exponent based on CSV files ( (this is just a mirror of https://hub.mos.ru/fominmv2498/hurst) )
Python reproduction of the self-organizing 3D Ising model of financial markets (Guimaraes & Lima, PRE 2021). Generates fat-tailed return distributions, volatility clustering, and long-range memory via Monte Carlo simulation with Numba acceleration.
Hurst exponent: from mathematical foundations to a systematic basket trading strategy with statistical validation.
To associate your repository with the hurst-exponent topic, visit your repo's landing page and select "manage topics."