FlorinAndrei / fast_feature_selection
Genetic algorithms and CMA-ES (covariance matrix adaptation evolution strategy) for efficient feature selection
☆14Updated last year
Alternatives and similar repositories for fast_feature_selection:
Users that are interested in fast_feature_selection are comparing it to the libraries listed below
- This code illustrates the use of genetic programming to evolve financial trading strategies for a single equity stock. Individuals (strat…☆24Updated 6 years ago
- Reproduce the result of the paper "Deep Learning with Long Short-Term Memory Networks for Financial Market Prediction"☆19Updated 4 years ago
- A CNN + Auto-Encoder Approach for Predicting Financial Time-Series☆12Updated 5 years ago
- Bayer, Friz, Gulisashvili, Horvath, Stemper (2017). Short-time near-the-money skew in rough fractional volatility models.☆12Updated 8 years ago
- Dynamic lead/lag inference for time series☆16Updated 6 years ago
- Alpha mining with DEAP-based genetic programming.☆9Updated last year
- This is a non-official implementation of the trend labeling method proposed in the paper "A Labeling Method for Financial Time Series Pre…☆37Updated 3 months ago
- ☆12Updated 4 years ago
- ☆19Updated 4 years ago
- Market making strategies and scientific papers☆13Updated last year
- Implementation of DBSCAN to find securities with a historical correlation for a pairs trading strategy☆13Updated 5 years ago
- Stock Price Prediction with PCA and LSTM☆14Updated 4 years ago
- ☆12Updated 5 years ago
- Allows the generation of optimal portfolios with CoIn, Gumbel, and no copula constraint for the stochastic interest rate - constant elast…☆13Updated last year
- Build an algorithm that can predict multiple future states of Limit Order Books using high-frequency, multi-variate, short time-frame dat…☆11Updated last year
- Markov decision processes under model uncertainty☆15Updated 2 years ago
- ☆12Updated last year
- Using DeepBSDE solver to price/hedge options & optimize portfolios under Black-Scholes, Heston and multiscale models.☆12Updated 5 years ago
- Deep Learning + Time Series Analysis☆27Updated 6 years ago
- Financial time-series forecasting has long been a challenging problem because of the inherently noisy and stochastic nature of the market…☆16Updated 3 years ago
- Various utilities for time series forecasting☆10Updated 2 years ago
- Stock Market Prediction on High-Frequency Data Using soft computing based AI models☆20Updated 7 months ago
- reinforcement learning project for crypto portfolio management☆9Updated 6 years ago
- Use total, upper, down, relative volatility factors to find Alpha. Implement whole trading process & back-test with visualization.☆12Updated 3 years ago
- Time-series analysis using restricted Boltzmann machines and dynamic Bayesian networks☆12Updated last year
- (Work In Progress) Implementation of "Financial Time Series Prediction Using Deep Learning"☆16Updated 7 years ago
- Collection of numerical methods for high frequency data, in Python notebooks☆13Updated 4 years ago
- Neural networks can detect model-free arbitrage static strategies☆15Updated last year
- XTX Forecasting Challenge https://challenge.xtxmarkets.com/☆9Updated 5 years ago
- 多因子选股框架☆20Updated 4 years ago