Moozzart / Meyer-Packard-Genetic-Algorithm-for-Prediction-of-Stock-Prices-and-PerformancesLinks
Stock Market predictions are one of the most difficult problems to solve, and during the looming days of recession it’s extremely difficult and next to impossible to do. This is because there are numerous patterns in the stock prices trend throughout the day and every variation from the normal trend could mean something new, since stocks is ever…
☆15Updated 4 years ago
Alternatives and similar repositories for Meyer-Packard-Genetic-Algorithm-for-Prediction-of-Stock-Prices-and-Performances
Users that are interested in Meyer-Packard-Genetic-Algorithm-for-Prediction-of-Stock-Prices-and-Performances are comparing it to the libraries listed below
Sorting:
- Market making strategies and scientific papers☆13Updated last year
- Momentum following strategies and optimal execution cost upon Implement Shortfall algorithm☆15Updated 6 years ago
- Use total, upper, down, relative volatility factors to find Alpha. Implement whole trading process & back-test with visualization.☆12Updated 4 years ago
- LSTM stock prediction and backtesting☆14Updated 5 years ago
- Backtesting a simple Buy Low Sell High Strategy☆9Updated 3 years ago
- Machine learning trading method using meta-labeling. You can see the details in 'Advances in Financial Machine Learning' by Lopez de Prad…☆13Updated 3 years ago
- Apply LASSO in High-Frequency-Trading☆9Updated 5 years ago
- This project analysed financial data and designed trading strategies by machine learning models.☆10Updated 6 years ago
- An equity analysis on momentum factor investing.☆10Updated 6 years ago
- Predicting a Stock Price Using a Genetic Algorithm☆16Updated 7 years ago
- Stock Market Prediction on High-Frequency Data Using soft computing based AI models☆20Updated 9 months ago
- Limit Order Book for high-frequency trading (HFT) strategies using data science approaches☆22Updated 3 years ago
- A Deep Reinforcement Learning model for high volume and frequency Forex Portfolio Management☆11Updated 2 years ago
- 2 algorithms of optimal trade execution: 1) Dynamic Programming 2) Frank-Wolfe Algorithm (Python & C++)☆17Updated 5 years ago
- A genetic algorithm that evolves generations of regression neural networks containing a combination of recurrent and dense layers.☆8Updated 6 years ago
- Alpaca-based Order Book Inbalace Algorithm.☆12Updated 4 years ago
- Apply Box&Tiao to generate stationary price spread series in steel industry commodity futures market for pair trading☆12Updated 2 years ago
- ☆12Updated last year
- High Frequency Trading bot for 2019 Traders at MIT, HFT Case. I placed 4th in the HFT competition (2nd overall) out of 120.☆19Updated 5 years ago
- Design your own Trading Strategy☆38Updated last year
- Exercises in 'Advances in Financial Machine Learning' by Lopez de Prado☆3Updated 2 years ago
- ML pipeline for SmartBeta momentum factor on equity portfolio☆11Updated 9 years ago
- Machine learning-driven financial trading strategy: momentum prediction, regime detection, and enhanced trading decisions.☆64Updated 2 years ago
- Deep Reinforcement Learning Framework for Factor Investing☆26Updated 2 years ago
- A low frequency statistical arbitrage strategy☆20Updated 6 years ago
- Crypto-Options Volatility Surface Calibration and Arbitrage☆13Updated 2 years ago
- ☆18Updated 8 years ago
- The course, authored by Prof. Jerzy in NYU, applies the R programming language to momentum trading, statistical arbitrage (pairs trading)…☆13Updated 6 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
- Machine learning approach to high frequency trading, MLP & RNN used☆22Updated 8 years ago