Moozzart / Meyer-Packard-Genetic-Algorithm-for-Prediction-of-Stock-Prices-and-Performances
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
- Use total, upper, down, relative volatility factors to find Alpha. Implement whole trading process & back-test with visualization.☆12Updated 3 years ago
- Market making strategies and scientific papers☆13Updated last year
- Exercises in 'Advances in Financial Machine Learning' by Lopez de Prado☆3Updated last year
- Predicting a Stock Price Using a Genetic Algorithm☆16Updated 6 years ago
- LSTM stock prediction and backtesting☆14Updated 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
- Backtesting a simple Buy Low Sell High Strategy☆9Updated 3 years ago
- ☆17Updated 8 years ago
- Short-term momentum trading strategy implemented for the lecture "Systematic risk premia strategies traded at hedge funds" at University …☆37Updated 2 years ago
- A financial trading method using machine learning.☆59Updated last year
- Limit Order Book for high-frequency trading (HFT) strategies using data science approaches☆21Updated 3 years ago
- Reproduce the result of the paper "Deep Learning with Long Short-Term Memory Networks for Financial Market Prediction"☆19Updated 4 years ago
- Implementation of code snippets and exercises in the book Machine Learning for Asset Managers written by Prof. Marcos López de Prado.☆15Updated 4 years ago
- Building a High Frequency Trading Engine with Neural Networks☆12Updated 6 years ago
- Momentum following strategies and optimal execution cost upon Implement Shortfall algorithm☆15Updated 5 years ago
- A Deep Reinforcement Learning neural net for an original Multi-Dimensional Pairs Trading strategy is proposed☆21Updated 6 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
- Different trading strategies using technical analysis. Data: Ethereum/USD 5 minutes bars☆16Updated 3 years ago
- This project is to apply Copula Function to pair trading strategy both in American stock market.☆24Updated 6 years ago
- Apply Box&Tiao to generate stationary price spread series in steel industry commodity futures market for pair trading☆12Updated 2 years ago
- Stock Market Prediction on High-Frequency Data Using soft computing based AI models☆18Updated 4 months ago
- Apply LASSO in High-Frequency-Trading☆9Updated 5 years ago
- 2 algorithms of optimal trade execution: 1) Dynamic Programming 2) Frank-Wolfe Algorithm (Python & C++)☆17Updated 5 years ago
- XGBoost is known to be fast and achieve good prediction results as compared to the regular gradient boosting libraries. This project atte…☆30Updated 5 years ago
- This is the final project of Statistical Arbitrage course and it aims to apply pairs trading in high frequency data to realize auto-tradi…☆18Updated 6 years ago
- This project is essentially the implementation of the paper “Algorithmic Financial Trading with Deep Convolutional Neural Networks: Time …☆17Updated 4 years ago
- A Deep Reinforcement Learning model for high volume and frequency Forex Portfolio Management☆11Updated 2 years ago
- A 50ETF Option Volatility Arbitrage Strategy Based on SABR Model☆23Updated 2 years ago
- ☆13Updated last year
- ☆26Updated 4 months ago