DavidCico / Forecasting-direction-of-trade-an-example-with-LSTM-neural-network
In this repository, the goal is to predict the tick direction of a stock based on its current order book and trade data. A LSTM Neural Network is used as an example of potential solution for such problem.
☆18Updated 3 years ago
Alternatives and similar repositories for Forecasting-direction-of-trade-an-example-with-LSTM-neural-network:
Users that are interested in Forecasting-direction-of-trade-an-example-with-LSTM-neural-network are comparing it to the libraries listed below
- This project is to apply Copula Function to pair trading strategy both in American stock market.☆24Updated 6 years ago
- Code base for the meta-labeling papers published with the Journal of Financial Data Science☆78Updated last year
- A financial trading method using machine learning.☆58Updated last year
- 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
- ☆17Updated 8 years ago
- Various python scripts to introduce mean reversion concepts.☆22Updated 6 years ago
- A 50ETF Option Volatility Arbitrage Strategy Based on SABR Model☆23Updated 2 years ago
- Deep Reinforcement Learning Framework for Factor Investing☆25Updated last year
- Mean Reversion Trading Strategy☆20Updated 3 years ago
- Modeling the S&P500 index as a hidden markov model for regime identification and creating a trading algorithm to capitalize on hidden sta…☆32Updated 4 years ago
- Implements different approaches to tactical and strategic asset allocation☆30Updated last month
- Trend Prediction for High Frequency Trading☆37Updated 2 years ago
- Backtest result archive for Momentum Trading Strategies☆49Updated 5 years ago
- A model simulation shows how pairs trading could be used for two S&P500 traded stocks. It proofs that the strategy is successful on real…☆24Updated 4 years ago
- Mock pairs trading strategy and backtesting with Kalman iltering and pair selection using clustering and cointegration.☆11Updated 2 years ago
- A low frequency statistical arbitrage strategy☆19Updated 5 years ago
- ☆21Updated 3 years ago
- Project description: https://medium.com/@tzhangwps/measuring-financial-turbulence-and-systemic-risk-9d9688f6eec1?source=friends_link&sk=1…☆25Updated 8 months 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
- ☆39Updated 3 years ago
- ☆15Updated last year
- Collection of indicators that I used in my strategies.☆51Updated last year
- ☆47Updated 3 years ago
- Develop about 200 alpha factors from securities report etc, Grid Search/Random Search/Particle Swarm Optimization to improve factors perf…☆19Updated 6 years ago
- ☆21Updated 5 years ago
- The Implied Volatility Smirk of Individual Option in S&P 500 Shows its Underlying Asset’s Return☆37Updated 4 years ago
- This repository stores the implementation of the paper "DETECTING DATA-DRIVEN ROBUST STATISTICAL ARBITRAGE STRATEGIES WITH DEEP NEURAL NE…☆56Updated 11 months ago
- Developing hybrid deep learning models by integrating Neural networks with (s,e,t)GARCH models to predict volatility in the Indian Commod…☆17Updated 3 years ago
- public version of MLFINLAB from Hudson-Thames☆21Updated 3 years ago
- Package to build risk model for factor pricing model☆24Updated 6 months ago