HFTHaidra / Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Strategy
Stock trading strategies play a critical role in investment. However, it is challenging to design a profitable strategy in a complex and dynamic stock market. In this paper, we propose a deep ensemble reinforcement learning scheme that automatically learns a stock trading strategy by maximizing investment return. We train a deep reinforcement le…
☆35Updated 2 years ago
Related projects: ⓘ
- The repository contains the code for project for DS 5500 course at Northeastern.☆35Updated 4 years ago
- ☆30Updated 4 years ago
- Deep Direct Recurrent Reinforcement Learning to learn trading system☆26Updated 6 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…☆27Updated 4 years ago
- Trend Prediction for High Frequency Trading☆38Updated last year
- This repository represents work in progress for the Worldquant University Capstone Project titled: Asset Portfolio Management using Deep …☆70Updated last year
- apolanco3225 / Deep-Reinforcement-Learning-for-Optimal-Execution-of-Portfolio-Transactions-using-DDPGPerforming a trading strategy using deep deterministic policy gradients to know when to buy, hold or sell stocks in a virtual environment…☆54Updated 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…☆24Updated 5 years ago
- This repository contains the main code used in the paper "Deep Reinforcement Learning for Market Making Under a Hawkes Process-Based Limi…☆51Updated last year
- Automated FOREX trading using recurrent reinforcement learning☆33Updated last year
- FinML: A Practical Machine Learning Framework for Dynamic Stock Selection☆101Updated 6 months ago
- A financial trading method using machine learning.☆56Updated last year
- Momentum following strategies and optimal execution cost upon Implement Shortfall algorithm☆15Updated 5 years ago
- A genetic programming algorithm used for generating alpha factors in the multi-factor investment strategy☆54Updated 3 years ago
- Build DDPG models and test on stock market☆22Updated 5 years ago
- Artificial-Intelligence-Big-Data-Lab / A-Multi-Layer-and-Multi-Ensembled-Stock-Trader-Using-Deep-Learning-and-Deep-Reinforcement-Learning☆51Updated 4 years ago
- Deep Reinforcement Learning Framework for Factor Investing☆20Updated last year
- Collection of indicators that I used in my strategies.☆48Updated last year
- Pair Trading Strategy using Machine Learning written in Python☆109Updated 2 years ago
- ☆51Updated last year
- Deep Reinforcement Learning for Stock trading task☆18Updated 3 years ago
- ☆13Updated 5 years ago
- Option hedging strategies are investigated using two reinforcement learning algorithms: deep Q network and deep deterministic policy grad…☆19Updated 4 years ago
- Contains detailed and extensive notes on quantitative trading, leveraging NLP for finance, backtesting, alpha factor research, portfolio …☆36Updated 2 years ago
- ☆175Updated 2 weeks ago
- An RL model that uses double deep Q learning to generate an optimal policy of stock market trades☆89Updated last year
- This project explores stock trading modelling with the use recurrent neural network (RNN) with long-short term memory (LSTM) architecture…☆27Updated 5 years ago
- Using Reinforcement Learning with Deep Deterministic Policy Gradient for Portfolio Optimization☆9Updated last year
- This project is to apply Copula Function to pair trading strategy both in American stock market.☆23Updated 5 years ago
- This project implements the two deep reinforcement learning algorithms on portfolio management☆41Updated 6 years ago