MilindYadav-97 / Hybrid_FastRNN-for-stock-predictionsLinks
☆14Updated 5 years ago
Alternatives and similar repositories for Hybrid_FastRNN-for-stock-predictions
Users that are interested in Hybrid_FastRNN-for-stock-predictions are comparing it to the libraries listed below
Sorting:
- Image Classification for Trading Strategies - Project for Machine Learning Class☆38Updated 4 years ago
- DATA-AIDED PAIRS TRADING VIA LEARNED KALMAN WITH BOLLINGER BANDS☆35Updated 3 years ago
- Evaluation of Hybrid MODWT-MARS framework for financial time series forecasting☆18Updated last year
- Code to support my Master's thesis☆21Updated 2 years ago
- sharpe is a unified, interactive, general-purpose environment for backtesting or applying machine learning(supervised learning and reinfo…☆50Updated 4 years ago
- Stock Broad-Index Trend Patterns Learning via Domain Knowledge Informed Generative Network☆15Updated 8 months ago
- ☆19Updated 8 years ago
- This project is essentially the implementation of the paper “Algorithmic Financial Trading with Deep Convolutional Neural Networks: Time …☆21Updated 5 years ago
- Portfolio optimization with cvxopt☆40Updated 9 months ago
- We use an adversarial expert based online learning algorithm to learn the optimal parameters required to maximise wealth trading zero-cos…☆10Updated 5 years ago
- Rebalancing a portfolio with optimal buy/sell decisions using Metaheuristics☆12Updated 4 years ago
- Time-Series Momentum Strategies☆12Updated 7 years ago
- A Deep Reinforcement Learning model for high volume and frequency Forex Portfolio Management☆12Updated 2 years ago
- Limit Order Book for high-frequency trading (HFT) strategies using data science approaches☆24Updated 3 years ago
- This is a non-official implementation of the trend labeling method proposed in the paper "A Labeling Method for Financial Time Series Pre…☆49Updated 9 months ago
- Stock Market Prediction on High-Frequency Data Using soft computing based AI models☆22Updated last year
- stock-pairs-trading is a python library for backtest with stock pairs trading using kalman filter on Python 3.8 and above.☆38Updated 2 years ago
- Codes for the paper Stock Trading Volume Prediction with Dual-Process Meta-Learning accepted by ECML PKDD 2022☆35Updated 3 years ago
- ☆19Updated 5 years ago
- Transformer and MultiTransformer layers for stock volatility forecasting purposes☆73Updated 4 years ago
- Implementation of the paper <Model-based Reinforcement Learning for Predictions and Control for Limit Order Books (Wei et al., J.P. Morga…☆12Updated 2 years ago
- Machine learning trading method using meta-labeling. You can see the details in 'Advances in Financial Machine Learning' by Lopez de Prad…☆15Updated 4 years ago
- This notebook contains an independently developed Keras/Tensorflow implementation of the CNN-LSTM model for Limit Order Book forecasting …☆35Updated 5 years ago
- Code repository for demos of the article 'Arbitrage-Free Implied Volatility Surface Generation with Variational Autoencoders'.☆37Updated 2 years ago
- LSTM stock prediction and backtesting☆14Updated 5 years ago
- Pytorch implementation of Axial-LOB from 'Axial-LOB: High-Frequency Trading with Axial Attention'☆58Updated 2 years ago
- Source code for Deep Fundamental Factor Models, https://arxiv.org/abs/1903.07677☆65Updated 3 years ago
- Pytorch implementation of deep learning models for financial time series forecasting using LOB☆17Updated 2 years ago
- Deep learning models for high-frequency financial data (limited order book)☆19Updated 6 years ago
- Replication of Time Series Momentum strategy by Moskowtiz, Ooi, Pedersen, 2011.☆67Updated 5 months ago