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:
- DATA-AIDED PAIRS TRADING VIA LEARNED KALMAN WITH BOLLINGER BANDS☆35Updated 2 years ago
- Image Classification for Trading Strategies - Project for Machine Learning Class☆38Updated 4 years ago
- Time-Series Momentum Strategies☆12Updated 7 years ago
- Code to support my Master's thesis☆20Updated 2 years ago
- Implementation of the paper <Model-based Reinforcement Learning for Predictions and Control for Limit Order Books (Wei et al., J.P. Morga…☆11Updated 2 years ago
- Stock Broad-Index Trend Patterns Learning via Domain Knowledge Informed Generative Network☆15Updated 6 months ago
- Limit Order Book for high-frequency trading (HFT) strategies using data science approaches☆23Updated 3 years ago
- Portfolio optimization with cvxopt☆40Updated 7 months ago
- Deep learning models for high-frequency financial data (limited order book)☆19Updated 6 years ago
- This project is essentially the implementation of the paper “Algorithmic Financial Trading with Deep Convolutional Neural Networks: Time …☆20Updated 4 years 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
- Codes for the paper Stock Trading Volume Prediction with Dual-Process Meta-Learning accepted by ECML PKDD 2022☆35Updated 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 7 months ago
- sharpe is a unified, interactive, general-purpose environment for backtesting or applying machine learning(supervised learning and reinfo…☆50Updated 3 years ago
- LSTM stock prediction and backtesting☆14Updated 5 years ago
- Evaluation of Hybrid MODWT-MARS framework for financial time series forecasting☆18Updated 11 months ago
- Application of Machine Learning Algorithms to Intraday Stock Trading Based on Demand Zones☆15Updated 6 years ago
- Fama French model on a subset of Canadian Equity data with Python☆48Updated 6 years ago
- ☆19Updated 8 years ago
- This is a sentiment trading strategy, written in Python, and applying NLP on 10-K's from the SEC EDGAR database.☆10Updated 3 years ago
- Reproduce the result of the paper "Deep Learning with Long Short-Term Memory Networks for Financial Market Prediction"☆19Updated 5 years ago
- Replication of Time Series Momentum strategy by Moskowtiz, Ooi, Pedersen, 2011.☆67Updated 3 months ago
- Pytorch implementation of DeepLOB-ATT and DeepLOB-Seq2Seq from Multi Horizon Forecasting for Limit Order Books☆11Updated 2 years ago
- A Deep Reinforcement Learning neural net for an original Multi-Dimensional Pairs Trading strategy is proposed☆21Updated 6 years ago
- Article on using deep learning to extract order flow information from the limit order book and forecast directional moves☆15Updated 2 years ago
- stock-pairs-trading is a python library for backtest with stock pairs trading using kalman filter on Python 3.8 and above.☆38Updated last year
- LeonardoBerti00 / Data-Normalization-for-Bilinear-Structures-in-High-Frequency-Financial-Time-series-BiN-TABLPytorch implementation of BIN-TABL from Data Normalization for Bilinear Structures in HF Financial Time-series☆12Updated last year
- Random Forest-based "Correlation" measures☆15Updated 3 years ago
- I use the random forest algorithm to forecast mid price dynamic over short time horizon i.e. a few seconds ahead☆30Updated 5 years ago
- Use total, upper, down, relative volatility factors to find Alpha. Implement whole trading process & back-test with visualization.☆12Updated 4 years ago