sjdee / Research-Stock-PredictionLinks
☆10Updated 6 years ago
Alternatives and similar repositories for Research-Stock-Prediction
Users that are interested in Research-Stock-Prediction are comparing it to the libraries listed below
Sorting:
- The code for Fuzzy Investment Counselor (FIC) and Markowitz portfolio theory for stock investment☆14Updated 5 years ago
- Time-Series Momentum Strategies☆12Updated 7 years ago
- ☆14Updated 5 years ago
- Pytorch implementation of deep learning models for financial time series forecasting using LOB☆14Updated 2 years ago
- Pull price targets from IEXCloud and paper trade on Alpaca 🦙☆13Updated 4 years ago
- 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
- A machine learning pipeline that ingest and process a 20-year historical stock price dataset and try to predict future prices using Light…☆12Updated 4 years ago
- Limit Order Book for high-frequency trading (HFT) strategies using data science approaches☆23Updated 3 years ago
- Codes for the paper Stock Trading Volume Prediction with Dual-Process Meta-Learning accepted by ECML PKDD 2022☆35Updated 3 years ago
- ☆10Updated 2 years ago
- ☆21Updated 3 months ago
- Paper: https://arxiv.org/pdf/2008.12275.pdf☆26Updated 5 years ago
- ☆19Updated 8 years ago
- Deep learning models for high-frequency financial data (limited order book)☆19Updated 6 years ago
- ☆38Updated last year
- Pytorch implementation of DeepLOB-ATT and DeepLOB-Seq2Seq from Multi Horizon Forecasting for Limit Order Books☆11Updated 2 years ago
- Evaluation of Hybrid MODWT-MARS framework for financial time series forecasting☆18Updated 11 months ago
- The PyTorch implementation of "Modeling Financial Time Series using LSTM with Trainable Initial Hidden States"☆11Updated 5 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
- ☆10Updated 6 years ago
- Use total, upper, down, relative volatility factors to find Alpha. Implement whole trading process & back-test with visualization.☆12Updated 4 years ago
- a unified environment for supervised learning and reinforcement learning in the context of quantitative trading☆45Updated 4 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
- Stock Market predictions are one of the most difficult problems to solve, and during the looming days of recession it’s extremely difficu…☆15Updated 5 years ago
- Advancing in Financial Machine Learning☆16Updated 5 years ago
- DATA-AIDED PAIRS TRADING VIA LEARNED KALMAN WITH BOLLINGER BANDS☆35Updated 2 years ago
- Fama French model on a subset of Canadian Equity data with Python☆48Updated 6 years ago
- Model news data in short, medium and long term for stock price trend prediction☆20Updated 7 years ago
- Apply Box&Tiao to generate stationary price spread series in steel industry commodity futures market for pair trading☆13Updated 2 years ago
- sharpe is a unified, interactive, general-purpose environment for backtesting or applying machine learning(supervised learning and reinfo…☆50Updated 3 years ago