hjeffreywang / Stock_feature_engineeringLinks
Created a continuous, homogeneous, and structured 10 GB dataset from self obtained collections of unstructured intraday financial data. Generated features from indicators, statistics, and recent factors. Used multi-disciplined analysis to find feature importance. Attached labels of trends and stop/hold positions for machine learning. Used machin…
☆74Updated 5 years ago
Alternatives and similar repositories for Stock_feature_engineering
Users that are interested in Stock_feature_engineering are comparing it to the libraries listed below
Sorting:
- CS7641 Team project☆97Updated 5 years ago
- ☆49Updated 6 years ago
- ☆121Updated 7 years ago
- Jupyter Notebook examples on how to use the ArbitrageLab - pairs trading - python library.☆134Updated last year
- Notes on Advances in Financial Machine Learning☆82Updated 6 years ago
- A statistical arbitrage strategy on treasury futures using mean-reversion property and meanwhile insensitive to the yield change☆79Updated 7 years ago
- Backtest result archive for Momentum Trading Strategies☆64Updated 6 years ago
- A collection of homeworks of market microstructure models.☆269Updated 7 years ago
- Baruch MFE 2019 Spring☆43Updated 5 years ago
- This repository stores the implementation of the paper "DETECTING DATA-DRIVEN ROBUST STATISTICAL ARBITRAGE STRATEGIES WITH DEEP NEURAL NE…☆69Updated last year
- Code base for the meta-labeling papers published with the Journal of Financial Data Science☆92Updated 2 years ago
- Research Repo (Archive)☆75Updated 5 years ago
- Delta hedging under SABR model☆40Updated last year
- Volume-Synchronized Probability of Informed Trading☆112Updated 12 years ago
- Python modules and jupyter notebook examples for the paper Detect and Repair Arbitrage in Price Data of Traded Options.☆121Updated last year
- Time Series Prediction of Volume in LOB☆58Updated last year
- Pairs Trading with Machine Learning on Distributed Python Platform☆122Updated 3 years ago
- Contains detailed and extensive notes on quantitative trading, leveraging NLP for finance, backtesting, alpha factor research, portfolio …☆48Updated 3 years ago
- Machine learning-driven financial trading strategy: momentum prediction, regime detection, and enhanced trading decisions.☆70Updated 2 years ago
- Build a statistical risk model using PCA. Optimize the portfolio using the risk model and factors using multiple optimization formulation…☆134Updated 6 years ago
- Solutions for selected exercises from Advances in Financial Machine Learning by Marcos Lopez De Prado☆77Updated 3 years ago
- This project used GARCH type models to estimate volatility and used delta hedging method to make a profit.☆68Updated 5 years ago
- High-frequency statistical arbitrage☆232Updated 2 years ago
- three stochastic volatility model: Heston, SABR, SVI☆91Updated 6 years ago
- To classify trades into buyer- and seller-initiated.☆154Updated 2 years ago
- Notebook based on the book "Advances in Financial Machine Learning" by Marcos Lopez de Prado☆125Updated 6 years ago
- Repository containing the code for a pairs trading investment strategy (Master Thesis in Electrical and Computer Engineering - Técnico Li…☆171Updated 6 years ago
- We release `LOBFrame', a novel, open-source code base which presents a renewed way to process large-scale Limit Order Book (LOB) data.☆206Updated last year
- Academic python library that records changes to instances of the limit order book for pairs supported on the coinbase exchange.☆54Updated 4 years ago
- Collection of notebooks and scripts related to financial engineering, quant-research and algo-trading.☆75Updated last year