hjeffreywang / Stock_feature_engineering
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…
☆70Updated 4 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
- ☆43Updated 5 years ago
- Jupyter Notebook examples on how to use the ArbitrageLab - pairs trading - python library.☆114Updated last year
- CS7641 Team project☆94Updated 4 years ago
- Time Series Prediction of Volume in LOB☆57Updated last year
- Features and labels engineering of raw data of quotes of several stocks.☆29Updated 5 years ago
- ☆113Updated 7 years ago
- A statistical arbitrage strategy on treasury futures using mean-reversion property and meanwhile insensitive to the yield change☆76Updated 6 years ago
- Code base for the meta-labeling papers published with the Journal of Financial Data Science☆80Updated 2 years ago
- Notes on Advances in Financial Machine Learning☆79Updated 6 years ago
- Research Repo (Archive)☆73Updated 4 years ago
- Baruch MFE 2019 Spring☆39Updated 4 years ago
- Backtest result archive for Momentum Trading Strategies☆54Updated 6 years ago
- Python modules and jupyter notebook examples for the paper Detect and Repair Arbitrage in Price Data of Traded Options.☆118Updated last year
- Python implementation of pricing analytics and Monte Carlo simulations for stochastic volatility models including log-normal SV model, He…☆158Updated 3 weeks ago
- Collection of notebooks and scripts related to financial engineering, quant-research and algo-trading.☆61Updated 9 months ago
- Volume-Synchronized Probability of Informed Trading☆111Updated 11 years ago
- High-frequency statistical arbitrage☆186Updated last year
- Machine learning-driven financial trading strategy: momentum prediction, regime detection, and enhanced trading decisions.☆60Updated 2 years ago
- This project used GARCH type models to estimate volatility and used delta hedging method to make a profit.☆63Updated 5 years ago
- Notebooks based on financial machine learning.☆50Updated 4 years ago
- Pair Trading Strategy using Machine Learning written in Python☆117Updated 2 years ago
- High Frequency Pairs Trading Based on Statistical Arbitrage (Python)☆102Updated 6 years ago
- ☆38Updated 2 years ago
- #易经 #道家 #十二生肖 #姓氏堂号子嗣贞节牌坊 #天文历法 #张灯结彩 #农历 #夜观星象 #廿四节气 #算卜 #紫微斗数 #十二时辰 #生辰八字 #命运 #风水 《始祖赢政之子赢家黄氏江夏堂联富•秦谏——大秦赋》 万般皆下品，唯有读书高。🚩🇨🇳🏹🦔中科红旗，…☆46Updated 3 weeks ago
- Delta hedging under SABR model☆30Updated 11 months ago
- A collection of homeworks of market microstructure models.☆235Updated 7 years ago
- Notebook based on the book "Advances in Financial Machine Learning" by Marcos Lopez de Prado☆124Updated 5 years ago
- Pairs trading strategy that includes a research pipeline for identifying and selecting pairs. Tests all possible pairs in a universe for …☆36Updated last year
- This repository stores the implementation of the paper "DETECTING DATA-DRIVEN ROBUST STATISTICAL ARBITRAGE STRATEGIES WITH DEEP NEURAL NE…☆62Updated last year
- Example of order book modeling.☆56Updated 5 years ago