singhaniatanay / QuantFinance-Trading
Quantative Trading, building a trading strategy by generating alpha, optimizing a portfolio.
☆14Updated last year
Related projects: ⓘ
- factor return calculation, mean-variance / Black&Litterman portfolio optimization, risk decomposition☆27Updated 5 years ago
- Dynamic portfolio optimization☆15Updated 8 months ago
- A financial trading method using machine learning.☆56Updated last year
- A 50ETF Option Volatility Arbitrage Strategy Based on SABR Model☆19Updated last year
- The Implied Volatility Smirk of Individual Option in S&P 500 Shows its Underlying Asset’s Return☆36Updated 3 years ago
- ☆23Updated 6 years ago
- This trading strategy deploy the copula model to define the divergence of two correlated asset. The backtesting system is built on backtr…☆21Updated 2 years ago
- Using Python and Tushare financial database☆24Updated 4 months ago
- This project is to apply Copula Function to pair trading strategy both in American stock market.☆23Updated 5 years ago
- Collection of Models related to market making☆14Updated 3 years ago
- A low frequency statistical arbitrage strategy☆16Updated 5 years ago
- ☆16Updated 4 years ago
- Topic : Option trading Strategies , B&S , Implied Volatility &Stochastic & Local Volatility , Geometric Brownian Motion.☆19Updated 10 months ago
- A project of building and running a trading system according to service oriented architecture standard.☆14Updated 6 years ago
- A constant proportion portfolio insurance (CPPI) trading algorithm on top of Alpaca's Trading API.☆11Updated 3 years ago
- Contains detailed and extensive notes on quantitative trading, leveraging NLP for finance, backtesting, alpha factor research, portfolio …☆36Updated 2 years ago
- Pairs trading strategy that includes a research pipeline for identifying and selecting pairs. Tests all possible pairs in a universe for …☆34Updated 4 months ago
- Firstly, multiple effective factors are discovered through IC value, IR value, and correlation analysis and back-testing. Then, XGBoost c…☆14Updated 4 years ago
- ☆34Updated 3 years ago
- This is a research about using ML or RL predictions for HFT Market Making. Backtest was build on Full order log☆24Updated 3 years ago
- This is for the capstone project "Optimal Execution of a VWAP order".☆29Updated 4 years ago
- ☆15Updated 6 years ago
- Develop about 200 alpha factors from securities report etc, Grid Search/Random Search/Particle Swarm Optimization to improve factors perf…☆16Updated 6 years ago
- AI based alpha research for trading☆42Updated 2 years ago
- XGBoost is known to be fast and achieve good prediction results as compared to the regular gradient boosting libraries. This project atte…☆24Updated 5 years ago
- Backtesting a simple Buy Low Sell High Strategy☆9Updated 2 years ago
- Design your own Trading Strategy☆35Updated 6 months ago
- Rebalancing a portfolio with optimal buy/sell decisions using Metaheuristics☆11Updated 3 years ago
- Contains all the Jupyter Notebooks used in our research☆14Updated 4 years ago
- Find trading pairs with Machine Learning☆39Updated 3 years ago