saeed349 / Advances-in-Financial-Machine-LearningLinks
Using Dask, a Python framework, I handle 900 million rows of S&P E-mini futures trade tick data directly on a local machine. Through exploratory data analysis, continuous series creation, and bar sampling, inspired by Marcos Lopez de Prado's work, I demonstrate efficient alternatives to costly data processing methods.
☆41Updated last year
Alternatives and similar repositories for Advances-in-Financial-Machine-Learning
Users that are interested in Advances-in-Financial-Machine-Learning are comparing it to the libraries listed below
Sorting:
- ☆146Updated last year
- Python library for asset pricing☆123Updated last year
- Portfolio optimization with cvxopt☆40Updated 10 months ago
- Entropy Pooling views and stress-testing combined with Conditional Value-at-Risk (CVaR) portfolio optimization in Python.☆269Updated 2 weeks ago
- ☆141Updated 2 years ago
- Research Repo (Archive)☆75Updated 5 years ago
- Python implementation of pricing analytics and Monte Carlo simulations for stochastic volatility models including log-normal SV model, He…☆191Updated 3 months ago
- Portfolio Construction and Risk Management book's Python code.☆151Updated last month
- Algo Trading Research & Documentation☆22Updated 4 months ago
- This repository contains different tools to simulate underlyings under SV dynamics. As well, we have implemented several tools for comput…☆124Updated last month
- Financial AI with Python☆96Updated 2 weeks ago
- Efficient Estimation of Bid-Ask Spreads from Open, High, Low, and Close Prices☆121Updated last month
- ☆47Updated 2 years ago
- Macrosynergy Quant Research☆161Updated this week
- Option pricing with various models (Black-Scholes, Heston, Merton jump diffusion, etc) and methods (Monte Carlo, finite difference, Fouri…☆88Updated 3 years ago
- Python modules and jupyter notebook examples for the paper Detect and Repair Arbitrage in Price Data of Traded Options.☆121Updated last year
- Jupyter Notebook examples on how to use the ArbitrageLab - pairs trading - python library.☆134Updated last year
- Created a continuous, homogeneous, and structured 10 GB dataset from self obtained collections of unstructured intraday financial data. G…☆74Updated 5 years ago
- Predictive yield curve modeling in reduced dimensionality☆45Updated 2 years ago
- Collection of notebooks and scripts related to financial engineering, quant-research and algo-trading.☆75Updated last year
- Feature Engineering and Feature Importance in Machine Learning for Financial Markets☆191Updated last year
- A portfolio optimization tool with scikit-learn interface. Hyperparameters selection and easy plotting of efficient frontiers.☆58Updated last year
- This repository contains the code for the O'Reilly book Reinforcement Learning for Finance.☆68Updated 7 months ago
- ☆84Updated last year
- Statistical Jump Models in Python, with scikit-learn-style APIs☆117Updated 10 months ago
- Rewriting the code in "Machine Learning for Factor Investing" in Python☆93Updated 4 years ago
- This collects the scripts and notebooks required to reproduce my published work.☆48Updated 2 weeks ago
- detecting regime of financial market☆41Updated 3 years ago
- Probabilistic Sharpe Ratio example in Python (by Marcos López de Prado)☆127Updated 5 years ago
- Real-time & historical data API for US stocks and options☆63Updated last year