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:
- Portfolio optimization with cvxopt☆40Updated last month
- Python library for asset pricing☆127Updated last year
- ☆153Updated 2 years ago
- ☆141Updated 2 years ago
- Research Repo (Archive)☆74Updated 5 years ago
- ☆86Updated last year
- This repository contains the code for the O'Reilly book Reinforcement Learning for Finance.☆76Updated 9 months ago
- Efficient Estimation of Bid-Ask Spreads from Open, High, Low, and Close Prices☆122Updated 3 months ago
- Entropy Pooling in Python with a BSD 3-Clause license.☆41Updated last week
- Algo Trading Research & Documentation☆30Updated 6 months ago
- Collection of notebooks and scripts related to financial engineering, quant-research and algo-trading.☆85Updated 2 weeks ago
- Entropy Pooling views and stress-testing combined with Conditional Value-at-Risk (CVaR) portfolio optimization in Python.☆281Updated this week
- Python implementation of pricing analytics and Monte Carlo simulations for stochastic volatility models including log-normal SV model, He…☆203Updated this week
- Jupyter Notebook examples on how to use the ArbitrageLab - pairs trading - python library.☆141Updated last year
- The code used for the free quants@dev Webinar series on Reinforcement Learning in Finance☆104Updated 3 years ago
- This collects the scripts and notebooks required to reproduce my published work.☆48Updated 2 months ago
- Created a continuous, homogeneous, and structured 10 GB dataset from self obtained collections of unstructured intraday financial data. G…☆75Updated 5 years ago
- Attribution and optimisation using a multi-factor equity risk model.☆35Updated 2 years ago
- A fundamental equity risk model that decomposes the risk of a portfolio by factors and individual securities☆44Updated 7 years ago
- Option pricing with various models (Black-Scholes, Heston, Merton jump diffusion, etc) and methods (Monte Carlo, finite difference, Fouri…☆88Updated 4 years ago
- Time Series Prediction of Volume in LOB☆60Updated last year
- Feature Engineering and Feature Importance in Machine Learning for Financial Markets☆195Updated last year
- This repository contains different tools to simulate underlyings under SV dynamics. As well, we have implemented several tools for comput…☆127Updated 3 months ago
- Statistical Jump Models in Python, with scikit-learn-style APIs☆131Updated last year
- A portfolio optimization tool with scikit-learn interface. Hyperparameters selection and easy plotting of efficient frontiers.☆58Updated 2 years ago
- Python modules and jupyter notebook examples for the paper Detect and Repair Arbitrage in Price Data of Traded Options.☆124Updated 2 years ago
- ☆52Updated 2 years ago
- Code for the paper "How to use the Sharpe ratio"☆85Updated last month
- ☆80Updated 4 years ago
- Financial AI with Python☆99Updated 2 months ago