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 9 months ago
- ☆145Updated last year
- ☆141Updated 2 years ago
- Algo Trading Research & Documentation☆21Updated 3 months ago
- Efficient Estimation of Bid-Ask Spreads from Open, High, Low, and Close Prices☆121Updated last month
- Research Repo (Archive)☆75Updated 5 years ago
- Python library for asset pricing☆120Updated last year
- Python implementation of pricing analytics and Monte Carlo simulations for stochastic volatility models including log-normal SV model, He…☆187Updated 2 months ago
- ☆82Updated 11 months ago
- Financial AI with Python☆93Updated this week
- Entropy Pooling views and stress-testing combined with Conditional Value-at-Risk (CVaR) portfolio optimization in Python.☆266Updated last month
- Option pricing with various models (Black-Scholes, Heston, Merton jump diffusion, etc) and methods (Monte Carlo, finite difference, Fouri…☆87Updated 3 years ago
- Quant Research☆90Updated last week
- This repository contains different tools to simulate underlyings under SV dynamics. As well, we have implemented several tools for comput…☆122Updated last month
- Jupyter Notebook examples on how to use the ArbitrageLab - pairs trading - python library.☆133Updated last year
- This collects the scripts and notebooks required to reproduce my published work.☆48Updated 3 weeks ago
- A portfolio optimization tool with scikit-learn interface. Hyperparameters selection and easy plotting of efficient frontiers.☆58Updated last year
- ☆77Updated 4 years ago
- Code base for the meta-labeling papers published with the Journal of Financial Data Science☆92Updated 2 years ago
- Feature Engineering and Feature Importance in Machine Learning for Financial Markets☆189Updated last year
- Script for Calculating Implied Probability Distribution from Option Prices - The Quant's Playbook @ Quant Galore☆40Updated last year
- Probabilistic Sharpe Ratio example in Python (by Marcos López de Prado)☆127Updated 5 years ago
- Time Series Prediction of Volume in LOB☆58Updated last year
- ☆50Updated 2 years ago
- Macrosynergy Quant Research☆160Updated this week
- This repository contains the code for the O'Reilly book Reinforcement Learning for Finance.☆66Updated 6 months ago
- Python modules and jupyter notebook examples for the paper Detect and Repair Arbitrage in Price Data of Traded Options.☆120Updated last year
- ☆215Updated 8 years ago
- Predictive yield curve modeling in reduced dimensionality☆45Updated 2 years ago
- By means of stochastic volatility models☆44Updated 5 years ago