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.
☆39Updated 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☆38Updated 4 months ago
- Python library for asset pricing☆115Updated last year
- ☆81Updated 6 months ago
- Collection of notebooks and scripts related to financial engineering, quant-research and algo-trading.☆64Updated 10 months ago
- ☆40Updated 2 years ago
- Machine Learning Trading Toolkit☆36Updated 2 weeks ago
- A portfolio optimization tool with scikit-learn interface. Hyperparameters selection and easy plotting of efficient frontiers.☆57Updated last year
- ☆45Updated last year
- Statistical Jump Models in Python, with scikit-learn-style APIs☆70Updated 4 months ago
- Created a continuous, homogeneous, and structured 10 GB dataset from self obtained collections of unstructured intraday financial data. G…☆70Updated 5 years ago
- Entropy Pooling in Python with a BSD 3-Clause license.☆40Updated 7 months ago
- detecting regime of financial market☆36Updated 2 years ago
- Option pricing with various models (Black-Scholes, Heston, Merton jump diffusion, etc) and methods (Monte Carlo, finite difference, Fouri…☆77Updated 3 years ago
- Research Repo (Archive)☆73Updated 4 years ago
- Code repository for demos of the article 'Arbitrage-Free Implied Volatility Surface Generation with Variational Autoencoders'.☆33Updated 2 years ago
- Predictive yield curve modeling in reduced dimensionality☆43Updated 2 years ago
- ☆23Updated 2 months ago
- Attribution and optimisation using a multi-factor equity risk model.☆31Updated last year
- This collects the scripts and notebooks required to reproduce my published work.☆47Updated this week
- By means of stochastic volatility models☆44Updated 5 years ago
- Code base for the meta-labeling papers published with the Journal of Financial Data Science☆81Updated 2 years ago
- Algo Trading Research & Documentation☆19Updated last year
- Notebooks based on financial machine learning.☆50Updated 4 years ago
- This repository contains the code for the O'Reilly book Reinforcement Learning for Finance.☆52Updated last month
- ☆50Updated last year
- Jupyter Notebook examples on how to use the ArbitrageLab - pairs trading - python library.☆115Updated last year
- Semi-automatic analysis of a financial series using Python.☆13Updated 3 years ago
- Notebook based on the book "Advances in Financial Machine Learning" by Marcos Lopez de Prado☆125Updated 5 years ago
- Quant Research☆78Updated 2 months ago
- Machine learning-driven financial trading strategy: momentum prediction, regime detection, and enhanced trading decisions.☆64Updated 2 years ago