saeed349 / Advances-in-Financial-Machine-Learning
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.
☆37Updated 9 months ago
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
- Python library for asset pricing☆107Updated 10 months ago
- Quant Research☆67Updated last month
- Here I am collecting the scripts I have used to prepare my book "Adventures in Financial Data Science" and to support my other writing, s…☆62Updated 5 months ago
- Macrosynergy Quant Research☆111Updated this week
- ☆45Updated last year
- ☆50Updated last year
- Statistical Jump Models in Python, with scikit-learn-style APIs☆49Updated this week
- Option pricing with various models (Black-Scholes, Heston, Merton jump diffusion, etc) and methods (Monte Carlo, finite difference, Fouri…☆72Updated 3 years ago
- ☆34Updated last year
- Algo Trading Research & Documentation☆15Updated 7 months ago
- Financial AI with Python☆58Updated 3 weeks ago
- This collects the scripts and notebooks required to reproduce my published work.☆44Updated last week
- Collection of notebooks and scripts related to financial engineering, quant-research and algo-trading.☆57Updated 5 months ago
- ☆63Updated this week
- Code of paper "Stock Price Prediction Incorporating Market Style Clustering" published in Cognitive Computation.☆26Updated 3 years ago
- detecting regime of financial market☆33Updated 2 years ago
- Attribution and optimisation using a multi-factor equity risk model.☆31Updated 11 months ago
- Neural network local volatility with dupire formula☆73Updated 3 years ago
- Code for the paper Volatility is (mostly) path-dependent☆58Updated 9 months ago
- Python implementation of pricing analytics and Monte Carlo simulations for stochastic volatility models including log-normal SV model, He…☆147Updated this week
- Resources for the AI in Finance Workshop at Texas State University (October 2023).☆48Updated last year
- ☆57Updated last year
- ☆80Updated last month
- Regime Based Asset Allocation with MPT, Random Forest and Bayesian Inference☆25Updated 2 years ago
- By means of stochastic volatility models☆42Updated 4 years ago
- Script for Calculating Implied Probability Distribution from Option Prices - The Quant's Playbook @ Quant Galore☆28Updated last year
- Python modules and jupyter notebook examples for the paper Detect and Repair Arbitrage in Price Data of Traded Options.☆115Updated last year
- Created a continuous, homogeneous, and structured 10 GB dataset from self obtained collections of unstructured intraday financial data. G…☆61Updated 4 years ago