Repository profile
Implementation of code snippets, exercises and application to live data from Machine Learning for Asset Managers (Elements in Quantitative Finance) written by Prof. Marcos López de Prado.
Tracked growth, recent movement, and commit velocity from stored repository snapshots.
Latest capture 2026-06-19 22:43
1 capture since 2026-06-19
Stars from baseline 0
All tracked data
Frameworks, package managers, ecosystems, and dependency manifests found during catalog scans.
Scanned 2026-06-19 22:43
requirements.txt
python ecosystem,
21 dependencies
setup.py
python ecosystem,
0 dependencies
Searchable topics, generated tags, and stack labels that explain where this repository fits.
Agent instructions and tool configuration paths found in the repository tree.
Nearest indexed repositories by embedding similarity.
Machine Learning in Asset Management (by @firmai)
Statistical and Algorithmic Investing Strategies for Everyone
Various Types of Stock Analysis in Excel, Matlab, Power BI, Python, R, and Tableau
Framework for quantitative trading. Complete framework for development, backtesting, and deploying automated trading algorithms and trading bots.
Local-first backtesting engine with built-in overfitting detection. Asset-class agnostic. MCP-native.
Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
