Portfolio Optimization and Quantitative Strategic Asset Allocation in Python

FinRL-X: An AI-Native Modular Infrastructure for Quantitative Trading

Build a statistical risk model using PCA. Optimize the portfolio using the risk model and factors using multiple optimization formulations.

Python-based portfolio / stock widget which sources data from Yahoo Finance and calculates different types of Value-at-Risk (VaR) metrics and many other (ex-post) risk/return characteristics both on an individual stock and portfolio-basis, stand-alone and vs. a benchmark of choice (constructed with wxPython)

Portfolio optimization using Genetic algorithm.

A portfolio optimization tool with scikit-learn interface. Hyperparameters selection and easy plotting of efficient frontiers.

Parameter Optimization for Lean Algorithms

A collection of various computational methods to optimize a user's investment portfolio using Modern Portfolio Theory and optimizing various factors such as Returns, Sharpe Ratio and Risk.

Design your own Trading Strategy

Markowitzify will implement a variety of portfolio and stock/cryptocurrency analysis methods to optimize portfolios or trading strategies. The two primary classes are "portfolio" and "stonks."

A quantitative trading strategy backtester with an interactive dashboard. Enables users to implement, test, and visualise trading strategies using historical market data, featuring customisable parameters and key performance metrics. Developed with Python and Polars.

C++ code for "A Faster Drop-in Implementation for Leaf-wise Exact Greedy Induction of Decision Tree Using Pre-sorted Deque"

Download brazillian investment funds and their benchmarks data from CVM and analyze their performance with pre-built functions.

Stock Portfolio Analysis using Python/Pandas

Stock Market Analysis

analyze financial data using python: numpy, pandas, etc.

Data Science Case Studies

A student Investment portfolio web app built with various optimization techniques and screening parameters from core finance

NIFTY50 Data Analysis from scratch (Data Extraction & Visualization to Investment Insights)

Python notes on finance