Probabilistic Machine Learning for Finance and Investing: A Primer to Generative AI with Python
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Updated
Apr 19, 2025 - Jupyter Notebook
Probabilistic Machine Learning for Finance and Investing: A Primer to Generative AI with Python
Data-driven risk-conscious thermoelectric materials discovery
Package to calculate the RIE estimator of a correlation matrix
Simple Modern Portfolio Theory in Python
This module contains quantitative portfolio analysis equations, portfolio back-testing, and asset data organization/cleaning data structures.
A mathematical approach to portfolio allocations. Based on the proposal by Fisher Black and Robert Litterman
Analysing monte-carlo portfolios with modern portfolio theory
Remake repo sebelumnya, yang ini semoga di acc sebagai skripsi UBHARA
My working through of The Missing Billionaires, by Haghani & White
Markowitz mean-variance criterion in R
This action runs back tests and generates `returns.csv` and `backtest_results.json` files.
A command line tool to display efficient frontier of a portfolio of selected stocks
In this simple project we were tasked with manipulating and visualizing portfolio data, create portfolios and compute basics statistics, draw the efficient frontier and find the best portfolio, and testing the Markowitz mean-variance theory in practice to see if we could beat the market.
A set of Portfolio Specifications for Factors
Slides for my talk at the Data Science Festival 2017
Este repositorio reúne dos proyectos académicos de Matemáticas Financieras II (CO5516), centrados en la teoría moderna de portafolios y la optimización financiera con datos reales del S&P 500.
Theoretical foundation of derivative pricing, covering financial markets, bonds, options and models like Black-Scholes.
Códigos asociados a la Teoría Estocástica de Portafolios
Finance Notes by Ryan Reece
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