Probabilistic Machine Learning for Finance and Investing: A Primer to Generative AI with Python
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Updated
Jan 15, 2024 - Jupyter Notebook
Probabilistic Machine Learning for Finance and Investing: A Primer to Generative AI with Python
Implementation of the DDPG algorithm for Optimal Finance Trading
Exploratory analysis, visualization of stock market data along with predictions made on it using different techniques.
Python library to implement advanced trading strategies using machine learning and perform backtesting.
Demo project of creating an interactive analytical tool for stock market using CAPM.
Fama-French models, idiosyncratic volatility, event study
modeling the behavior of stock markets: create a market simulator, technical indicator, and a strategy that generates orders
This notebook provides some skills to perform financial analysis on economical data.
An Empirical Study of Capital Asset Pricing Model based on Chinese A-share Trading Data.
Python beta calculator that retrieves stock and market data and provides linear regressions.
Master Degree Coursework: Econometrics I
Finance R program - bond pricing, option pricing, and others
robo-advisor is a quantitative analysis script written in Python that generates the least volatile portfolio given a list of stocks, with the goal of a 0% return.
A toolkit for asset pricing research
Script to perform the asset pricing test of Gibbons, Ross, and Shanken (1989)
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