This repository contains code examples supplementing the paper titled "Machine Learning, Regression, and Optimization".
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Updated
Aug 13, 2021 - Jupyter Notebook
This repository contains code examples supplementing the paper titled "Machine Learning, Regression, and Optimization".
Project 1 of the 2020 Northwestern Financial Technology Bootcamp. We built a functional quantitative trading system that implements strategies researched and tested in Quantopian. Those strategies are then executed in Alpaca- the commission-free stock trading API.
Boost investment returns with PyInvestor: Python-based tool for optimized stock allocation.
Risk-return analysis with mean-variance method
A mini-lab for visualizing portfolio optimization and the 'Efficient Frontier'
Business case (SQL): Revenue optimization for a multinational wholesaler
Presentación de mi TFM titulado "Aplicación de redes neuronales artificiales y programación cuadrática en la gestión de carteras"
Portfolio optimization with minimum risk for the Dow Jones Index companies
Ledoit Wolf shrinkage for covariance matrices in Java
MPT demonstration code
Machine learning techniques to determine bank defaults and optimal composition of portfolio weights
Stock Price Prediction and Portfolio Return Maximization
Optimization of portfolio returns using SciPy's minimization solver.
Implementation of Smart Beta and Portfolio Optimization
Пример описания портфолио
This project showcases a comprehensive application of financial analytics concepts, portfolio optimization techniques, and statistical software in the R programming language and Microsoft Excel
Boldly drive your kart to where no one has gone before: the Northwest corner of the Efficient Frontier. Can you hold on, or will the economic shocks throw you off your game?
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