Functions for the construction of risk-based portfolios

Stock Market Analysis

This R Shiny App utilizes the Hierarchical Equal Risk Contribution (HERC) approach, a modern portfolio optimization method developed by Raffinot (2018).

An R package implementing a collection of clustered and hierarchical portfolio optimization techniques.

Trading R Package

Cross asset allocation with mean-variance and mean-CVaR (Expected Shortfall) optimization methods

Using an optimization strategy analyze stock data to find a portfolio with the lowest Conditional Value-at-Risk

Sharpe ratio portfolio maximization by way of quadratic programming.

Stock Portfolio Performance by Weighted Stock Selection - The project quantitatively predicts the factors that must be given the most and least weights to obtain obtain the highest returns, risk and win-rates while developing a S&P500 portfolio

An application of the paper "Rockafellar, R. and S. Uryasev. “Optimization of conditional value-at risk.” Journal of Risk 3 (2000): 21-41."

Machine Learning for Finance, Portfolio Management and Optimization

Finding optimum portfolio consisting of the instruments of Dhaka Stock Exchange.

Contains source code for Shiny Web application for portfolio optimization

R wrapper for Alpha Vantage API and various quantitative finance methods/functions/algorithms

This repository features a R Shiny Web App for training Machine Learning models for Segementation tasks

Investment Funnel

Presentación de mi TFM titulado "Aplicación de redes neuronales artificiales y programación cuadrática en la gestión de carteras"

Mi TFM titulado "Aplicación de redes neuronales artificiales y programación cuadrática en la gestión de carteras"

Portfolio optimization in AMPL; compared minimum covariance and Young's minimax models

Stock returns prediction using ML and DL techniques and portfolio optimization using the variance covariance matrix estimation.