Trabajo de grado - Maestría
Portfolio optimization in cryptocurrencies: a comparison of deep reinforcement learning and traditional approaches
Fecha
2022-12-16Registro en:
instname:Universidad de los Andes
reponame:Repositorio Institucional Séneca
Autor
García Pardo, César Camilo
Institución
Resumen
Cryptocurrencies have become appealing investment options in recent years because of their high potential returns. This asset class emerged as a unique investment opportunity with distinguishing characteristics such as decentralized nature and uncorrelation with other assets. Investing in this product, however, has become a hazardous venture due to its extreme volatility and unpredictable price swings. As a result, a portfolio optimization is an essential tool for investors seeking to reduce risk while aiming for high returns. This thesis studies the Deep Reinforcement Learning models applied to cryptocurrency portfolio optimization compared to traditional methodologies like Markowitz's and rudimentary equally weighted portfolios.