A carregar...
Publicação
Portfolio optimization in cryptocurrencies: a comparison of deep reinforcement learning and traditional approaches
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 1.65 MB | Adobe PDF |
Autores
Orientador(es)
Resumo(s)
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.
Descrição
Palavras-chave
Cryptocurrency Decentralized Deep reinforcement learning Markowitz's Optimization Portfolio optimization