Optimization of a Cryptocurrency Portfolio using Conditional Value at Risk and Markov Switching GARCH approach

In recent years, the popularity of investing in cryptocurrencies has increased, and gradually, the cryptocurrency market has matured by attracting higher liquidity and developing online trading platforms. However, investing in this area can disrupt the balance between risk-adjusted returns due to sudden price fluctuations. To address this issue, selecting an optimal portfolio that simultaneously maximizes expected return while minimizing investment risk is crucial. Accordingly, this study aims to select an optimal portfolio of cryptocurrencies using the Conditional Value at Risk approach and the Markov Switching GARCH process. For this purpose, daily return data from six high-market-cap cryptocurrencies—Bitcoin, Ethereum, Litecoin, Ripple, Cardano, and Binance Coin—as well as the stablecoin Tether—were utilized from January 1, 2019, to December 1, 2023. The study results indicate that in a high-volatility regime, a larger portion of the investment portfolio is allocated to the stablecoin Tether and Bitcoin (which exhibit more stable price movements than other cryptocurrencies). Conversely, in a low-volatility regime, the optimal investment portfolio allocates a higher weight to altcoins, aiming to maximize expected returns.