Portfolio optimization in cryptocurrency market

Thanks to the convenience of technology, money flow and trade can be done quickly in today's economies. In particular, the restrictions brought by the Covid-19 pandemic have brought technology to the forefront in the use of investment instruments, as in all areas of life. Bitcoin and subsequent cryptocurrencies, which gained prominence for the first time with an article published by Satoshi Nakamoto in 2008, they have been the investment choice of many people due to their completely technology-based infrastructure, easy acquisition, simplicity of clearing transactions, and not being connected to any central authority. Investment transactions to be made with cryptocurrencies should be done by considering the return-risk balance, just like other investment instruments. In this context, the purpose of our study is to determine the cryptocurrencies to be used for investment, to decide which cryptocurrencies to invest in and to what extent, to interpret the performance indicators of the portfolios created with cryptocurrencies, and to choose the optimal portfolio. In this study, among the cryptocurrencies with the highest market value as of April 01, 2023, and with full data information between 2020-2022, 10 cryptocurrencies named Cardona (ADA), BNB Coin (BNB), Bitcoin (BTC), Ethereum (ETH), Chainlink (LINK), Litecoin (LTC), Polygon (MATIC), Tron (TRX), Tether (USDT) and Ripple have been used. From these ten cryptocurrencies, four different portfolios were created, namely, one with equal weightings, one with the highest Sharpe ratio, one with the lowest variance, and one based on market values for the weights. During the review period of the study, it was observed that the return-risk findings in 4 different portfolio models used in the study gave results in accordance with their names during the review period. The portfolio with the highest annualized average return rate is the portfolio with the maximum Sharpe ratio. The lowest rate of return was observed in the market value-weighted portfolio. In the portfolio created with the minimum variance model, the annualized risk is at the lowest level in line with the expectations. The highest risk ratio was observed in the portfolio with the maximum Sharpe ratio. The Sharpe ratio remained at a higher level in the portfolio with the maximum Sharpe ratio in all periods compared to other portfolios, yielding results as expected. The study's findings suggest that investors may benefit from portfolio optimization to identify the portfolio that aligns most closely with their desired return-risk levels. In addition, it has been determined that the use of portfolio optimization can significantly reduce the risk in cryptocurrencies with very high individual risk ratios. Overall, the findings provide valuable insight for those seeking to make informed investment decisions in the cryptocurrency market.