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CRYPTOCURRENCY TRADING —FROM SINGLE-FACTOR MODEL TO MULTIFACTOR MODEL BY TAKING LONG-SHORT STRATEGIES

Aluno: Wenyan Zhao


Resumo
This study explored the impact of different indicator factor models on the performance of portfolios under the same trading strategy within the same time frame. The indicator factors selected were the Commodity Channel Index (CCI), Volume, and Bollinger bands (Boll count). The trading strategy employed is known as the 'Long-short pairing strategy', which involves taking a long and holding position in a single coin ranked first while short-holding a coin ranked last at the same time. 264 Coins that are traded on Binance plarforms are included in this research, and coin selection process is refreshed every 6 hours. The time frame considered for this analysis spans from September 20, 2020, to September 20, 2023. The evaluation metrics for portfolio performance are the accumulated net value, annual return, portfolio standard deviation, Sharpe ratio, maximum draw-down, information ratio, etc. The hyper-parameter of the factors was tuned by machine learning using Grid search. The results showed that combining additional factors into the model can increase annual returns. However, reducing portfolio volatility and risk exposure is in doubt. Also, the impact of additional factors on portfolio performance and risk can vary significantly depending on the specific factors and their correlations, emphasising the importance of careful factor selection and combination in


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