Portfolio Construction Based on XGBoost-CAPM Model: Evidence from the Cryptocurrency Market

Jintong Yang ()
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Jintong Yang: Zhuhai College of Science and Technology, School of Finance and Trade

A chapter in Proceedings of the 2024 9th International Conference on Social Sciences and Economic Development (ICSSED 2024), 2024, pp 127-136 from Springer

Abstract: Abstract This study investigates the construction of an optimal investment portfolio in the cryptocurrency market using the XGBoost algorithm and the CAPM model. To achieve this objective, one selected Bitcoin, Ethereum, Litecoin, and Tether as representative assets in the cryptocurrency market and used the CMC200 as the market index. The study primarily employed the XGBoost algorithm to predict the returns of the market index, while using the CAPM model and OLS regression analysis to calculate the alpha and beta of each asset. Based on the predicted market index returns and the alpha and beta values of each asset, this paper further calculated the expected returns of each asset. For portfolio optimization strategies, one used the maximum Sharpe ratio and minimum volatility as optimization goals to determine the weights of the optimal investment portfolio. The results indicate that by combining the XGBoost prediction model, CAPM theory, and portfolio optimization strategies, one can build investment portfolios in the cryptocurrency market with higher returns and lower risk, providing valuable guidance for cryptocurrency investors.

Keywords: Portfolio Construction; Cryptocurrency; CAPM Model; XGBoost; Time series (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-459-4_16

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DOI: 10.2991/978-94-6463-459-4_16

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