A Prospect Theory Model for Predicting Cryptocurrency Returns

Alexander Thoma
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引用次数: 3

Abstract

This paper investigates the risk and return properties of a trading strategy for the cryptocurrency market. The main predictive power for portfolio formation comes from a simple prospect theory model that only uses price information readily available. The dataset consists of a large body of cryptocurrencies from 2014 to 2020. I find a strong outperformance over the market, even after controlling for known predictors. Factor regressions with a cryptocurrency three-factor model further reveal significant alphas. Robustness test emphasize the legitimacy of the strategy. On average, cryptocurrencies with a high (low) prospect theory value earn low (high) subsequent returns. Interestingly, traders in the cryptocurrency market seem to assess the attractiveness of cryptocurrency in a way described by prospect theory. Mechanical tests of the model show that probability weighting is a main driver behind this assessment. Cryptocurrencies with a high prospect theory value tend to be highly positively skewed. This skewness could be the reason why the cryptocurrency seems attractive to traders, similar to lottery-like gambles.
预测加密货币收益的前景理论模型
本文研究了加密货币市场中一种交易策略的风险和收益性质。投资组合形成的主要预测能力来自一个简单的前景理论模型,该模型只使用现成的价格信息。该数据集由2014年至2020年的大量加密货币组成。我发现,即使在控制了已知的预测因素之后,它的表现也明显优于市场。使用加密货币三因素模型的因素回归进一步揭示了显著的alpha。稳健性检验强调策略的合法性。平均而言,具有高(低)前景理论价值的加密货币获得低(高)后续回报。有趣的是,加密货币市场的交易者似乎以前景理论描述的方式评估加密货币的吸引力。模型的力学测试表明,概率加权是这一评估背后的主要驱动因素。具有高前景理论价值的加密货币倾向于高度正向倾斜。这种不对称性可能是加密货币对交易者具有吸引力的原因,类似于彩票类赌博。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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