Observing Cryptocurrencies through Robust Anomaly Scores

【Author】 Bae, Geumil; Kim, Jang Ho

【Source】ENTROPY

【影响因子】2.738

【Abstract】The cryptocurrency market is understood as being more volatile than traditional asset classes. Therefore, modeling the volatility of cryptocurrencies is important for making investment decisions. However, large swings in the market might be normal for cryptocurrencies due to their inherent volatility. Deviations, along with correlations of asset returns, must be considered for measuring the degree of market anomaly. This paper demonstrates the use of robust Mahalanobis distances based on shrinkage estimators and minimum covariance determinant for observing anomaly scores of cryptocurrencies. Our analysis shows that anomaly scores are a critical complement to volatility measures for understanding the cryptocurrency market. The use of anomaly scores is further demonstrated through portfolio optimization and scenario analysis.

【Keywords】cryptocurrency; anomaly score; Mahalanobis distance; minimum covariance determinant; shrinkage estimators

【发表时间】2022 NOV

【收录时间】2023-01-02

【文献类型】理论模型

【主题类别】

区块链治理-市场治理-数字货币