{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T12:24:44Z","timestamp":1764937484068,"version":"build-2065373602"},"reference-count":48,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2022,11,11]],"date-time":"2022-11-11T00:00:00Z","timestamp":1668124800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Education","award":["RS-2022-00155911"],"award-info":[{"award-number":["RS-2022-00155911"]}]},{"name":"National Research Foundation of Korea","award":["RS-2022-00155911"],"award-info":[{"award-number":["RS-2022-00155911"]}]},{"name":"Institute of Information &amp; Communications Technology Planning &amp; Evaluation (IITP)","award":["RS-2022-00155911"],"award-info":[{"award-number":["RS-2022-00155911"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/e24111643","type":"journal-article","created":{"date-parts":[[2022,11,14]],"date-time":"2022-11-14T02:32:01Z","timestamp":1668393121000},"page":"1643","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Observing Cryptocurrencies through Robust Anomaly Scores"],"prefix":"10.3390","volume":"24","author":[{"given":"Geumil","family":"Bae","sequence":"first","affiliation":[{"name":"Industrial and Systems Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jang Ho","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Industrial and Management Systems Engineering, Kyung Hee University, Yongin-si 17104, Korea"},{"name":"Department of Big Data Analytics, Graduate School, Kyung Hee University, Yongin-si 17104, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40854-021-00321-6","article-title":"Cryptocurrency trading: A comprehensive survey","volume":"8","author":"Fang","year":"2022","journal-title":"Financ. 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