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报 告 人：尚广志
We establish that cryptocurrency returns are driven and can be predicted by factors that are specific to cryptocurrency markets. Cryptocurrency returns are exposed to cryptocurrency network factors but not cryptocurrency production factors. We construct the network factors to capture the user adoption of cryptocurrencies and the production factors to proxy for the costs of cryptocurrency production. Moreover, there is a strong time-series momentum effect, and proxies for investor attention strongly forecast future cryptocurrency returns.
Guangzhi Shang is Jim Moran Associate Professor of Operations Management in the Department of Business Analytics, Information Systems, and Supply Chain at Florida State University. His research has been published in Production and Operations Management (POM), Journal of Operations Management (JOM), and Decision Sciences (DS), among others, and recognized by best paper awards at POM, JOM, and POM Society’s College of Operational Excellence. He serves as the co-Department-Editor for the Empirical Research Methods Department at JOM and for the Retail Operations Department at DS. His review service is recognized by the 2019 outstanding reviewer award of DS and the 2018 best reviewer award of the Journal of Operations Management. He was also nominated for the best reviewer for POM and best associate editor for JOM. He co-produces a column together with Mike Galbreth and Mark Ferguson in the Reverse Logistics Magazine named “View from Academia,” aimed at disseminating fresh-off-the-press academic knowledge among industry professionals dealing with consumer returns.