Blockchain Characteristics and the Cross-Section of Cryptocurrency Returns

55 Pages Posted: 13 May 2019 Last revised: 4 Feb 2022

See all articles by Siddharth Bhambhwani

Siddharth Bhambhwani

University of Miami Herbert Business School

Stefanos Delikouras

University of Miami - Department of Finance

George M. Korniotis

University of Miami; Miami Business School; University of Miami - Behavioral Decision Making Cluster

Date Written: May 2019

Abstract

We examine whether blockchain characteristics such as network size and computing power affect cryptocurrency prices and returns. Consistent with theoretical models, cryptocurrency prices are cointegrated with these two blockchain characteristics. Further, a stochastic discount factor with aggregate network and computing power explains the cross-sectional variation in expected cryptocurrency returns at least as well as models with cryptocurrency return-based factors (market, size, momentum). Overall, our results show that theoretically motivated factors are important sources of risk for cryptocurrency prices and expected returns.

Keywords: Factor Analysis, GMM, Hashrate, network, Rolling Estimation

JEL Classification: E4, G12, G15

Suggested Citation

Bhambhwani, Siddharth and Delikouras, Stefanos and Korniotis, George M., Blockchain Characteristics and the Cross-Section of Cryptocurrency Returns (May 2019). CEPR Discussion Paper No. DP13724, Available at SSRN: https://ssrn.com/abstract=3387313

Siddharth Bhambhwani (Contact Author)

University of Miami Herbert Business School ( email )

P.O. Box 248126
Florida
Coral Gables, FL 33124
United States

Stefanos Delikouras

University of Miami - Department of Finance ( email )

P.O. Box 248094
Coral Gables, FL 33124-6552
United States

George M. Korniotis

University of Miami ( email )

P.O. Box 248094
Coral Gables, FL 33124-6552
United States
305-284-5728 (Phone)

Miami Business School ( email )

University of Miami - Behavioral Decision Making Cluster ( email )

5250 University Drive
Coral Gables, FL 33124
United States

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