Emergence of Non-Speculative Demand for Bitcoin: Learning about Stochastic Correlations with Stock Markets

48 Pages Posted: 1 Mar 2021 Last revised: 5 Mar 2021

See all articles by James Yae

James Yae

University of Houston - C. T. Bauer College of Business

George Zhe Tian

University of Houston - C. T. Bauer College of Business

Date Written: February 9, 2021

Abstract

When a new asset keeps changing its narrative, investors find difficulty in classifying and understanding the new asset. Rational investors therefore face unprecedented uncertainty and learn about the joint dynamics to optimize their portfolio accordingly. Bitcoin's "digital gold" narrative, as a safe haven, best demonstrates this uncertainty-learning behavior. We find that an increase in investors' estimates on the correlations between Bitcoin and the US stock markets strongly predict lower subsequent Bitcoin returns, consistent with a mean-variance framework. However, portfolio optimization errors associated with uncertainty in volatilities are 30 times greater than those with correlations; therefore, volatility-related predictors fail to explain Bitcoin returns. The same empirical patterns appear in out-of-sample predictions, global equity markets, and other cryptocurrencies.

Keywords: Bitcoin, Uncertainty, Learning, Time-Varying Correlation

JEL Classification: G12, G15, D83

Suggested Citation

Yae, James and Tian, George Zhe, Emergence of Non-Speculative Demand for Bitcoin: Learning about Stochastic Correlations with Stock Markets (February 9, 2021). Available at SSRN: https://ssrn.com/abstract=3794697 or http://dx.doi.org/10.2139/ssrn.3794697

James Yae (Contact Author)

University of Houston - C. T. Bauer College of Business ( email )

Houston, TX 77204-6021
United States

George Zhe Tian

University of Houston - C. T. Bauer College of Business ( email )

Houston, TX 77204-6021
United States

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