Empirical Crypto Asset Pricing

TL;DR

This paper investigates the unique characteristics and return drivers of crypto assets, demonstrating their potential as an independent asset class with returns influenced mainly by univariate financial factors.

Contribution

It provides a comprehensive empirical analysis of crypto assets, highlighting their distinctiveness and the significance of univariate return-based factors in their pricing.

Findings

Crypto assets form a distinct, attractive asset class.

Univariate financial factors significantly predict crypto returns.

Speculative factors dominate in explaining crypto asset returns.

Abstract

We motivate the study of the crypto asset class with eleven empirical facts, and study the drivers of crypto asset returns through the lens of univariate factors. We argue crypto assets are a new, attractive, and independent asset class. In a novel and rigorously built panel of crypto assets, we examine pricing ability of sixty three asset characteristics to find rich signal content across the characteristics and at several future horizons. Only univariate financial factors (i.e., functions of previous returns) were associated with statistically significant long-short strategies, suggestive of speculatively driven returns as opposed to more fundamental pricing factors.