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Empirical Crypto Asset Pricing

Adam Baybutt

arXiv 24 May 2024 · Econometrics

arXiv:2405.15716 · PDF · DOI · OpenAlex · Extracted main text

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.

Citation extraction

24
references
38
in-text mentions
24
distinct cited
0
self-citations
6,554
main-text words

appendix boundary found by appendix_command · 61% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Borri, Massacci, Rubin, and Ruzzi (2022) Crypto risk premia0.84333100%
2Cong, Karolyi, Tang, and Zhao (2022) Value premium, network adoption, and factor pricing of crypto assets0.73732100%
3Liu, Tsyvinski, and Wu (2022) Common risk factors in cryptocurrency0.73732100%
4Bianchi, Guidolin, and Pedio (2022) The dynamics of returns predictability in cryptocurrency markets0.64422100%
5Hayek (1976) The Denationalization of Money: An Analysis of the Theory and Practice of Concurrent Currencies0.64422100%
6Liebi (2022) Is there a value premium in cryptoasset markets?0.64422100%
7Liu and Tsyvinski (2021) Risks and returns of cryptocurrency0.64422100%
8Shams (2020) The structure of cryptocurrency returns0.64422100%
9Zhang and Li (2020) Is idiosyncratic volatility priced in cryptocurrency markets?0.64422100%
10Zhang, Li, Xiong, and Wang (2021) Downside risk and the cross-section of cryptocurrency returns0.64422100%

Showing the top 10 of 24 scored citations.