Paper: arXiv 2510.14435

Authors: Nicola Borri, Yukun Liu, Aleh Tsyvinski, Xi Wu

Abstract

We organize existing empirical regularities of cryptocurrencies into seven stylized facts and analyze cryptocurrencies through the lens of empirical asset pricing. We find important similarities with traditional markets–risk-adjusted performance so far is broadly comparable, and the cross-section of returns can be summarized by a small set of factors. However, cryptocurrency also has its own distinct character: jumps are frequent and large, and blockchain information helps drive prices. This common set of stylized facts provides evidence that cryptocurrency is emerging as an investable asset class. Additionally, we discuss potential data quality issues and possible changes in future regulations and the cryptocurrency environment.

Complexity vs Empirical Score

  • Math Complexity: 3.5/10
  • Empirical Rigor: 8.5/10
  • Quadrant: Street Traders — practical and empirical, lighter on theory

Why this score: This survey paper presents a comprehensive empirical evaluation of the cryptocurrency asset class by organizing return dynamics into seven key stylized facts. While it relies on empirical asset pricing frameworks rather than heavy theoretical derivations, it exhibits exceptional empirical rigor, using a massive dataset spanning over 16,000 unique coins and cross-exchange tick data.

Research Flowchart

  flowchart TD
    A[Research Goal: Evaluate Cryptocurrency as an Investable Asset Class] --> B[Data Inputs: Historical Crypto Prices & On-Chain Blockchain Data]
    B --> C[Methodology: Empirical Asset Pricing & Factor Modeling]
    C --> D[Analysis: Evaluate Returns, Risk-Adjusted Performance & Jump Dynamics]
    D --> E[Outcome 1: Identify 7 Stylized Facts Similar to Traditional Markets]
    D --> F[Outcome 2: Distinct Features Found - Frequent Jumps & On-Chain Price Drivers]
    E & F --> G[Conclusion: Cryptocurrency is Emerging as a Valid Investable Asset Class]

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4 of 225 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.