Paper: arXiv 2601.07664

Authors: Matthew Brigida

Abstract

We estimate risk premia in the cross-section of cryptocurrency returns using the Giglio-Xiu (2021) three-pass approach, allowing for omitted latent factors alongside observed stock-market and crypto-market factors. Using weekly data on a broad universe of large cryptocurrencies, we find that crypto expected returns load on both crypto-specific factors and selected equity-industry factors associated with technology and profitability, consistent with increased integration between crypto and traditional markets. In addition, we study non-tradable state variables capturing investor sentiment (Fear and Greed), speculative rotation (Altcoin Season Index), and security shocks (hacked value scaled by market capitalization), which are new to the literature. Relative to conventional Fama-MacBeth estimates, the latent-factor approach yields materially different premia for key factors, highlighting the importance of controlling for unobserved risks in crypto asset pricing.

Complexity vs Empirical Score

  • Math Complexity: 5.5/10
  • Empirical Rigor: 6.5/10
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper effectively applies the advanced Giglio-Xiu three-pass latent factor model to cryptocurrency markets, addressing omitted variable bias in asset pricing. It introduces novel non-tradable state variables like security hacks and sentiment indices, backed by a solid empirical methodology using block bootstrapping for statistical inference.

Research Flowchart

  flowchart TD
    A[Goal: Estimate Risk Premia in Crypto Returns Controlling for Unobserved Factors] --> B[Data Inputs: Weekly Crypto Returns, Equity-Industry Factors, State Variables]
    B --> C[Method: Giglio-Xiu 2021 Three-Pass Asset Pricing Framework]
    C --> D[Compute: Extract Latent Factors & Correct Risk Premia for Omitted Factor Bias]
    D --> E[Outcome 1: Returns Load on Tech/Profitability Equities & Crypto Factors]
    D --> F[Outcome 2: Non-Tradable State Variables Matter Sentiment, Alt Season, Hacks]
    D --> G[Outcome 3: Latent Factors Materially Shift Premia vs. Fama-MacBeth]

Cited References (15)

  1. On the Estimation of Beta-Pricing Models (1992) — link
  2. Cryptocurrency returns and the volatility of liquidity (2022)
  3. Factor pricing of cryptocurrencies (2021)
  4. Common risk factors in cryptocurrency (2022)
  5. Risk Premia in the Bitcoin Market (2024) — link
  6. Common risk factors in the returns on stocks and bonds (1993)
  7. What is the expected return on Bitcoin? Extracting the term structure of returns from options prices (2022)
  8. Asset Pricing with Omitted Factors (2021) — link
and 7 more
  1. Risk, Return, and Equilibrium: Empirical Tests (1973) — link
  2. Crypto Risk Premia (2022) — link
  3. Risks and Returns of Cryptocurrency (2020) — link
  4. The surprising irrelevance of total-value-locked on cryptocurrency returns (2025) — link
  5. Shrinkage estimation of high-dimensional factor models with structural instabilities (2016)
  6. Stability selection (2010)
  7. Asset Pricing: Revised Edition (2005)

0 of 15 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.