I'm pleased to share that my paper, Crypto Pricing with Hidden Factors, has been accepted for publication in Finance Research Letters. The paper examines how hidden sources of risk influence crypto asset pricing and what they reveal about the relationship between crypto and traditional financial markets.
Over 2023–24, crypto expected returns are linked not only to crypto-native risks, but also to stock-market factors, especially technology/software and profitability-related risks, pointing to growing integration between crypto and traditional capital markets.
The method matters: using the Giglio-Xiu latent-factor approach, which accounts for unobserved sources of risk, the estimated crypto market premium is roughly 24% annualized, compared with about 6% under a standard Fama-MacBeth approach, meaning that ignoring hidden risk factors can materially change the estimated compensation investors require for crypto-market exposure.
The paper also finds that the crypto size factor is priced, with smaller-cap crypto exposure earning a positive premium that holds across several specifications after correcting for token migration and market-cap construction issues. Sentiment carries pricing information as well, with innovations in the Crypto Fear & Greed Index linked to expected returns. Total value locked, by contrast, does not appear to be independently priced once latent risk is accounted for; instead, TVL loads on broader common factors, consistent with my earlier Economics Letters result.
I'm grateful to my colleagues at the Algorand Foundation for their support throughout this work, and to the anonymous reviewers whose thoughtful feedback helped strengthen the paper.
Read the paper in Finance Research Letters here (available at that share link through September 11, 2026), or the accepted manuscript here.