How Markets Price China Risk: Evidence from the Valuation Discount of US-Listed Chinese Firms

This article examines whether US-listed Chinese firms trade at systematically lower valuation multiples than comparable developed market firms and what that discount means for investment practice. Using quarterly data from 2015 to 2025, we study Chinese firms drawn from the NASDAQ Golden Dragon China Index and compare them with NASDAQ-100 constituents and, as a broader alternative benchmark, with the Russell 1000. Our primary specification uses the natural log of price-to-sales as the dependent variable and log revenue as the main size control, alongside revenue growth, profitability, leverage, and year effects. Chinese firms trade at a substantial discount under both benchmarks, although the estimated magnitude is benchmark-sensitive and larger against the NASDAQ-100 than against the Russell 1000. Matched-sample regressions continue to show a large discount after improving size and industry comparability. Interaction regressions add a more selective result: They provide limited evidence that profitability is capitalized less favorably for Chinese firms in the NASDAQ-based full sample and stronger evidence that the valuation effect of operating scale differs for Chinese firms in the broader Russell-based specifications. Firm fixed-effects regressions indicate that the discount widened further after 2020 within the same firms, and alternative breakpoint tests show that the repricing was not confined to a single arbitrary cutoff year. Additional diagnostics, coverage-by-year exhibits, restricted-sample reestimation, and alternative-multiple tests support the interpretation that low valuations on US-listed Chinese equities reflect a priced and time-varying China-risk premium rather than ordinary value alone. For practitioners, the central implication is that peer-multiple valuation, benchmark design, factor attribution, and tactical allocation decisions should distinguish firm fundamentals from country-risk-related discounting.