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A0861
Title: Two-pass cross-sectional regressions with individual stocks Authors:  Cesare Robotti - Imperial College London (United Kingdom) [presenting]
Valentina Raponi - Imperial College London (United Kingdom)
Paolo Zaffaroni - Imperial College London (United Kingdom)
Abstract: A limiting theory for estimating and testing linear asset-pricing models with a large number of assets and a fixed time-series sample size is presented. The focus is on the modified ordinary least squares estimator of the ex-post risk premia. We derive the asymptotic distribution of this estimator and show how its limiting variance can be consistently estimated. In addition, we characterize the asymptotic distribution of a cross-sectional test of the fundamental asset-pricing relation. Finally, we show how our results can be extended to deal with an unbalanced panel. The practical relevance of our findings is demonstrated using Monte Carlo simulations and an empirical application to asset-pricing models with traded risk factors. Our analysis suggests that only the market, size, and value factors are priced consistently in the cross-section of NYSE-AMEX-NASDAQ individual stock returns. Overall, we cannot reject the null of zero risk premia for the profitability and investment factors.