We examine the efficiency of using individual stocks or portfolios as base assets to test asset pricing models using cross-sectional data. The literature has argued that creating portfolios reduces idiosyncratic volatility and allows more precise estimates of factor loadings, and consequently risk premia. We show analytically and empirically that smaller standard errors of portfolio beta estimates do not lead to smaller standard errors of cross-sectional coefficient estimates. Factor risk premia standard errors are determined by the cross-sectional distributions of factor loadings and residual risk. Portfolios destroy information by shrinking the dispersion of betas, leading to larger standard errors.
Wide and volatile interest rate spreads in the 2007-2009 financial crisis could represent concerns over asset liquidity or issuer solvency. To precisely identify the contribution of these two effects on sovereign bond and interbank spreads, I propose a model-free measure of euro-area market liquidity that captures all liquidity information impounded in bond yields. I find that credit and liquidity are independently important in risk spreads; the role of liquidity dominates in the interbank market, while its relative importance in sovereign bond spreads varies substantially by country. I exploit variation in sovereign bond returns over countries, maturities and time to directly test liquidity risk pricing; the possibility that liquidity could be negatively correlated with marginal utility. I find that liquidity risk premia are large and significant, evidencing the importance of a liquidity channel missed by measures that capture only instantaneous liquidity.Keywords market liquidity, interbank credit, liquidity risk, money markets, interest rates, financial crisis Disciplines Finance and Financial ManagementThis working paper is available at ScholarlyCommons: http://repository.upenn.edu/fnce_papers/19Electronic copy available at: https://ssrn.com/abstract=1486240 Mind the Gap: Disentangling Credit and Liquidity in Risk SpreadsKrista Schwarz *The Wharton School University of Pennsylvania February 2017 AbstractWide and volatile interest rate spreads in the 2007-2009 financial crisis could represent concerns over asset liquidity or issuer solvency. To precisely identify the contribution of these two effects on sovereign bond and interbank spreads, I propose a model-free measure of euro-area market liquidity that captures all liquidity information impounded in bond yields. I find that credit and liquidity are independently important in risk spreads; the role of liquidity dominates in the interbank market, while its relative importance in sovereign bond spreads varies substantially by country. I exploit variation in sovereign bond returns over countries, maturities and time to directly test liquidity risk pricing; the possibility that liquidity could be negatively correlated with marginal utility. I find that liquidity risk premia are large and significant, evidencing the importance of a liquidity channel missed by measures that capture only instantaneous liquidity.JEL Classification: E44, G01, G12, G15 Keywords: market liquidity, interbank credit, liquidity risk, money markets, interest rates, financial crisis. * Department of Finance, The Wharton School, University of Pennsylvania, 3620 Locust Walk, Philadelphia, PA 19104. Tel. 215-898-6087. E-mail: kschwarz@wharton.upenn.edu. I am grateful to an anonymous referee, Heitor Almeida, Andrew Ang, Charles Calomiris, Larry Glosten, Charles Jones, Ahn Le, Francis Longstaff and Suresh Sundaresan for their extremely helpful comments on this work, to the Department of Economics and Finance at Columbia Business School for funding the MTS data used in this paper, and t...
We examine the asymptotic efficiency of using individual stocks or portfolios as base assets to test crosssectional asset pricing models. The literature has argued that creating portfolios reduces idiosyncratic volatility and enables factor loadings, and consequently risk premia, to be estimated more precisely. We show analytically and find empirically that the more efficient estimates of betas from creating portfolios do not lead to lower asymptotic variances of factor risk premia estimates. Instead, the standard errors of factor risk premia estimates are determined by the cross-sectional distribution of factor loadings and residual risk. Creating portfolios shrinks the dispersion of betas and leads to higher asymptotic standard errors of risk premia estimates. AbstractWe examine the asymptotic efficiency of using individual stocks or portfolios as base assets to test cross-sectional asset pricing models. The literature has argued that creating portfolios reduces idiosyncratic volatility and enables factor loadings, and consequently risk premia, to be estimated more precisely. We show analytically and find empirically that the more efficient estimates of betas from creating portfolios do not lead to lower asymptotic variances of factor risk premia estimates. Instead, the standard errors of factor risk premia estimates are determined by the cross-sectional distribution of factor loadings and residual risk. Creating portfolios shrinks the dispersion of betas and leads to higher asymptotic standard errors of risk premia estimates.
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