A Note on the Estimation of Asset Pricing Models Using Simple Regression Betas

Since Black, Jensen, and Scholes (1972) and Fama and MacBeth (1973), the two-pass cross-sectional regression (CSR) methodology has become the most popular tool for estimating and testing beta asset pricing models. In this paper, we focus on the case in which simple regression betas are used as regressors in the second-pass CSR. Under general distributional assumptions, we derive asymptotic standard errors of the risk premia estimates that are robust to model misspecification. When testing whether the beta risk of a given factor is priced, our misspecification robust standard error and the Jagannathan and Wang (1998) standard error (which is derived under the correctly specified model) can lead to different conclusions

Zur Quantifizierung der Risikoprämien deutscher Versicherungsaktien im Kontext eines Multifaktorenmodells

Vorgestellt wird eine empirische Studie, welche den Zusammenhang zwischen Rendite und Risiko für ein Sample deutscher Versicherungsaktien im Zeitraum 1975-1998 untersucht. Als Methode wurde ein Multifaktorenmodell mit makroökonomischen Faktoren verwendet. Je nach Untersuchungszeitraum beläuft sich der Anteil der erklärten Varianz auf 9,29% bis 13,62%. Es konnte eine signifikanter negativer Einfluß zwischen der Veränderung des allgemeinen Zinsniveaus und den Risikoprämien von Versicherungsaktien identifiziert werden. Weiterhin ist Wechselkurses der DM zum US-Dollar signifikant

The Size Effect in Value and Momentum Factors: Implications for the Cross-Section of International Stock Returns

We document a consistent and robust relation between expected equity premia and common risk factors constructed on the basis of small stocks. Empirically, we show that (i) small-stock components of traditional value and momentum factors capture patterns in returns on regional and global portfolios of stocks; (ii) size-effect models substantially outperform benchmark models in finance; (iii) global small-stock value and momentum components are priced but regional models lead to more accurate asset evaluations; (iv) funding liquidity risk is a partial explanation of these findings

Transaction Costs, Liquidity and Expected Returns at the Berlin Stock Exchange, 1892-1913

We estimate effective spreads and round-trip transaction costs at the Berlin Stock Exchange for the period 1892-1913 using daily stock market returns for a sample of 27 stocks. Our results show that transaction costs at the main stock exchange in a bank-based financial system at the turn of the 20th century were quite low and about comparable to transaction costs in modern markets. Nonetheless, transaction costs varied substantially over time and across securities, whereby the cross-sectional variation could be substantially explained by firm size and time variation by crises. Furthermore, we find surprising evidence that transaction costs decrease the expected excess returns. Thereby size and momentum premia are of expected signs while market beta has no significant influence on the cross-sectional return variation

Creative Destruction and Asset Prices

This paper introduces Schumpeter's idea of creative destruction into asset pricing. The key point of our model is that small and value firms are more likely destroyed during technological revolutions, resulting into higher expected returns for these stocks. A two-factor model including market return and patent activity growth - the proxy for creative destruction risk - accounts for a large portion of the cross-sectional variation of size and book-to-market sorted portfolios and prices HML and SMB. The expected return difference between assets with the highest and lowest exposure to creative destruction risk amounts to 8.6 percent annually

Testing for Alpha in Linear Factor Pricing Models with a Large Number of Securities

This paper proposes a novel test of zero pricing errors for the linear factor pricing model when the number of securities, N, can be large relative to the time dimension, T, of the return series. The test is based on Student t tests of individual securities and has a number of advantages over the existing standardised Wald type tests. It allows for non-Gaussianity and general forms of weakly cross correlated errors. It does not require estimation of an invertible error covariance matrix, it is much faster to implement, and is valid even if N is much larger than T. Monte Carlo evidence shows that the proposed test performs remarkably well even when T = 60 and N = 5;000. The test is applied to monthly returns on securities in the S&P 500 at the end of each month in real time, using rolling windows of size 60. Statistically significant evidence against Sharpe-Lintner CAPM and Fama-French three factor models are found mainly during the recent financial crisis. Also we find a significant negative correlation between a twelve-months moving average p-values of the test and excess returns of long/short equity strategies (relative to the return on S&P 500) over the period November 1994 to June 2015, suggesting that abnormal profits are earned during episodes of market inefficiencies