Asset Pricing with a Reference Level of Consumption: New Evidence from the Cross-Section of Stock Returns

This paper presents an empirical evaluation of recently proposed asset pricing models which extend the standard preference specification by a reference level of consumption. We motivate an alternative model that accounts for the return on human capital as a determinant of the reference level. Our analysis is based on a broad cross-section of test assets which provides a level playing field for a comparison to established benchmark models. The human capital extended reference level model does a good job in explaining size and value premia. Estimated on Fama and French's size and book-to-market sorted portfolios it outperforms Lettau and Ludvigson's scaled CCAPM and delivers average pricing errors comparable to the Fama-French three-factor model. --Consumption-Based Asset Pricing,Cross-Section of Stock Returns,Reference Level

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. --creative destruction,asset pricing,size and value premium,patents

Consumption-Based Asset Pricing with a Reference Level: New Evidence from the Cross-Section of Stock Returns

This paper presents an empirical evaluation of recently proposed asset pricing models which extend the standard preference specification by a reference level of consumption. The novelty is that we use a broad cross-section of test assets, which provides a level playing field for a comparison to well-established benchmark models. We also motivate a specification that accounts for the return on human capital as a determinant of the reference level. We find that this extension does a good job in explaining the cross-sectional variation in average returns across the 25 Fama- French portfolios with pricing errors close to those of Lettau/Ludvigson's celebrated scaled factor models. --Consumption-based Asset Pricing,Cross-Section of Stock Returns,Reference Level

International price discovery in the presence of microstructure noise

This paper addresses and resolves the issue of microstructure noise when measuring the relative importance of home and U.S. market in the price discovery process of Canadian interlisted stocks. In order to avoid large bounds for information shares, previous studies applying the Cholesky decomposition within the Hasbrouck (1995) framework had to rely on high frequency data. However, due to the considerable amount of microstructure noise inherent in return data at very high frequencies, these estimators are distorted. We offer a modified approach that identifies unique information shares based on distributional assumptions and thereby enables us to control for microstructure noise. Our results indicate that the role of the U.S. market in the price discovery process of Canadian interlisted stocks has been underestimated so far. Moreover, we suggest that rather than stock specific factors, market characteristics determine information shares

Tell-tale tails: A data driven approach to estimate unique market information shares

The trading of securities on multiple markets raises the question of each market's share in the discovery of the informationally efficient price. We exploit salient distributional features of multivariate financial price processes to uniquely determine these contributions. Thereby we resolve the main drawback of the widely used Hasbrouck (1995) methodology which merely delivers upper and lower bounds of a market's information share. When these bounds diverge, as is the case in many applications, informational leadership becomes blurred. We show how fat tails and tail dependence of price changes, which emerge as a result of differences in market design and liquidity, can be exploited to estimate unique information shares. The empirical application of the new methodology emphasizes the leading role of the credit derivatives market compared to the corporate bond market in pricing credit risk during the pre-crisis period. --price discovery,information share,fat tails,tail dependence,liquidity,credit risk

International price discovery in the presence of market microstructure effects

This paper addresses and resolves the problems caused by microstructure effects when measuring the relative importance of home and U.S. market in the price discovery process of internationally cross listed stocks. In order to avoid large bounds for information shares, previous studies applying the Cholesky decomposition within the Hasbrouck (1995) framework had to rely on high frequency data. However, this entails a potential bias of estimated information shares induced by microstructure effects. We propose a modified approach that relies on distributional assumptions and yields unique and unbiased information shares. Our results indicate that the role of the U.S. market in the price discovery process of Canadian interlisted stocks has been severely underestimated to date. Moreover, we find that rather than stock specific factors, market design determines information shares. --international cross-listings,market microstructure effects,price discovery

Limit order books and trade informativeness

In the microstructure literature, information asymmetry is an important determinant of market liquidity. The classic setting is that uninformed dedicated liquidity suppliers charge price concessions when incoming market orders are likely to be informationally motivated. In limit order book markets, however, this relationship is less clear, as market participants can switch roles, and freely choose to immediately demand or patiently supply liquidity by submitting either market or limit orders. We study the importance of information asymmetry in limit order books based on a recent sample of thirty German DAX stocks. We find that Hasbrouck’s (1991) measure of trade informativeness Granger-causes book liquidity, in particular that required to fill large market orders. Picking-off risk due to public news induced volatility is more important for top-of-the book liquidity supply. In our multivariate analysis we control for volatility, trading volume, trading intensity and order imbalance to isolate the effect of trade informativeness on book liquidity. JEL Classification: G14 Keywords: Price Impact of Trades , Trading Intensity , Dynamic Duration Models, Spread Decomposition Models , Adverse Selection Ris

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants