Liquidity costs,idiosyncratic volatility and expected stock returns

This paper considers liquidity as an explanation for the positive association between expected idiosyncratic volatility (IV) and expected stock returns. Liquidity costs may affect the stock returns, through bid-ask bounce and other microstructure-induced noise, which will affect the estimation of IV. We use a novel method (developed by Weaver, 1991) to eliminate microstructure influences from stock closing price-based returns and then estimate IV. We show that there is a premium for IV in value-weighted portfolios, but this premium is less strong after correcting returns for microstructure bias. We further show that this premium is driven by liquidity in the prior month after correcting returns for microstructure noise. The pricing results from equally-weighted portfolios indicate that IV does not predict returns either before or after controlling for liquidity costs. These findings are robust after controlling for common risk factors as well as analysing double-sorted portfolios based on IV and liquidity.     

New return anomalies and new-Keynesian ICAPM

I propose a new multi-factor asset pricing model with new-Keynesian factors to explain stock return anomalies from 1972Q1 to 2009Q2. This new model explains the average returns across testing portfolios formed on financial distress, momentum, and standardized unexpected earnings with misspecification-robust statistics. Test portfolios formed on net stock issues and total accruals are also partly explained by new-Keynesian factors. Two monetary policy factors play an important role in explaining these new anomalies. The credit aspect of these new anomalies suggests an economic rationale for the model through capital market imperfections and the credit channel of monetary policy mechanism.     

The Variation of Economic Risk Premiums in Real Estate Returns

We examine the predictable components of returns on stocks, bonds, and real estate investment trusts (REITs). We employ a multiple-beta asset pricing model and find that there are varying degrees of predictability among stocks, bonds, and REITs. Furthermore, we find that most of the predictability of returns is associated with the economic variables employed in the asset pricing model. The stock market risk premium is highly important in capturing the predictable variation in stock portfolios, and the bond market risk premiums (term and risk structure of interest rates) are important in capturing the predictable variation in bond portfolios. For REITs, however, both the stock and bond market risk premiums capture the predictable variation in returns. REITs have comparable return predictability to stock portfolios. We conclude that there is an important economic risk premium for REITs that are not captured by traditional multiple-beta asset pricing models.     

ROBUSTNESS OF THE HEADQUARTERS‐CITY EFFECT ON STOCK RETURNS

Recent studies report that U.S. firms headquartered near each other experience positive comovement in their stock returns, a finding suggestive of local biases in equity trading activity. We investigate the robustness of these findings and find that including additional pricing factors in models for monthly stock returns materially reduces the magnitude of the headquarters‐city effect in stock returns. Additionally, we find that an implicit null hypothesis of zero local return comovement is inappropriate as there is positive comovement between a stock's return and returns on portfolios of stocks from nonheadquarters cities, on average. Nevertheless, results benchmarked against estimates based on resampling methods indicate a significant and robust headquarters‐city effect in stock returns.     

Common risk factors in bank stocks

This paper provides evidence on the risk factors that are priced in bank equities. Alternative empirical models with precedent in the nonfinancial asset pricing literature are tested, including the single-factor CAPM, three-factor Fama–French model, and ICAPM. Our empirical results indicate that an unconditional two-factor ICAPM model that includes the stock market excess return and shocks to the slope of the yield curve is useful in explaining the cross-section of bank stock returns. However, we find no evidence that firm specific factors such as size and book-to-market ratios are priced in bank stock returns. These results have a number of important implications for the estimation of the banks’ cost of capital as well as regulatory initiatives to utilize market discipline to evaluate bank risk under Basel II.     

An empirical analysis of marginal conditional stochastic dominance

Stochastic dominance is a more general approach to expected utility maximization than the widely accepted mean–variance analysis. However, when applied to portfolios of assets, stochastic dominance rules become too complicated for meaningful empirical analysis, and, thus, its practical relevance has been difficult to establish. This paper develops a framework based on the concept of Marginal Conditional Stochastic Dominance (MCSD), introduced by Shalit and Yitzhaki (1994), to test for the first time the relationship between second order stochastic dominance (SSD) and stock returns. We find evidence that MCSD is a significant determinant of stock returns. Our results are robust with respect to the most popular pricing models.     

Cashflow news,the value premium and an asset pricing view on European stock market integration

The decomposition of national CAPM market betas of European countries’ value and growth portfolio returns into cashflow and discount rate news driven components reveals that i) high average returns on value portfolios are associated with disproportionately high sensitivity to national cashflow news which corroborates recent evidence for the U.S. and ii) two-beta variants of national CAPMs capture the cross-sectional dispersion in European stock returns. The latter finding is suggestive of relatively well integrated stock markets among the core European countries and reflects basic asset pricing theory. One (national) discount factor should price any (international) asset.     

Asset pricing: A tale of two days

We show that asset prices behave very differently on days when important macroeconomic news is scheduled for announcement. In addition to significantly higher average returns for risky assets on announcement days, return patterns are much easier to reconcile with standard asset pricing theories, both cross-sectionally and over time. On such days, stock market beta is strongly related to average returns. This positive relation holds for individual stocks, for various test portfolios, and even for bonds and currencies, suggesting that beta is after all an important measure of systematic risk. Furthermore, a robust risk–return trade-off exists on announcement days. Expected variance is positively related to future aggregated quarterly announcement day returns, but not to aggregated non-announcement day returns. We explore the implications of our findings in the context of various asset pricing models.     

The alpha factor asset pricing model: A parable

Recent empirical studies use the returns of attribute-sorted portfolios of common stocks as if they represent risk factors in an asset pricing model. If the attributes are chosen following an empirically observed relation to the cross-section of stock returns, such portfolios will appear to be useful risk factors, even when the attributes are completely unrelated to risk. We illustrate this result using a parable and argue that the moral of the story is important in practice.     

Cash, investments and asset returns

We use an investment-based asset pricing model to examine the effect of firms’ investments relative to cash holdings on stock returns, assuming holding cash lowers transaction costs. We find that mimicking portfolios based on investments relative to non-cash capital and based on investments relative to cash capital are priced for various testing portfolios. On average, momentum stocks and growth stocks are more sensitive to the factor constructed using investment relative to cash.     

Financial constraints and stock returns

We test whether the impact of financial constraints on firmvalue is observable in stock returns. We form portfolios offirms based on observable characteristics related to financialconstraints and test for common variation in stock returns.Financially constrained firms' stock returns move together overtime, suggesting that constrained firms are subject to commonshocks. Constrained firms have low average stock returns inour 1968-1997 sample of growing manufacturing firms. We findno evidence that the relative performance of constrained firmsreflects monetary policy, credit conditions, or business cycles.     

Sovereign Credit Risk,Banks' Government Support,and Bank Stock Returns around the World

We explore the joint effect of expected government support to banks and changes in sovereign credit ratings on bank stock returns using data for banks in 37 countries between 1995 and 2011. We find that sovereign credit rating downgrades have a large negative effect on bank stock returns for those banks that are expected to receive stronger support from their governments. This result is stronger for banks in advanced economies where governments are better positioned to provide that support. Our results suggest that stock market investors perceive sovereigns and domestic banks as markedly interconnected, partly through government guarantees.     

Stock return expectations in the credit market

In this paper we compute long-term stock return expectations (across the business cycle) for individual firms using information backed out from the credit derivatives market. Our methodology builds on previous theoretical results in the literature on stock return expectations and, empirically, we demonstrate a close relationship between credit-implied stock return expectations and future realized stock returns. We also find stock portfolios selected based on credit-implied stock return forecasts to beat equally- and value-weighted portfolios of the same stocks out-of-sample. Contrary to many other studies, our expectations/predictions are made at the individual stock level rather than at the portfolio level, and no parameter estimations using historical stock price- or credit spread observations are needed.     

Evaluating asset pricing models in the Korean stock market

This paper evaluates and compares asset pricing models in the Korean stock market. The asset pricing models considered are the CAPM, APT-motivated models, the Consumption-based CAPM, Intertemporal CAPM-motivated models, and the Jagannathan and Wang conditional CAPM model. By using various test portfolios as well as individual stocks, we conduct time-series tests and cross-sectional regression tests based on individual t-tests, the joint F-tests, the Hansen and Jagannathan (1997) distance, and R-squares. Overall, the Fama and French (1993) five-factor model performs most satisfactorily among the asset pricing models considered in explaining the intertemporal and cross-sectional behavior of stock returns in Korea. The Fama and French (1993) three-factor model, the Chen et al. (2010) three-factor model, and the Campbell (1996) model are the next. The results indicate that the two bond portfolios, term spread and default spread, play an important role in explaining stock returns in Korea.     

Liquidity and asset pricing: Evidence from the Hong Kong stock market

This study investigates the role of liquidity in pricing stock returns in the Hong Kong stock market. Our results show that liquidity is an important factor for pricing returns in Hong Kong after taking well-documented asset pricing factors into consideration. The results are robust to adding portfolio residuals and higher moment factor in the factor models. The results are also robust to seasonality, and conditional-market tests. We also compare alternative factor models and find that the liquidity four-factor model (market excess return, size, book-to-market ratio, and liquidity) is the best model to explain stock returns in the Hong Kong stock market, while the momentum factor is not found to be priced.     

Liquidity,Skewness and Stock Returns: Evidence from Chinese Stock Market

In this paper, a capital asset pricing model (CAPM) incorporating liquidity and skewness factors is proposed and tested by using the Chinese stock market data. The empirical results indicate that, under various market conditions, the liquidity-adjusted three-moment CAPM provides a better fit to the realized returns of various stock portfolios. Overall, this research reveals that illiquidity cost, liquidity risk and as well as skewness have important impacts on asset pricing in the Chinese stock market.     

Book Assets,Real Estate,and Returns on Common Stock

Since real estate is common to most firms, this study examines whether there is a real estate factor in common stock returns that is not completely captured by existing asset pricing models. The three-factor model of Fama and French (1993), hereafter FF, is extended to incorporate a unique real estate factor. Using his extended-FF model, we examine the returns on 53 industry portfolios of common stocks over the 1972 through 1995 time period. The results indicate that a significant 19 percent of the industries are systematically related to the real estate factor. Most interestingly, we show that the loading of the real estate factor in common stock return is related to the loading of the book-to-market equity factor in these returns. We also construct decile portfolios of common stocks based on historical sensitivities of common stock returns to the real estate factor. The coefficients on the real estate factor vary systematically across the decile portfolios. The results of our analysis suggest that portfolio managers should manage their exposure to real estate.     

What lies behind the asset growth effect?

This study finds that changes in total factor productivity (TFP) serve as one of the drivers behind the asset growth effect. Firms increase (decrease) assets when there is an increase (decrease) in TFP. And increases (decreases) in TFP also cause corresponding increases (decreases) in earnings and returns. Subsequently, changes in TFP reverse, which also reverse earnings and returns, leading to the observed asset growth effect. Our results are robust to sorting using the Fama-French five-factor model and momentum factor, and its asset pricing implications, using low-high spread asset growth portfolios with correspondingly low-high spread TFP changes.     

Empirical Evidence on Capital Investment, Growth Options, and Security Returns

Growth in capital expenditures conditions subsequent classification of firms to portfolios based on size and book‐to‐market ratios, as in the widely used Fama and French (1992, 1993) methods. Growth in capital expenditures also explains returns to portfolios and the cross section of future stock returns. These findings are consistent with recent theoretical models (e.g., Berk, Green, and Naik (1999)) in which the exercise of investment‐growth options results in changes in both valuation and expected stock returns.