A Comparison of the Efficacy of Liquidity,Momentum, Size and Book‐to‐Market Value Factors in Equity Pricing on a Heterogeneous Sample: Evidence from Asia

This paper compares the size and book‐to‐market value factors of Fama and French (1993) alongside Momentum of Jagadeesh and Titman ( 1993 ) with two Liu ( 2006 ) liquidity factors formed from 1 year rebalancing and 1 month rebalancing respectively. A heterogeneous and comprehensive sample of the top blue chip stocks of all national Asian equity markets with further differentiation undertaken between sub samples formed for Japan only and Asia excluding Japan for period January 2000 to August 2014. Our empirical results suggest that multifactor time invariant pricing models based on augmented capital asset pricing model (CAPM) framework are ineffective in explaining the cross section of stock returns in the presence of significant inter and intra‐market segmentation. However an alternative model specification based on a time varying parameter specification and using same sets of factors yields significant enhancements in explaining cross section of stock returns across universe. We find that momentum factor largely lacks significance while a time varying two factor model, based on CAPM plus liquidity factor, is optimal. The liquidity factor being that of Liu (2006) and annually rebalanced. Our findings are important for investment managers seeking appropriate factors and modelling techniques to hedge against risks as well as firm's financial managers seeking to reduce costs of equity capital.     

Accounting Ratios and the Cross‐section of Expected Stock Returns

Under clean‐surplus accounting, the log return on a stock can be decomposed into a linear function of the contemporaneous log return on equity, the contemporaneous log dividend–price ratio (if the stock pays a dividend), and both the contemporaneous and lagged values of the log book‐to‐market equity ratio. This paper studies the implications of this decomposition for the cross‐section of conditional expected stock returns. The empirical analysis reveals that the log accounting ratios capture cross‐sectional variation in both the conditional mean and conditional variance of log stock returns, which is consistent with the decomposition. It also brings fresh insights to the relation between firm size (market equity) and conditional expected stock returns. The evidence indicates that the conditional median return increases with firm size, while the conditional return skewness decreases with firm size. Empirically, the skewness effect outweighs the median effect, leading to the well‐documented inverse relation between size and average returns. The results of out‐of‐sample tests suggest that investors could use the information provided by the observed values of the log accounting ratios to formulate more effective portfolio strategies.     

Multimarket Trading and Liquidity: Theory and Evidence

We develop a new model of multimarket trading to explain the differences in the foreign share of trading volume of internationally cross‐listed stocks. The model predicts that the trading volume of a cross‐listed stock is proportionally higher on the exchange in which the cross‐listed asset returns have greater correlation with returns of other assets traded on that market. We find robust empirical support for this prediction using stock return and volume data on 251 non‐U.S. stocks cross‐listed on major U.S. exchanges.     

Industry‐Specific Human Capital,Idiosyncratic Risk,and the Cross‐Section of Expected Stock Returns

Human capital is one of the largest assets in the economy and in theory may play an important role for asset pricing. Human capital is heterogeneous across investors. One source of heterogeneity is industry affiliation. I show that the cross‐section of expected stock returns is primarily affected by industry‐level rather than aggregate labor income risk. Furthermore, when human capital is excluded from the asset pricing model, the resulting idiosyncratic risk may appear to be priced. I find that the premium for idiosyncratic risk documented by several empirical studies depends on the covariance between stock and human capital returns.     

Corporate Governance and Expected Stock Returns: Evidence from Germany

Recent empirical work shows evidence for higher valuation of firms in countries with a better legal environment. We investigate whether differences in the quality of firm‐level corporate governance also help to explain firm performance in a cross‐section of companies within a single jurisdiction. Constructing a broad corporate governance rating (CGR) for German public firms, we document a positive relationship between governance practices and firm valuation. There is also evidence that expected stock returns are negatively correlated with firm‐level corporate governance, if dividend yields are used as proxies for the cost of capital. An investment strategy that bought high‐CGR firms and shorted low‐CGR firms earned abnormal returns of around 12% on an annual basis during the sample period.     

Aggregate Jump and Volatility Risk in the Cross‐Section of Stock Returns

We examine the pricing of both aggregate jump and volatility risk in the cross‐section of stock returns by constructing investable option trading strategies that load on one factor but are orthogonal to the other. Both aggregate jump and volatility risk help explain variation in expected returns. Consistent with theory, stocks with high sensitivities to jump and volatility risk have low expected returns. Both can be measured separately and are important economically, with a two‐standard‐deviation increase in jump (volatility) factor loadings associated with a 3.5% to 5.1% (2.7% to 2.9%) drop in expected annual stock returns.     

Foreign Exchange Volatility Is Priced in Equities

This paper finds that standard asset pricing models fail to explain the significantly negative delta hedging errors that occur as a result of the purchase of options on foreign exchange futures. Foreign exchange volatility does influence stock returns, however. The volatility of the JPY/USD exchange rate predicts the time series of stock returns and is priced in the cross‐section of stock returns.     

Growth Opportunities,Technology Shocks,and Asset Prices

We explore the impact of investment‐specific technology (IST) shocks on the cross section of stock returns. Using a structural model, we show that IST shocks have a differential effect on the value of assets in place and the value of growth opportunities. This differential sensitivity to IST shocks has two main implications. First, firm risk premia depend on the contribution of growth opportunities to firm value. Second, firms with similar levels of growth opportunities comove with each other, giving rise to the value factor in stock returns and the failure of the conditional CAPM. Our empirical tests confirm the model's predictions.     

CAPM for estimating the cost of equity capital: Interpreting the empirical evidence

We argue that the empirical evidence against the capital asset pricing model (CAPM) based on stock returns does not invalidate its use for estimating the cost of capital for projects in making capital budgeting decisions. Because stocks are backed not only by projects in place, but also by the options to modify current projects and undertake new ones, the expected returns on stocks need not satisfy the CAPM even when expected returns of projects do. We provide empirical support for our arguments by developing a method for estimating firms' project CAPM betas and project returns. Our findings justify the continued use of the CAPM by firms in spite of the mounting evidence against it based on the cross section of stock returns.     

Real Options Models of the Firm,Capacity Overhang,and the Cross Section of Stock Returns

We use a stochastic frontier model to obtain a stock‐level estimate of the difference between a firm's installed production capacity and its optimal capacity. We show that this “capacity overhang” estimate relates significantly negatively to the cross section of stock returns, even when controlling for popular pricing factors. The negative relation persists among small and large stocks, stocks with more or less reversible investments, and in good and bad economic states. Capacity overhang helps explain momentum and profitability anomalies, but not value and investment anomalies. Our evidence supports real options models of the firm featuring valuable divestment options.     

Equity order flow and exchange rate dynamics

This paper contributes to the literature on international portfolio choice in several ways. First, I generalize the model of Dunne et al. (2010) and derive order flow as the result of correlated belief changes by heterogeneous investors. This strategy delivers testable implications for the daily dynamics of stock flows, equity returns, and exchange rate changes. Second, I empirically confirm these conditions using fifteen years of high-frequency data for US stocks and daily data for twenty US bilateral exchange rates. Third, the model relies on differences in the volatility of country-specific shocks to account for the empirical results. It can explain why the ‘portfolio rebalancing motive’ is not important for commodity countries, as well as the asymmetric structure of currency and stock returns.     

Imperfect Information and Stock Market Volatility

The purpose of this paper is to (1) develop a model to show how imperfect information can create excess volatility in asset returns and (2) provide empirical evidence consistent with the model. In this framework, variations in information quality cause the market prices to fluctuate more than the corresponding economic fundamentals. Using high‐frequency data from 1988 to 2002, the empirical evidence supports the predictions of the model by showing that economic volatility, defined as squared deviations of the quarterly gross domestic product (GDP) growth rate from its long‐run trend, can explain about half of the variation in S&P 500‐stock index quarterly volatility.     

Mental Accounting, Loss Aversion, and Individual Stock Returns

We study equilibrium firm-level stock returns in two economies: one in which investors are loss averse over the fluctuations of their stock portfolio, and another in which they are loss averse over the fluctuations of individual stocks that they own. Both approaches can shed light on empirical phenomena, but we find the second approach to be more successful: In that economy, the typical individual stock return has a high mean and excess volatility, and there is a large value premium in the cross section which can, to some extent, be captured by a commonly used multifactor model.     

ASYMMETRIC COVARIANCE,VOLATILITY, AND THE EFFECT OF NEWS

We propose that covariance (rather than beta) asymmetry provides a superior framework for examining issues related to changing risk premiums. Accordingly, we investigate whether the conditional covariance between stock and market returns is asymmetric in response to good and bad news. Our model of conditional covariance accommodates both the sign and magnitude of return innovations, and we find significant covariance asymmetry that can explain, at least in part, the volatility feedback of stock returns. Our findings are consistent across firm size, firm leverage, and temporal and cross‐sectional aggregations.     

Does PIN affect equity prices around the world?

This study examines the empirical controversy over the pricing effect of the Easley, Hvidkjaer, and O?Hara (2002) probability of information-based trading, PIN, on a sample of 30,095 firms from 47 countries worldwide. Contrary to the empirical evidence of Easley, Hvidkjaer, and O?Hara, but consistent with that of Duarte and Young (2009), we do not find that PIN exhibits a positive effect on a cross section of expected stock returns in international markets. Alternative information-based trading measures also display no effect on expected stock returns, corroborating our finding that information risk proxied by PIN, in general, has no pricing effect in world markets.     

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.     

Cross‐sectional Tests of Conditional Asset Pricing Models: Evidence from the German Stock Market

We study the performance of conditional asset pricing models and multifactor models in explaining the German cross‐section of stock returns. We focus on several variables, which (according to previous research) are associated with market expectations on future market excess returns or business cycle conditions. Our results suggest that the empirical performance of the Capital Asset Pricing Model (CAPM) can be improved when allowing for time‐varying parameters of the stochastic discount factor. A conditional CAPM using the term spread explains the returns on our size and book‐to‐market sorted portfolios about as well as the Fama‐French three‐factor model and performs best in terms of the Hansen‐Jagannathan distance. Structural break tests do not necessarily indicate parameter instability of conditional model specifications. Another major finding of the paper is that the Fama‐French model – despite its generally good cross‐sectional performance – is subject to model instability. Unconditional models, however, do a better job than conditional ones at capturing time‐series predictability of the test portfolio returns.     

Relevance of the disposition effect on the options market: New evidence

A moneyness‐based propensity to sell (MPS) measure, at the aggregate level, determines the propensity of option holders to exercise their winning relative to losing positions. Using data on individual stock and S&P 500 Index options, we find that the MPS measure has significant predictive power over the cross section of delta‐hedged option returns. We test the disposition effect in the options market based on a long–short strategy that exploits price distortions induced by the disposition bias. More pronounced evidence of the disposition bias is found for individual at‐the‐money call options than put options where the significance of abnormal returns remains robust across different subsamples even after we control for the portfolio option greeks and market‐based risk factors. The profitability of the long–short strategy is related to limit‐to‐arbitrage proxies suggesting that behavioral explanations help explain the positive relation between the MPS measure and delta‐hedged option returns.     

Capital expenditures and firm performance: evidence from a cross‐sectional analysis of stock returns

Using a simple two‐period model of investment, we show that there should be a nonlinear relation between a firm's investment‐to‐capital ratio and its subsequent stock returns. This prediction finds substantial empirical support. The evidence indicates that the slope of the investment function is negative at low investment levels, close to zero at intermediate investment levels and negative at high investment levels. Our results, which are robust to the use of narrowly‐ and broadly‐defined measures of capital investment, pose a challenge to the hypothesis that the negative cross‐sectional correlation between investment and stock returns is attributable to some sort of overinvestment phenomenon.     

BETA,SIZE, RISK,AND RETURN

We relate the cross‐section of stock returns to firm size, beta, and total risk. We find that as extreme monthly security returns are censored from the data, the significance level decreases rapidly for the size variable and increases for beta and total risk. An analysis of up and down markets reaffirms our findings. Consequently, average returns relate positively with beta, negatively with total risk, and not at all with firm size. We infer that investors willingly accept a lower average return on high‐total‐risk investments as the trade‐off for buying a chance at an extreme positive return. JEL classification: G1.