The dynamics of mergers and acquisitions

This paper presents a dynamic model of takeovers based on the stock market valuations of merging firms. The model incorporates competition and imperfect information and determines the terms and timing of takeovers by solving option exercise games between bidding and target shareholders. The implications of the model for returns to stockholders are consistent with the available evidence. In addition, the model generates new predictions relating these returns to the drift, volatility and correlation coefficient of the bidder and the target stock returns and to the dispersion of beliefs regarding the benefits of the takeover.     

The Cross-Section of Expected Stock Returns: New Evidence from an Emerging Market

Over 300 factors have been found to explain the cross-section of expected stock returns. Empirical studies also show that findings from multifactor asset-pricing models have not been consistent in an emerging market. Using DuPont analysis and a residual income valuation model for 284 nonfinancial companies on Ho Chi Minh Stock Exchange during the period 2008–2014, findings suggest that the return on equity and its change are informative for stock returns in Vietnam. In addition, the level of capital turnover, financial cost ratio (FCR), and changes in capital and in the FCR contain incremental explanatory power for stock returns.     

Time-series and cross-sectional momentum in anomaly returns

We find strong evidence of time-series and cross-sectional momentum in the long–short returns of a comprehensive sample of anomalies. Strategies that exploit such persistence deliver significant abnormal returns that are robust to the stock momentum effect, cannot be explained by traditional asset-pricing models, and are more pronounced when arbitrage capital is scarcer or market liquidity is lower. Momentum in anomaly returns dissipates but does not reverse, in the long-run. Our findings are consistent with limits-to-arbitrage and slow-moving capital causing mispricing to persist. Supporting this explanation, we find that both the level and persistence of anomaly returns are positively related to idiosyncratic volatility.     

Capital Investment,Innovative Capacity,and Stock Returns

We study the dynamic implications of capital investment in innovative capacity (IC) on future stock returns, investment, and profitability by modeling the unique effects of IC investment on uncertain option generation/exercise and postexercise revenue. The model highlights the diverse effects of IC investment on expected returns in different postinvestment regimes and yields the novel prediction that, under the neoclassical assumption of nonincreasing revenue returns, IC investment is positively related to subsequent cumulative stock returns with a lag. The model also predicts a positive effect of IC investment on future investment and profitability. We find strong empirical support for these predictions.     

Foreign exchange risk and the cross-section of stock returns

We examine the relation between the cross-section of US stock returns and foreign exchange rates during the period from 1973 to 2002. We find that stocks most sensitive to foreign exchange risk (in absolute value) have lower returns than others. This implies a non-linear, negative premium for foreign exchange risk. Sensitivity to foreign exchange generates a cross-sectional spread in stock returns unexplained by existing asset-pricing models. Consequently, we form a zero-investment factor related to foreign exchange-sensitivity and show that it can reduce mean pricing errors for exchange-sensitive portfolios. One possible explanation for our findings includes Johnson's [2004. Forecast dispersion and the cross-section of expected returns. Journal of Finance, 59, 1957–1978] option-theoretic model in which expected returns are decreasing in idiosyncratic cashflow volatility.     

Return dispersion and expected returns

This paper proposes a two-factor asset-pricing model that incorporates market return and return dispersion. Consistent with this model, we find that stocks with higher sensitivities to return dispersion have higher average returns, and that return dispersion carries a significant positive price of risk. In particular, the return dispersion factor dominates the book-to-market factor in explaining cross-sectional expected returns. The return dispersion model outperforms the CAPM, MVM, IVM, and FF-3M when using a set of 5×5 test portfolios constructed from NYSE and AMEX stock returns from August 1963 to December 2005. Return dispersion continues to play an important role in explaining the cross-sectional variation of expected returns, even when market volatility, idiosyncratic volatility, size, book-to-market factors, and a momentum factor are included. This study sheds some light on the ability of return dispersion to explain expected returns beyond the standard asset-pricing factors. Our finding suggests that return dispersion captures two dimensions of systematic risk: the business cycle and fundamental economic restructuring.     

Market segmentation and international diversification across country and industry portfolios

We conjecture that partially segmented stock indexes that are characterized by low correlation with the world market are mainly priced by local factors and should produce abnormal returns relative to a global asset-pricing model. This implies a negative relation between correlation and future index returns in the presence of segmented indexes. Empirical evidence confirms such a relationship for the sample of industry indexes, suggesting a heterogeneous segmentation. However, we do not observe a similar pattern for country indexes. In addition, the international diversification potential of industries does not vanish during volatile periods. The hypothesis that the negative relationship should be stronger for the more segmented subsamples that are characterized by small market size and emerging country origin is verified for the industry sample. Thus, cross-industry diversification is superior to mere cross-country diversification.     

The independence axiom and asset returns

This paper integrates models of atemporal risk preference that relax the independence axiom into a recursive intertemporal asset-pricing framework. The resulting models are amenable to empirical analysis using market data and standard Euler equation methods. We are thereby able to provide the first nonlaboratory-based evidence regarding the usefulness of several new theories of risk preference for addressing standard problems in dynamic economics. Using both stock and bond returns data, we find that a model incorporating risk preferences that exhibit first-order risk aversion accounts for significantly more of the mean and autocorrelation properties of the data than models that exhibit only second-order risk aversion. Unlike the latter class of models which require parameter estimates that are outside of the admissible parameter space, e.g., negative rates of time preference, the model with first-order risk aversion generates point estimates that are economically meaningful. We also examine the relationship between first-order risk aversion and models that employ exogenous stochastic switching processes for consumption growth.     

Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation

Linear and nonlinear Granger causality tests are used to examine the dynamic relation between daily Dow Jones stock returns and percentage changes in New York Stock Exchange trading volume. We find evidence of significant bidirectional nonlinear causality between returns and volume. We also examine whether the nonlinear causality from volume to returns can be explained by volume serving as a proxy for information flow in the stochastic process generating stock return variance as suggested by Clark's (1973) latent common-factor model. After controlling for volatility persistence in returns, we continue to find evidence of nonlinear causality from volume to returns.     

Stock and bond market interactions with level and asymmetry dynamics: An out-of-sample application

We model the dynamic interaction between stock and bond returns using a multivariate model with level effects and asymmetries in conditional volatility. We examine the out-of-sample performance using daily returns on the S&P 500 index and 10 year Treasury bond. We find evidence for significant (cross-) asymmetries in the conditional volatility and level effects in bond returns. The out-of-sample covariance matrix forecasts of the model imply that an investor is willing to pay between 129 and 820 basis points per year for using a dynamic trading strategy instead of a passive strategy.     

Tests of Asset Pricing with Time-Varying Expected Risk Premiums and Market Betas

Tests of asset-pricing models are developed that allow expected risk premiums and market betas to vary over time. These tests exploit the relation between expected excess returns and current market values. Using weekly data for 1963 through 1982 on ten common stock portfolios formed according to equity capitalization, a single-risk-premium model is not rejected if the expected premium is time varying and is not constrained to correspond to a market factor. Conditional mean-variance efficiency of a value-weighted stock index is rejected, and the rejection is insensitive to how much variability of expected risk premiums is assumed.     

The persistent effects of a false news shock

In September 2008, a six-year-old article about the 2002 bankruptcy of United Airlines' parent company resurfaced on the Internet and was mistakenly believed to be reporting a new bankruptcy filing by the company. This episode caused the company's stock price to drop by as much as 76% in just a few minutes, before NASDAQ halted trading. After the “news” had been identified as false, the stock price rebounded, but still ended the day 11.2% below the previous close. We explore this natural experiment by using a simple asset-pricing model to study the aftermath of this false news shock. We find that, after three trading sessions, the company's stock was still trading below the two-standard-deviation band implied by the model and that it returned to within one standard deviation only during the sixth trading session. On the seventh day after the episode, the stock was trading at the level predicted by the asset-pricing model. We investigate several potential explanations for this finding, but fail to find empirical evidence supporting any of them. We also document that the false news shock had a persistent negative effect on the stock prices of other major airline companies. This is consistent with the view that contagion effects would have dominated competitive effects had the bankruptcy actually taken place.     

Relationship between gold and stock markets during the global financial crisis: Evidence from nonlinear causality tests

This paper investigates the nonlinear dynamic co-movements between gold returns, stock market returns and stock market volatility during the recent global financial crisis for the UK (FTSE 100), the US (S&P 500) and Japan (Nikkei 225). Initially, the bivariate dynamic relationships between i) gold returns and stock market returns and ii) gold returns and stock market volatility are tested; both of these relationships are further investigated in the multivariate nonlinear settings by including changes in the three-month LIBOR rates. In this paper correlation integrals based on the bivariate model show significant evidence of nonlinear feedback effect among the variables during the financial crisis period for all the countries understudy. Very limited evidence of significant feedback is found during the pre-crisis period. Results from the multivariate tests including changes in the LIBOR rates provide results similar to the bivariate results. These results imply that gold may not perform well as a safe haven during the financial crisis period due to the bidirectional interdependence between gold returns and, stock returns as well as stock market volatility. However, gold may be used as a hedge against stock market returns and volatility in stable financial conditions.     

EQUITY VALUATION EFFECTS OF FORCED WARRANT EXERCISE

We examine stock price reactions to announced calls of in-the-money warrants and find a significant average devaluation in excess of 4 percent, consistent with the recent literature. We test theoretical predictions based on asymmetric information, agency costs, and corporate control in a cross-sectional model of announcement-period returns and find support for voting rights and ownership dilution as an explanation. We find evidence of some price recovery after the call announcement; however, further evidence of a liquidity-based explanation is mixed.     

Developing a Trading Rule from the FTSE-100 Stock Index Futures Contract: Evidence in Support of the EMH

An extensive literature documents the predictability of both short and long horizon returns, over a wide range of sample periods, frequencies and markets. This predictability may represent weak form inefficiency, or it may be caused by a failure to account for a time-variation in risk. We develop statistically reliable ex ante models of the returns on the FTSE-100 stock index futures contract and test a simple trading rule based on the out-of-sample predictions from these models. We interpret the failure of our ex ante model to produce abnormal returns for a risk neutral investor as evidence in favour of the EMH. Our trading rule results clearly suggest that we should be careful in interpreting such ex ante models as evidence of financial market inefficiency.     

Conditional conservatism and cost of capital

We empirically test the association between conditional conservatism and cost of equity capital. Conditional conservatism imposes stronger verification requirements for the recognition of economic gains than economic losses, resulting in earnings that reflect losses faster than gains. This asymmetric reporting of gains and losses is predicted to lower firm cost of equity capital by increasing bad news reporting precision, thereby reducing information uncertainty (Guay and Verrecchia 2007) and the volatility of future stock prices (Suijs 2008). Using standard asset-pricing tests, we find a significant negative relation between conditional conservatism and excess average stock returns over the period 1975–2003. This evidence is corroborated by further tests on the association between conditional conservatism and measures of implied cost of capital derived from analysts’ forecasts.     

Heteroskedasticity in Stock Returns

We use predictions of aggregate stock return variances from daily data to estimate time-varying monthly variances for size-ranked portfolios. We propose and estimate a single factor model of heteroskedasticity for portfolio returns. This model implies time-varying betas. Implications of heteroskedasticity and time-varying betas for tests of the capital asset pricing model (CAPM) are then documented. Accounting for heteroskedasticity increases the evidence that risk-adjusted returns are related to firm size. We also estimate a constant correlation model. Portfolio volatilities predicted by this model are similar to those predicted by more complex multivariate generalized-autoregressive-conditional-heteroskedasticity (GARCH) procedures.     

Price Convexity and Skewness

This paper develops a model in which investors who are prohibited from short selling agree to disagree on the precision of a publicly observed signal. The model implies that the equilibrium price is a convex function of the public signal. The model predicts that (1) the stock price reacts more to good news than to bad news; (2) the skewness of stock returns is positively correlated with contemporaneous returns, but negatively correlated with lagged returns; (3) short sale constraints increase rather than decrease skewness; and (4) disagreement about information precision increases skewness. Empirical tests conducted find supportive evidence for all these predictions.     

Asymmetric Correlation and Volatility Dynamics among Stock, Bond, and Securitized Real Estate Markets

We apply a multivariate asymmetric generalized dynamic conditional correlation GARCH model to daily index returns of S&P500, US corporate bonds, and their real estate counterparts (REITs and CMBS) from 1999 to 2008. We document, for the first time, evidence for asymmetric volatilities and correlations in CMBS and REITs. Due to their high levels of leverage, REIT returns exhibit stronger asymmetric volatilities. Also, both REIT and stock returns show strong evidence of asymmetries in their conditional correlation, suggesting reduced hedging potential of REITs against the stock market downturn during the sample period. There is also evidence that corporate bonds and CMBS may provide diversification benefits for stocks and REITs. Furthermore, we demonstrate that default spread and stock market volatility play a significant role in driving dynamics of these conditional correlations and that there is a significant structural break in the correlations caused by the recent financial crisis.     

Firm characteristics,alternative factors,and asset-pricing anomalies: evidence from Japan

Based on the errors-in-variables-free approach proposed by Brennan et al. [J. Financial Econ., 1998, 49, 345–373], we investigate the competing explanatory capabilities of alternative multi-factor models when examining various asset-pricing anomalies using Japanese data for the period 1978–2006. We find that turnover and book-to-market (BM) ratio are the two major characteristics that significantly explain the average stock returns. A further sub-period analysis reveals that the turnover effect is significant only before 1990, but cannot be explained by any multifactor models. In contrast, the BM premium is significant only after 1990, and can be explained by the Fama–French three-factor model. Thus, the results suggest that asset-pricing anomalies documented in the literature are not universal, and may be different across different markets.