COMMON STOCK RETURNS,EXPECTED INFLATION,AND THE RATIONAL EXPECTATIONS HYPOTHESIS

This paper provides empirical evidence that expected inflation has a cross-sectional impact on common stock returns. The study differs from others in that (a) the relation between stock returns and expected inflation is investigated in a two-factor asset pricing model, where the factors are the return on an equally weighted stock portfolio and the expected rate of inflation; (b) the estimation of the expected rate of inflation is based on the rational expectations hypothesis of Muth; and (c) a non-linear seemingly unrelated regression technique is employed to determine consistent and asymptotically efficient estimates. The joint hypothesis of the two-factor asset pricing model and rational expectations is not rejected in this study. It is found that the return on common stocks is significantly affected by expected inflation. Also stocks whose returns are positively correlated with expected inflation have lower expected returns.     

On estimating the expected return on the market: An exploratory investigation

The expected market return is a number frequently required for the solution of many investment and corporate finance problems, but by comparison with other financial variables, there has been little research on estimating this expected return. Current practice for estimating the expected market return adds the historical average realized excess market returns to the current observed interest rate. While this model explicitly reflects the dependence of the market return on the interest rate, it fails to account for the effect of changes in the level of market risk. Three models of equilibrium expected market returns which reflect this dependence are analyzed in this paper. Estimation procedures which incorporate the prior restriction that equilibrium expected excess returns on the market must be positive are derived and applied to return data for the period 1926–1978. The principal conclusions from this exploratory investigation are: (1) in estimating models of the expected market return, the non-negativity restriction of the expected excess return should be explicity included as part of the specification: (2) estimators which use realized returns should be adjusted for heteroscedasticity.     

Risk and Return: A Revisit Using Expected Returns

This paper uses direct estimates of expected returns to examine the link between standard measures of financial risk and investor return requirements. The results show that systematic risk commands a significant positive risk premium, much larger than found using historical returns as proxies for expectations. Furthermore, there are nonlinearities in the relationship between risk and return. Finally, we show that expected returns and risk premiums in the equity markets change over time and that these changes are related to changes in interest rates on U.S. government obligations.     

Predictive Systems: Living with Imperfect Predictors

We develop a framework for estimating expected returns—a  predictive system —that allows predictors to be imperfectly correlated with the conditional expected return. When predictors are imperfect, the estimated expected return depends on past returns in a manner that hinges on the correlation between unexpected returns and innovations in expected returns. We find empirically that prior beliefs about this correlation, which is most likely negative, substantially affect estimates of expected returns as well as various inferences about predictability, including assessments of a predictor's usefulness. Compared to standard predictive regressions, predictive systems deliver different expected returns with higher estimated precision.     

EXPECTED VOLATILITY,UNEXPECTED VOLATILITY,AND THE CROSS‐SECTION OF STOCK RETURNS

The existing literature finds conflicting results on the cross‐sectional relation between expected returns and idiosyncratic volatility. We contend that at the firm level, the sample correlation between unexpected returns and expected idiosyncratic volatility can cloud the true relation between the expected return and expected idiosyncratic volatility. We show strong evidence that unexpected idiosyncratic volatility is positively related to unexpected returns. Using unexpected idiosyncratic volatility to control for unexpected returns, we find expected idiosyncratic volatility to be significantly and positively related to expected returns. This result holds after controlling for various firm characteristics, and it is robust across different sample periods.     

Sensitivity of Multivariate Tests of the Capital Asset-Pricing Model to the Return Measurement Interval

The capital asset-pricing model's (CAPM) primary empirical implication is a positively sloped linear relation between a security's expected rate of return and its relative risk (beta). Recent research indicates that inferences about the risk-return relation are sensitive to the choice of the return measurement interval. We perform multivariate tests of the Sharpe-Lintner CAPM using monthly and annual returns on market-value-ranked portfolios. The CAPM is rejected using monthly returns, a result consistent with previous research. In contrast, we fail to reject the CAPM when annual holding period returns are used.     

Robust anomalies? A close look at accrual‐based trading strategy returns

The last 40 years have seen an extensive literature documenting so‐called anomalies in major capital markets. Evidence of ‘abnormal’ returns associated with trading strategies based on readily observable phenomena such as accounting‐based data involves experimental design choices that can be expected to influence the results. We show how evidence of an accrual anomaly in Australia is sensitive to research design specifications such as the choice of proxy for total accruals; the definition of abnormal returns (i.e. the return generating model); the impact of data trimming as a response to exceptionally large returns; and the choice between value and equal weighting of returns. We show that research design choices do matter and help reconcile conflicting prior evidence of any accrual anomaly in Australia. More broadly, our results suggest the need for caution in drawing inferences from trading strategy tests which claim to identify anomalies.     

Explaining the accrual anomaly by market expectations of future returns and earnings

This study examines the accrual anomaly under the framework of the Campbell [Campbell, J.Y. (1991). A variance decomposition for stock returns. Economic Journal 101 (405), 157-179.] model. The Campbell (1991) model shows that realized asset returns are a joint function of 1) expected returns, 2) revisions in market expected future returns (i.e., return news), and 3) revisions in market expected future cash flows (i.e., cash flow news). The current study adopts the Easton [Easton, P. (2004). PE ratios, PEG ratios, and estimating the implied expected rate of return on equity capital. The Accounting Review 79 (1), 73-96.] model to estimate proxies for expected returns, return news, and cash flow news. The results show that firms with low accruals have lower expected returns than firms with high accruals, which is contradictory to prior research that argues that firms with low accruals are more risky. However, investors underestimate (overestimate) future earnings growth, a proxy for cash flow growth, for low (high) accrual firms. Further analysis demonstrates that earnings news (proxy for cash flow news) plays a major role in explaining abnormal returns associated with the accrual anomaly.     

The selection of multinational equity portfolios: forecasting models and estimation risk

The problem considered is the selection of a portfolio of international assets, particularly the forecasting of the inputs to a selection algorithm. Four models of the asset return generating process are considered, two of which ignore the international nature of the universe of assets, two which exploit it in different ways. Several estimation methods are considered for each component: expected return, variance and covariance of returns. The combinations of model and estimation method are first evaluated in terms of their forecasting performance for the components mentioned for the individual assets. The universe used is the components of the Financial Times Eurotrack 100 Index. Significant differences were found between the forecasting accuracy of the methods considered for each component. In the final stage of the analysis, a comparison of the returns on portfolios chosen using each combination showed a significant difference. The analysis suggests that the choice of estimation method is more critical than the choice of pricing model.     

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.     

Conditional Skewness in Asset Pricing Tests

If asset returns have systematic skewness, expected returns should include rewards for accepting this risk. We formalize this intuition with an asset pricing model that incorporates conditional skewness. Our results show that conditional skewness helps explain the cross-sectional variation of expected returns across assets and is significant even when factors based on size and book-to-market are included. Systematic skewness is economically important and commands a risk premium, on average, of 3.60 percent per year. Our results suggest that the momentum effect is related to systematic skewness. The low expected return momentum portfolios have higher skewness than high expected return portfolios.     

Asymmetries of the intraday return-volatility relation

This study investigates the asymmetry of the intraday return-volatility relation at different return horizons ranging from 1, 5, 10, 15, up to 60 min and compares the empirical results with results for the daily return horizon. Using data on the S&P 500 (SPX) and the VIX from September 25, 2003 to December 30, 2011 and a Quantile-Regression approach, we observe strong negative return-volatility relation over all return horizons. However, this negative relation is asymmetric in three different aspects. First, the effects of positive and negative returns on volatility are different and more pronounced for negative returns. Second, for both positive and negative returns, the effect is conditional on the distribution of volatility changes. The absolute effect is up to five times larger in the extreme tails of the distribution. Third, at the intraday level, there is evidence of both autocorrelation in volatility changes and cross-autocorrelation with returns. This lead-lag relation with returns is also very asymmetric and more pronounced in the tails of the distribution. These effects are, however, not observed at the daily return horizon.     

Covariance complexity and rates of return on assets

This paper considers the estimation of the expected rate of return on a set of risky assets. The approach to estimation focuses on the covariance matrix for the returns. The structure in the covariance matrix determines shared information which is useful in estimating the mean return for each asset. An empirical Bayes estimator is developed using the covariance structure of the returns distribution. The estimator is an improvement on the maximum likelihood and Bayes–Stein estimators in terms of mean squared error. The effect of reduced estimation error on accumulated wealth is analyzed for the portfolio choice model with constant relative risk aversion utility.     

Are stock markets really efficient? Evidence of the adaptive market hypothesis

This study examines the adaptive market hypothesis in the S&P500, FTSE100, NIKKEI225 and EURO STOXX 50 by testing for stock return predictability using daily data from January 1990 to May 2014. We apply three bootstrapped versions of the variance ratio test to the raw stock returns and also whiten the returns through an AR-GARCH process to study the nonlinear predictability after accounting for conditional heteroscedasticity through the BDS test. We evaluate the time-varying return predictability by applying these tests to fixed-length moving subsample windows and also examine whether there is a relationship between the level of predictability in stock returns and market conditions. The results show that there are periods of statistically significant return predictability, but also episodes of no statistically significant predictability in stock returns. We also find that certain market conditions are statistically significantly related to predictability in certain markets but each market interacts differently with the different market conditions. Therefore our findings suggest that return predictability in stock markets does vary over time in a manner consistent with the adaptive market hypothesis and that each market adapts differently to certain market conditions. Consequently our findings suggest that investors should view each market independently since different markets experience contrasting levels of predictability, which are related to market conditions.     

The abnormal return associated with consecutive dividend increases

Several studies conclude that dividend changes that are seemingly predictable on a calendar basis attract abnormal returns. We study the abnormal returns associated with consecutive dividend increases to understand this puzzle. We use regression techniques to study the relation between the number of consecutive dividend increases and the abnormal return associated with the events. Further, we study whether this relation is sensitive to firm characteristics by partitioning the regressions by the characteristics that influence the abnormal return. Our results show that the abnormal returns associated with consecutive dividend increases decline at a diminishing rate and they do not disappear, consistent with the puzzle. In addition, the decline in returns is slowest among firms that are unprofitable, small, or have high payouts. These findings suggest that the abnormal returns persist because firms that are not expected to continue a dividend-increase streak based on their characteristics do so, surprising the market and perpetuating the abnormal return.     

Cross-sectional determinants of New Zealand share market returns

We present evidence of the cross-sectional relation between security returns, beta, firm size and book-to-market ratio over the period 1971 to 1993 on the New Zealand sharemarket. Our results suggest that the NZSE-40 market index is not a mean-variance efficient market proxy—the betas calculated with respect to it being of little use for explaining expected returns cross-sectionally. Also, there is a significant positive relation between book-to-market ratio and average return.     

Active Portfolio Management,Implied Expected Returns,and Analyst Optimism

This paper investigates whether implied expected returns based on the approach of CLAUS/THOMAS (2001) can be implemented in active portfolio management. This approach uses analysts' forecasts to derive return expectations by equating the present value of expected cash-flows to the current market price. It is found that active investment strategies which maximize implied expected returns significantly outperform a passive index investment. A significant part of this outperformance can be explained by the difference between the implied expected return and the return expectation justified by the CAPM. The empirical results suggest that a substantial part of this difference can be attributed to an optimism bias in analysts' forecasts.     

Idiosyncratic risk,costly arbitrage,and the cross-section of stock returns

We test a new cross-sectional relation between expected stock return and idiosyncratic risk implied by the theory of costly arbitrage. If arbitrageurs find it more difficult to correct the mispricing of stocks with high idiosyncratic risk, there should be a positive (negative) relation between expected return and idiosyncratic risk for undervalued (overvalued) stocks. We combine several well-known anomalies to measure stock mispricing and proxy stock idiosyncratic risk using an exponential GARCH model for stock returns. We confirm that average stock returns monotonically increase (decrease) with idiosyncratic risk for undervalued (overvalued) stocks. Overall, our results support the importance of idiosyncratic risk as an arbitrage cost.     

Options Trading and the CAPM

This article studies equilibrium asset pricing when agents facenonnegative wealth constraints. In the presence of these constraintsit is shown that options on the market portfolio are nonredundantsecurities and the economy's pricing kernel is a function ofboth the market portfolio and the nonredundant options. Thisimplies that the options should be useful for explaining riskyasset returns. To test the theory, a model is derived in whichthe expected excess return on any risky asset is linearly related(via a collection of betas) to the expected excess return onthe market portfolio and to the expected excess returns on thenonredundant options. The empirical results indicate that thereturns on traded index options are relevant for explainingthe returns on risky asset portfolios.     

Asset Pricing and Expected Inflation

This paper provides an equilibrium model in which expected real returns on common stocks are negatively related to expected inflation and money growth. It is shown that the fall in real wealth associated with an increase in expected inflation decreases the real rate of interest and the expected real rate of return of the market portfolio. The expected real rate of return of the market portfolio falls less, for a given increase in expected inflation, when the increase in expected inflation is caused by an increase in money growth rather than by a worsening of the investment opportunity set. The model has empirical implications for the effect of a change in expected inflation on the cross-sectional distribution of asset returns and can help to understand why assets whose return covaries positively with expected inflation may have lower expected returns. The model also agrees with explanations advanced by Fama [5] and Geske and Roll [10] for the negative relation between stock returns and inflation.