Future Excess Returns Research Articles

Aggregate idiosyncratic volatility and stock return predictability: Evidence from the Korean stock market

ABSTRACTEmploying various proxies of idiosyncratic volatility, we investigate the relationship between aggregate idiosyncratic volatility and future market returns in Korea. We find a positive association between aggregate idiosyncratic volatility and subsequent market returns, and especially, that the idiosyncratic volatility measure proposed by Garcia, Mantilla-García, and Martellini (2014) has a striking forecasting power for future market excess returns. The predictive power of aggregate idiosyncratic volatility is robust to several considerations including weighting schemes, market variance and trading exchanges. Overall, our empirical results indicate that aggregate idiosyncratic volatility plays an important role in predicting future stock returns in the Korean stock market.

Asset Pricing with Persistence Risk

Persistence risk is an endogenous source of risk that arises when a rational agent learns about the length of business cycles. Persistence risk is positive during recessions and negative during expansions. This asymmetry, which solely results from learning about persistence, causes expected returns, return volatility, and the price of risk to rise during recessions. Persistence risk predicts future excess returns, particularly at 3- to 7-year horizons. Its predictability is strongest around business-cycle peaks and troughs. We confirm the model's predictions in the data and provide evidence that persistence risk is priced in financial markets.

Time-varying risk aversion and return predictability

The risk aversion implied in option prices contains information about the attitude of investors toward risk and therefore its variation can capture the changes in risk premiums implicit in financial markets. In this paper, we propose a new method for estimating the variations of risk aversion and examine its predictability on future excess returns. Results for the S&P 500 index show that risk aversion has predictive power for future excess returns, even for short horizons that is, two- and four-week horizons and does not lose significance in the presence of conventional forecasting variables, including dividend yield, short rate, and variance risk premium. For robustness, we conduct an additional test on Sharpe ratio prediction and these results also support the predictability of time-varying risk aversion on future Shape ratio movements.

The Information Content of the Implied Volatility Term Structure on Future Returns

We adopt the Heston (1993) stochastic volatility (SV) model framework to examine the theoretical relationship between the term structure of implied volatility and the expected excess returns of underlying assets. Three alternative approaches are adopted for our compilation of the variables representing the information on the squared VIX level and the term structure in support of our empirical investigation of the information content of the level and term structure variables on future excess returns in the S&P 500 index. Our empirical results provide support for the important role of the term structure in the determination of future excess returns, with such predictive power being discernible for various horizons. Overall, the information content of the term structure variable is found to be significant, and indeed, a strong complement to that of the level variable. In particular, due to the mean-reversion behavior of volatility, the information in the term structure of implied volatility is found to be very effective in the prediction of shorter-term excess returns.

The Household Equity Share and Expected Market Returns

The “Household Equity Share” (HEShare), the share of the household sector's equity and credit assets allocated to equities, is a negative predictor of excess returns on the US stock market. When the household sector has a higher equity share, future excess returns to equities are lower on average. This predictability is robust to the definition of the asset classes, first versus second half of sample, and adjusting for finite sample bias. HEShare outperforms many popular forecasters of market returns, including the cyclically adjusted price-earnings ratio, the equity share in new issuances, and the consumption-wealth ratio. Our results suggest that household holdings of financial assets play an important role in setting asset prices and risk premia.

Analyst Long-Term Growth Forecasts, Accounting Fundamentals and Stock Returns

We decompose consensus analyst long-term growth forecasts into a hard growth component that captures accounting information (asset and sales growth, profitability and equity dilution) and an orthogonal soft growth component. The soft component does not forecast future returns, and the hard component does forecast future returns, but in a perverse way. Specifically, stocks with accounting information indicating favorable long-term growth forecasts tend to realize negative future excess returns. This and other evidence we present is consistent with biased long-term growth forecasts generating stock mispricing.

Aggregate Distress Risk and Equity Returns

We show in two ways that, ceteris paribus, investors require a positive return premium for taking aggregate distress risk. First, aggregate distress risk correlates positively with future excess stock market returns. Second, stocks that provide a poor hedge against aggregate distress risk have high expected returns. To reconcile our results with previous evidence of a negative default probability-return relation, we find that default probabilities are an inadequate measure of exposure to systematic distress risk. Consistent with George and Hwang’s (2010) tradeoff theory of capital structure, firms that are more susceptible to aggregate distress risk have a lower level of leverage.

Systematic risk and yield premiums in the bond market

This research shows traditional measures of systematic risk of bonds have very large downward biases and develops an improved method for calculating the market betas of credit instruments. An empirical evaluation indicates that yield spreads are highly related to such estimates of systematic risk. These betas in conjunction with yields enable estimates for the market price of risk that are empirically found to be useful indicators of future excess returns on the aggregate market. The ex-ante systematic risk premiums are discovered to be negatively related to past market returns on bonds and be positively associated with past market volatility.

Predictive Ability of Three Different Estimates of “Cay” to Excess Stock Returns – A Comparative Study for South Africa and USA

The results of Lettau and Ludvigson (2001) show that Cay-LL has a significant predictive power both in the in-sample and the out-of-sample forecast of excess return. Our study departs from Lettau and Ludvigson (2001) in adding and comparing other two estimates of cay namely cay-OLS and cay-DLS besides cay-LL for forecasting excess return in both the United States and South Africa. Using quarterly data over the period 1988:1 to 2012:2, the results for the United States suggest that the three alternative measures of cay have positive significant predicting ability for the in-sample and out-of-sample forecasting models. Furthermore, and in line with the results of Lettau and Ludvigson (2001), cay-LL has the least mean squared forecasting errors. For the case of South Africa, lagged excess return and dividend yield beat the three alternative measures of cay in forecasting excess return. The results suggest that for the case of South Africa, the trend deviations of the macroeconomic variables is not a strong predictor of the excess stock returns over a treasury bill rate, and cannot account for a statistical significant variation in future excess returns.

Using Option Implied Volatilities to Predict Absolute Stock Returns - Evidence from Earnings Announcements and Annual Shareholderss Meetings

We provide evidence that an option implied volatility-based measure predicts future absolute excess returns of the underlying stock around earnings announcements and annual meetings of shareholders, even after controlling for the realized stock return volatility shortly before these information events, and the volatility of excess stock returns around these two events in the past. Our results imply that option traders anticipate the change in uncertainty around these two scheduled events, and also trade on the expected volatility. In addition, we show that net straddle returns (after transaction costs) around earnings announcements and annual meetings of shareholders are significantly and negatively related to the predicted volatility of returns around the events. This suggests that the writers of call and put options expect to be compensated for the predicted volatility. Overall, we find that option traders anticipate and correctly incorporate the volatility induced by the information released in quarterly earnings announcements, and annual meetings of shareholders.

Heterogeneous Beliefs About Rare Event Risk in the Lucas Orchard

This paper investigates the asset pricing implications of investor disagreement about the likelihood of a systematic disaster. I specify a general equilibrium model with multiple trees and heterogeneous beliefs about rare event risk, to understand how risk-sharing mechanisms affect equity and variance risk premia, at an aggregate level and in the cross-section of stock returns. I identify a state dependent link between equity and variance premia, that changes with the distribution of agent consumption. Empirically, as in the model, the variance premium’s predictive power for future excess returns is greater during times of financial distress, mainly for small stocks.

Risk and Return Trade-Off in the U.S. Treasury Market

This paper characterizes the risk-return trade-off in the U.S. Treasury market. We propose a discrete-time no-arbitrage term structure model, in which bond prices are solved in closed form and the conditional variances of bond yields are decomposed into a short-run component and a long-run component, each of which follows a GARCH-type process. Estimated using Treasury yields data from January 1962 to August 2007, our model simultaneously matches the conditional volatility dynamics and the deviation from the expectations hypothesis in the data. We find that a higher short-run volatility component of bond yields significantly predicts a higher future excess return, above and beyond the predictive power of the yields. The long-run volatility component does not predict bond excess returns.

A New Test for the Detection of the Pricing Role of Aggregate Idiosyncratic Risk in the Predictive Regression

The standard test for the pricing role of aggregate idiosyncratic risk in the conventional predictive regression considers aggregate total idiosyncratic risk a reasonable proxy for its undiversified component, which should be priced as theory suggests. However, when the priced component is relatively small, the test has little statistical power to reject the null hypothesis that idiosyncratic risk does not matter, even when the priced component, albeit small, explains an economically large portion of future excess return variation. We propose a simple regression-based method that can, under certain conditions, substantially improve the power of the test when economically important alternative hypotheses are true, but sacrifices little in the size of the test for the improved power. Based on the new test, we strongly reject the proposition that idiosyncratic risk does not matter and uncover a significantly positive relationship between aggregate undiversified idiosyncratic risk and future market excess returns.

Mispricing and risk of R&D investment in European firms

We study whether R&D-intensive firms earn superior stock returns compared to matched size and book-to-market portfolios across several financial markets in Europe. Mispricing can arise if investors are not able to correctly estimate the long-term benefits of R&D investment or whether R&D firms are more risky than others. The results confirm that more innovative firms can earn future excess returns. Stocks listed on continental Europe markets and operating in high-tech sectors are more prone to undervaluation. This can be caused in the first case by information asymmetries that are more severe in bank-based countries. No evidence is found for a different risk pattern of R&D-intensive stocks.

The reaction of international stock markets to Federal Reserve policy

This paper investigates how changes in Federal Reserve policy impact international stock returns, with the three objectives of measuring the reaction of international stock markets, understanding the transmission channels of that reaction, and explaining the economic sources of that reaction. We find that unanticipated Federal Reserve policy actions exert a significant and robust influence on international stock prices. However, the influence of unanticipated monetary policy actions is not strong enough to change the correlation structure of international equity returns. We also find that international stock return co-movements play an important role in the transmission of monetary policy. Finally, the variance decomposition analysis indicates that the effects of monetary policy surprises on future excess returns or dividend returns account for the largest portion of the equity price response.

Do Analysts Underestimate Future Benefits of R&D?

This paper investigates whether future excess returns to R&D-intensive firms documented in prior literature is due to mispricing or compensation for additional risk. Prior research provides evidence consistent with the explanation that the positive association is compensation for additional risk associated with R&D (Chambers et al. 2002). I investigate another possibility: The future excess returns to R&D are correction for undervaluation in the prior periods. I first investigate financial analysts’ behavior about future benefits of R&D-intensive firms because financial analysts are one of the most important information intermediaries between investors and managers. Moreover, investor dependence on analyst information is greater in R&D-intensive firms (Barth et al., 2001). I find that analysts underestimate earnings long term growth in R&D-intensive firms and correct their underestimation in following years. I also find that investors are not aware of analysts’ underestimation of future benefits of R&D suggesting that investors are mislead by analysts long term forecasts.

The relationship between earnings transparency and future excess return in business environment

In this research, we try to emphasize voluntary disclosure as an important mechanism for the corporate governance process, and the financial reporting system to reduce the costs linked to the information asymmetries. Researchers have long been interested in the anticipation of future returns, which is important in obtaining excess return (the difference between actual and expected returns). According to the previous conceptual studies, increasing in more transparency in reported earnings can reduce information asymmetry and hence, decrease excess return. This study examines the relationship between earnings transparency and future excess return. Using more than 90 firms listed in the Tehran stock exchange from 2005 over 2009 are selected; the evidences of present research supported that there is no significant relationship between earnings transparency and future excess returns. Key words: Earnings transparency, expected returns, future excess returns, disclosure, business environment.

Innovative Capacity and the Asset Growth Anomaly

Innovative capacity (IC) is a firm’s ability to produce and commercialize multiple innovations. Expected returns need not fall following asset growth (AG) by high IC firms because investment can generate new growth options. Using patents-based measures for IC, we find that the well-known negative relation between AG and subsequent excess returns (the “asset growth anomaly”) holds only for low IC firms. However, there is no such anomaly for high IC firms and AG is significantly positively related to future excess returns. Moreover, changes in market risk following asset growth are positively related to IC. Therefore, IC plays an important role in the dynamics between AG and returns, and in driving the time-varying market risk of firms.

Out-of-sample stock return predictability in Australia

We provide one of the first comprehensive studies on out-of-sample stock returns predictability in Australia. While most of the empirically well-known predictive variables fail to generate out-of-sample predictability, we document a significant out-of-sample prediction in forecasting ahead one-year and, to a lesser extent, one-quarter future excess returns, using a combination forecast of variables. We also find improved asset allocation using the combination forecast of these predictors. The combining methods are useful in predicting sector premia. Specifically, a sector rotation strategy relying on the combining methods outperforms the market by 3.27% per annum on a risk-adjusted basis.

Segregating Continuous Volatility from Jumps in Long-Run Risk-Return Trade-Offs

We provide a multi-horizon characterization of the strength of the relationship between market realized variance components, namely continuous volatility and jump, and future market excess return. Building on quadratic variation theory, we find that continuous volatility is a key driver of medium/long-run risk-return trade-offs while jumps lack predictive power to explaining the time variation in medium/long-term excess return. We use inference methods that are robust to persistent predictor in a multi-horizon setup. Specifically, we show that rescaled versions of the usual test statistics converge to non-degenerate distributions in our local-to-unity framework. This study yields evidence supporting a proportional risk-return linkage when jumps are extracted from the quadratic variation activity.