Boomer retirement: headwinds for U.S. equity markets?
Historical data indicate a strong relationship between the age distribution of the U.S. population and stock market performance. A key demographic trend is the aging of the baby boom generation. As they reach retirement age, they are likely to shift from buying stocks to selling their equity holdings to finance retirement. Statistical models suggest that this shift could be a factor holding down equity valuations over the next two decades.
AUTHORS: Liu, Zheng; Spiegel, Mark M.
The impact of creditor protection on stock prices in the presence of credit crunches
Data show that better creditor protection is correlated across countries with lower average stock market volatility. Moreover, countries with better creditor protection seem to have suffered lower decline in their stock market indexes during the current financial crisis. To explain this regularity, we use a Tobin q model of investment and show that stronger creditor protection increases the expected level and lowers the variance of stock prices in the presence of credit crunches. There are two main channels through which creditor protection enhances the performance of the stock market: (1) The credit-constrained stock price increases with better protection of creditors; (2) The probability of a credit crunch leading to a binding credit constraint falls with strong protection of creditors. We find strong empirical support for both predictions using data on stock market performance, amount and cost of credit, and creditor rights protection for 52 countries over the period 1980-2007. In particular, we find that crises are more frequent in countries with poor creditor protection. Using propensity score matching we also show that during crises stock market returns fall by more in countries with poor creditor protection.
AUTHORS: Razin, Assaf; Tong, Hui; Hale, Galina
The information content of high-frequency data for estimating equity return models and forecasting risk
We demonstrate that the parameters controlling skewness and kurtosis in popular equity return models estimated at daily frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information content of realized volatility measures extracted from high-frequency data. For this purpose, we introduce asymptotically exact volatility measurement equations in state space form and propose a Bayesian estimation approach. Our highly efficient estimates lead in turn to substantial gains for forecasting various risk measures at horizons ranging from a few days to a few months ahead when taking also into account parameter uncertainty. As a practical rule of thumb, we find that two years of high frequency data often suffice to obtain the same level of precision as twenty years of daily data, thereby making our approach particularly useful in finance applications where only short data samples are available or economically meaningful to use. Moreover, we find that compared to model inference without high-frequency data, our approach largely eliminates underestimation of risk during bad times or overestimation of risk during good times. We assess the attainable improvements in VaR forecast accuracy on simulated data and provide an empirical illustration on stock returns during the financial crisis of 2007-2008.
AUTHORS: Dobrev, Dobrislav; Szerszen, Pawel J.
An empirical investigation of consumption-based asset pricing models with stochastic habit formation
We econometrically estimate a consumption-based asset pricing model with stochastic internal habit and test it using the generalized method of moments. The model departs from existing models with deterministic internal habit (e.g., Dunn and Singleton (1983), Ferson and Constan- tinides (1991), and Heaton (1995)) by introducing shocks to the coefficients in the distributed lag specification of consumption habit and consequently an additional shock to the marginal rate of substitution. The stochastic shocks to the consumption habit are persistent and provide an additional source of time variation in expected returns. Using Treasury bond returns and broad equity market index returns, we show that stochastic internal habit formation models resolve the dichotomy between the autocorrelation properties of the stochastic discount factor and those of expected returns. Consequently, they provide a better explanation of time-variation in expected returns than models with either deterministic habit or stochastic external habit.
AUTHORS: Dai, Qiang; Grishchenko, Olesya V.
Stock return predictability and variance risk premia: statistical inference and international evidence
Recent empirical evidence suggests that the variance risk premium, or the difference between risk-neutral and statistical expectations of the future return variation, predicts aggregate stock market returns, with the predictability especially strong at the 2-4 month horizons. We provide extensive Monte Carlo simulation evidence that statistical finite sample biases in the overlapping return regressions underlying these findings can not ``explain" this apparent predictability. Further corroborating the existing empirical evidence, we show that the patterns in the predictability across different return horizons estimated from country specific regressions for France, Germany, Japan, Switzerland and the U.K. are remarkably similar to the pattern previously documented for the U.S. Defining a "global" variance risk premium, we uncover even stronger predictability and almost identical cross-country patterns through the use of panel regressions that effectively restrict the compensation for world-wide variance risk to be the same across countries. Our findings are broadly consistent with the implications from a stylized two-country general equilibrium model explicitly incorporating the effects of world-wide time-varying economic uncertainty.
AUTHORS: Bollerslev, Tim; Marrone, James; Zhou, Hao; Xu, Lai
External habit and the cyclicality of expected stock returns
We estimate an equilibrium asset pricing model in which agents' preferences have an unobserved external habit using the efficient method of moments (EMM). Given the estimated structural parameters we examine the cyclical behavior of expected stock returns in the model. We find that the estimated structural parameters imply countercyclical expected stock returns as documented in existing empirical studies. The model, however, is still rejected at the one percent level. Detailed examination of the moment conditions in our estimation indicates that the model performs reasonably well in matching the mean of returns, but it fails to capture the higher order moments.
AUTHORS: Tallarini, Thomas D.; Zhang, Harold H.
The high-frequency impact of news on long-term yields and forward rates: Is it real?
This paper uses high-frequency intradaily data to estimate the effects of macroeconomic news announcements on yields and forward rates on nominal and index-linked bonds, and on inflation compensation. To our knowledge, it is the first study in the macro announcements literature to use intradaily real yield data, which allow us to parse the effects of news announcements on real rates and inflation compensation far more precisely than we can using daily data. Long-term nominal yields and forward rates are very sensitive to macroeconomic news announcements. We find that inflation compensation is sensitive to announcements about price indices and monetary policy. However, for news announcements about real economic activity, such as nonfarm payrolls, the vast majority of the sensitivity is concentrated in real rates. Accordingly, we conclude that most of the sizeable impact of news about real economic activity on the nominal term structure of interest rates represents changes in expected future real short-term interest rates and/or real risk premia rather than changes in expected future inflation and/or inflation risk premia. This suggests that explanations for the puzzling sensitivity of long-term nominal rates need to look beyond just inflation expectations and toward models that encompass uncertainty about the long-run real rate of interest.
AUTHORS: Beechey, Meredith J.; Wright, Jonathan H.
Limited market participation and asset prices in the presence of earnings management
We examine the role of earnings management in explaining the properties of asset prices and stock market participation. We demonstrate that investors' uncertainty about the extent of manipulation can cause excess movements in stock price relative to fluctuations in output. When faced with information asymmetry about fundamentals in the presence of earnings management, investors demand a higher equity premium for bearing the additional risk associated with their payoffs. In addition, when investors have heterogeneous beliefs about managerial manipulation, the dispersion in belief endogenously gives rise to limited stock market participation. Our model suggests that the increasing stringency of corporate governance and varying composition of investors may have played a role in the contemporaneous run-up of market participation rates in the recent years.
AUTHORS: Sun, Bo
Jackknifing stock return predictions
We show that the general bias reducing technique of jackknifing can be successfully applied to stock return predictability regressions. Compared to standard OLS estimation, the jackknifing procedure delivers virtually unbiased estimates with mean squared errors that generally dominate those of the OLS estimates. The jackknifing method is very general, as well as simple to implement, and can be applied to models with multiple predictors and overlapping observations. Unlike most previous work on inference in predictive regressions, no specific assumptions regarding the data generating process for the predictors are required. A set of Monte Carlo experiments show that the method works well in finite samples and the empirical section finds that out-of-sample forecasts based on the jackknifed estimates tend to outperform those based on the plain OLS estimates. The improved forecast ability also translates into economically relevant welfare gains for an investor who uses the predictive regression, with jackknifed estimates, to time the market.
AUTHORS: Chiquoine, Benjamin; Hjalmarsson, Erik
Predicting global stock returns
I test for stock return predictability in the largest and most comprehensive data set analyzed so far, using four common forecasting variables: the dividend- and earnings-price ratios, the short interest rate, and the term spread. The data contain over 20,000 monthly observations from 40 international markets, including 24 developed and 16 emerging economies. In addition, I develop new methods for predictive regressions with panel data. Inference based on the standard fixed effects estimator is shown to suffer from severe size distortions in the typical stock return regression, and an alternative robust estimator is proposed. The empirical results indicate that the short interest rate and the term spread are fairly robust predictors of stock returns in developed markets. In contrast, no strong or consistent evidence of predictability is found when considering the earnings- and dividend-price ratios as predictors.
AUTHORS: Hjalmarsson, Erik