The Danish stock and bond markets: comovement,return predictability and variance decomposition

VAR models of the kind developed by Shiller and Beltratti [J. Monetary Econ. 30 (1992) 25] and Campbell and Ammer [J. Finance 48 (1993) 3] are used to analyze the Danish stock and bond markets and their comovement. In contrast to these papers, however, VAR parameter estimates are bias-adjusted and VAR generated statistics, including their standard errors and confidence intervals, are computed using bootstrap simulation. In addition, we modify the Campbell–Ammer variance decomposition such that it can handle returns from a long-term coupon bond. Some parts of the results for the Danish stock and bond markets are quite similar to the US results reported by Shiller and Beltratti and Campbell and Ammer, but other parts stand in sharp contrast to the results for the US. The most important differences between the US and Denmark are that in Denmark news about higher future inflation lead to an increase in expected future stock returns, and that excess stock return news and excess bond return news are negatively correlated.     

The Comovement of US and UK Stock Markets

US and UK stock returns are highly positively correlated over the period 1918–99. Using VAR‐based variance decompositions, we investigate the nature of this comovement. Excess return innovations are decomposed into news about future dividends, real interest rates, and excess returns. We find that the latter news component is the most important in explaining stock return volatility in both the USA and the UK and that stock return news is highly correlated across countries. This is evidence against Beltratti and Shiller's (1993) finding that the comovement of US and UK stock markets can be explained in terms of a simple present value model. We interpret the comovement as indicating that equity premia in the two countries are hit by common real shocks.     

UK Stock Returns and the Impact of Domestic Monetary Policy Shocks

Abstract:  We investigate the influence of changes in UK monetary policy on UK stock returns and the possible reasons behind such a response. Firstly, we conduct an event study to assess the impact of unexpected changes in monetary policy on aggregate and sectoral stock returns. The decomposition of unexpected changes in the policy rate is based on futures markets data. Secondly, using a variance decomposition in the spirit of Campbell (1991) we attempt to identity the channels behind the response of stock returns to monetary policy surprises. The variance decomposition results indicate that the monetary policy shock leads to a persistent negative response in terms of future excess returns for a number of sectors.     

Bayesian Alphas and Mutual Fund Persistence

We use daily returns to compare the performance predictability of Bayesian estimates of mutual fund performance with standard frequentist measures. When the returns on passive nonbenchmark assets are correlated with fund holdings, incorporating histories of these returns produces a performance measure that predicts future performance better than standard measures do. Bayesian alphas based on the Capital Asset Pricing Model (CAPM) are particularly useful for predicting future standard CAPM alphas. Over our sample period, priors consistent with moderate to diffuse beliefs in managerial skill dominate more skeptical prior beliefs, a result that is consistent with investor cash flows.     

Do Decomposed Financial Ratios Predict Stock Returns and Fundamentals Better?

We investigate the prediction of excess returns and fundamentals by financial ratios, which include dividend‐price ratios, earnings‐price ratios, and book‐to‐market ratios, by decomposing financial ratios into a cyclical component and a stochastic trend component. We find both components predict excess returns and fundamentals. Cyclical components predict increases in future stock returns, while stochastic trend components predict declines in future stock returns in long horizons. This helps explain previous findings that financial ratios in the absence of decomposition find weak predictive power in short horizons and some predictive power in long horizons. We also find both components predict fundamentals.     

Macro variables and the components of stock returns

We conduct a decomposition for the stock market return by incorporating the information from 124 macro variables. Using factor analysis, we estimate six common factors and run a VAR containing these factors and financial variables such as the market dividend yield and the T-bill rate. Including the macro factors does not have a significant impact in the estimation of the components of aggregate (excess) stock returns—cash-flow, discount-rate, and interest-rate news. Using the macro factors in the computation of cash-flow and discount-rate news does not significantly improve the fit of a two-factor ICAPM for the cross-section of stock returns.     

The Risk‐Return Relation in International Stock Markets

We investigate the risk‐return relation in international stock markets using realized variance constructed from MSCI (Morgan Stanley Capital International) daily stock price indices. In contrast with the capital asset pricing model, realized variance by itself provides negligible information about future excess stock market returns; however, we uncover a positive and significant risk‐return tradeoff in many countries after controlling for the (U.S.) consumption‐wealth ratio. U.S. realized variance is also significantly related to future international stock market returns; more importantly, it always subsumes the information content of its local counterparts. Our results indicate that stock market variance is an important determinant of the equity premium.     

Permanent and transitory components of GDP and stock prices: further analysis

Using the conventional VAR identification approach, Cochrane (Quarterly Journal of Economics 107: 241–65, 1994) finds that substantial amounts of variation in GDP growth and stock returns are due to transitory shocks. Following the common trend decomposition of King etal. (American Economic Review 81: 819–40, 1991), we show that Cochrane's results depend on the assumption of weak exogeneity of one of the variables with respect to the cointegration vector. When this assumption holds both approaches coincide. If not, the shocks Cochrane called transitory are not totally transitory. In this case, the conventional VAR approach with the assumption of the weak exogeneity may overstate the magnitude of transitory shocks and understate that of permanent shocks. We find that the permanent components of GDP and stock prices are much larger than those estimates of Cochrane, although substantial (but much smaller than in Cochrane 1994) variations in GDP growth and stock returns are attributed to transitory shocks.     

Stock Market Returns and Economic Fundamentals in an Emerging Market: The Case of Korea

This paper investigates the feedback relationship between stock market returnsand economic fundamentals in an emerging market. Starting from an intertemporalconsumption-based CAPM (CCAPM), we obtain a restricted VAR model for stockreturns and macroeconomic variables. We then apply this model to Korea and findstatistically significant departures from the restrictions implied by CCAPM.Consequently, an unrestricted VAR model is used to analyze the variations of expectedand unexpected returns in the Korean stock market. It is shown that the expectedmarket returns vary with a set of macroeconomic variables, and that thepredictable component is substantial. Reflecting richer dynamics in the data,relative to the usual single equation modeling in the literature, the estimatedVAR model shows considerable predictive ability for both real economic activityand real returns. Using the model for a variance decomposition of unexpectedreturns, we find that, although we cannot directly observe the market's revisionof expected future dividend growth, we can estimate a large part of therevision with the news in the expected industry output growth from our VAR model.Finally, we also find that economic fundamentals can explain only a smallportion of the variation in unexpected returns in the Korean stock market.     

Average correlation and stock market returns

If the Roll critique is important, changes in the variance of the stock market may be only weakly related to changes in aggregate risk and subsequent stock market excess returns. However, since individual stock returns share a common sensitivity to true market return shocks, higher aggregate risk can be revealed by higher correlation between stocks. In addition, a change in stock market variance that leaves aggregate risk unchanged can have a zero or even negative effect on the stock market risk premium. We show that the average correlation between daily stock returns predicts subsequent quarterly stock market excess returns. We also show that changes in stock market risk holding average correlation constant can be interpreted as changes in the average variance of individual stocks. Such changes have a negative relation with future stock market excess returns.     

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.     

Market Timing And Model Uncertainty: An Exploratory Study For The Swiss Stock Market

We use statistical model selection criteria and Avramov's (2002) Bayesian model averaging approach to analyze the sample evidence of stock market predictability in the presence of model uncertainty. The empirical analysis for the Swiss stock market is based on a number of predictive variables found important in previous studies of return predictability. We find that it is difficult to discard any predictive variable as completely worthless, but that the posterior probabilities of the individual forecasting models as well as the cumulative posterior probabilities of the predictive variables are time-varying. Moreover, the estimates of the posterior probabilities are not robust to whether the predictive variables are stochastically detrended or not. The decomposition of the variance of predicted future returns into the components parameter uncertainty, model uncertainty, and the uncertainty attributed to forecast errors indicates that the respective contributions strongly depend on the time period under consideration and the initial values of the predictive variables. In contrast to AVRAMOV (2002), model uncertainty is generally not more important than parameter uncertainty. Finally, we demonstrate the implications of model uncertainty for market timing strategies. In general, our results do not indicate any reliable out-of-sample return predictability. Among the predictive variables, the dividend-price ratio exhibits the worst external validation on average. Again in contrast to AVRAMOV (2002), our analysis suggests that the out-of-sample performance of the Bayesian model averaging approach is not superior to the statistical model selection criteria. Consequently, model averaging does not seem to help improve the performance of the resulting short-term market timing strategies.     

Stock Return Predictability and The Role of Monetary Policy

This article examines whether shifts in the stance of monetary policy can account for the observed predictability in excess stock returns. Using long-horizon regressions and short-horizon vector autoregressions, the article concludes that monetary policy variables are significant predictors of future returns, although they cannot fully account for observed stock return predictability. I undertake variance decompositions to investigate how monetary policy affects the individual components of excess returns (risk-free discount rates, risk premia, or cash flows).     

Consumption, Aggregate Wealth, and Expected Stock Returns

This paper studies the role of fluctuations in the aggregate consumption–wealth ratio for predicting stock returns. Using U.S. quarterly stock market data, we find that these fluctuations in the consumption–wealth ratio are strong predictors of both real stock returns and excess returns over a Treasury bill rate. We also find that this variable is a better forecaster of future returns at short and intermediate horizons than is the dividend yield, the dividend payout ratio, and several other popular forecasting variables. Why should the consumption–wealth ratio forecast asset returns? We show that a wide class of optimal models of consumer behavior imply that the log consumption–aggregate wealth (human capital plus asset holdings) ratio summarizes expected returns on aggregate wealth, or the market portfolio. Although this ratio is not observable, we provide assumptions under which its important predictive components for future asset returns may be expressed in terms of observable variables, namely in terms of consumption, asset holdings and labor income. The framework implies that these variables are cointegrated, and that deviations from this shared trend summarize agents' expectations of future returns on the market portfolio.     

Asymmetric mean-reversion and contrarian profits: ANST-GARCH approach

This paper investigates the time-series evidence of asymmetric reverting patterns in stock returns that is attributable to “contrarian profitability.” Using asymmetric nonlinear smooth-transition (ANST) GARCH(M) models, we find that, for monthly excess returns of US market indexes over the period of 1926:01–1997:12, negative returns on average reverted more quickly, with a greater reverting magnitude, to positive returns than positive returns revert to negative returns. The results are quite consistent when the models are implemented not only for the different sample periods, such as 1926:01–1987:09 and 1947:01–1997:12, but also for portfolios with different characteristics, such as different firm-size portfolios and Fama–French risk-adjusted factor portfolios. We interpret the asymmetrical reversion as evidence of stock market overreaction.     

Time-varying risk premia and the cost of capital: An alternative implication of the Q theory of investment

Evidence suggests that expected excess stock market returns vary over time, and that this variation is much larger than that of expected real interest rates. It follows that a large fraction of the movement in the cost of capital in standard investment models must be attributable to movements in equity risk-premia. In this paper we emphasize that such movements in equity risk premia should have implications not merely for investment today, but also for future investment over long horizons. In this case, predictive variables for excess stock returns over long-horizons are also likely to forecast long-horizon fluctuations in the growth of marginal Q, and therefore investment. We test this implication directly by performing long-horizon forecasting regressions of aggregate investment growth using a variety of predictive variables shown elsewhere to have forecasting power for excess stock market returns.     

Leverage, excess leverage, and future returns

We examine the cross-sectional relation between leverage and future returns while considering the dynamic nature of capital structure and potentially delayed market reactions. Prior studies find a negative relation between leverage and future returns that contradicts standard finance theory. We decompose leverage into optimal and excess components and find that excess leverage tends to drive this negative relation. We also find that excess leverage predicts firm fundamentals and that the negative relation between excess leverage and future returns may be explained by investors’ failure to react promptly to information contained in excess leverage about future financial distress and asset growth.     

Portfolio selection with two-stage preferences

We propose a model of portfolio selection under ambiguity, based on a two-stage valuation procedure which disentangles ambiguity and ambiguity aversion. The model does not imply “extreme pessimism” from the part of the investor, as multiple priors models do. Furthermore, its analytical tractability allows to study complex problems thus far not analyzed, such as joint uncertainty about means and variances of returns.     

Corporate Disclosure Policy and the Informativeness of Stock Prices

We examine the association between voluntary corporate disclosure and the informativeness of stock prices. We measure corporate disclosure using the AIMR-FAF annual corporate disclosure ratings. We define price informativeness by the association between current stock returns and future earnings changes: more informative stock price changes contain more information about future earnings changes. To measure this association, we regress current returns against (current and) future earnings changes. The aggregated coefficient on the future earnings changes, which we refer to as the future ERC, is our measure of informativeness (association).We hypothesize and find that greater disclosure is associated with stock prices that are more informative about future earnings (i.e., higher future ERC). These results provide empirical support for the widely held, but heretofore empirically undocumented, belief that greater disclosure provides information benefits to investors.     

What Drives Firm‐Level Stock Returns?

I use a vector autoregressive model (VAR) to decompose an individual firm's stock return into two components: changes in cash-flow expectations (i.e., cash-flow news) and changes in discount rates (i.e., expected-return news). The VAR yields three main results. First, firm-level stock returns are mainly driven by cash-flow news. For a typical stock, the variance of cash-flow news is more than twice that of expected-return news. Second, shocks to expected returns and cash flows are positively correlated for a typical small stock. Third, expected-return-news series are highly correlated across firms, while cash-flow news can largely be diversified away in aggregate portfolios.