Efficient tests of stock return predictability

Conventional tests of the predictability of stock returns could be invalid, that is reject the null too frequently, when the predictor variable is persistent and its innovations are highly correlated with returns. We develop a pretest to determine whether the conventional t-test leads to invalid inference and an efficient test of predictability that corrects this problem. Although the conventional t-test is invalid for the dividend–price and smoothed earnings–price ratios, our test finds evidence for predictability. We also find evidence for predictability with the short rate and the long-short yield spread, for which the conventional t-test leads to valid inference.     

Time varying stock return predictability: Evidence from US sectors

This paper argues that dividend yield stock return predictability is time-varying. We conjecture that such time-variation is linked to the business cycle. Employing monthly data for US sector portfolios we estimate 5-year rolling fixed window predictive regressions. The resulting series of time-varying predictive coefficients is regressed on industrial production growth and a recession dummy. Our results support the view of a negative relationship between predictability and output growth. That is the strength of the predictive relationship between returns and the dividend yield is stronger during contractionary periods, while during expansions the magnitude of the relationship declines.     

Credit conditions and stock return predictability

U.S. stock return predictability is analyzed using a measure of credit standards (Standards) derived from the Federal Reserve Board׳s Senior Loan Officer Opinion Survey on Bank Lending Practices. Standards is a strong predictor of stock returns at a business cycle frequency, especially in the post-1990 data period. Empirically, a tightening of Standards predicts lower future stock returns. Standards performs well both in-sample and out-of-sample and is robust to a host of consistency checks. Standards captures stock return predictability at a business cycle frequency and is driven primarily by the ability of Standards to predict cash flow news.     

Disagreement and return predictability of stock portfolios

This paper provides evidence that portfolio disagreement measured bottom-up from individual-stock analyst forecast dispersions has a number of asset pricing implications. For the market portfolio, market disagreement mean-reverts and is negatively related to ex post expected market return. Contemporaneously, an increase in market disagreement manifests as a drop in discount rate. For book-to-market sorted portfolios, the value premium is stronger among high disagreement stocks. The underperformance by high disagreement stocks is stronger among growth stocks. Growth stocks are more sensitive to variations in disagreement relative to value stocks. These findings are consistent with asset pricing theory incorporating belief dispersion.     

Credible reforms and stock return volatility: Evidence from privatization

In this paper we investigate how privatization affects stock return volatility. A credible privatization builds investors’ confidence through a reduction in political risk. In particular, a privatization program that is maintained over time signals credibility, which reduces political risk and in turn volatility. We further show that privatization is associated with lower idiosyncratic volatility mainly among developed markets, while it is associated with lower systematic volatility in developing markets. Additional tests suggest that the reduction in volatility is greater when privatization sales are carried out through the stock market than through asset sales.     

Real-time macroeconomic data and ex ante stock return predictability

We report results on the ex ante predictability of monthly excess stock returns in Germany using real-time and revised macroeconomic data. Our real-time macroeconomic data cover the period 1994-2005. We report that the contribution of real-time macroeconomic data to ex ante stock return predictability is similar to that of revised macroeconomic data. Moreover, the performance of an investor who had to rely on noisy real-time macroeconomic data would have been similar to the performance of an investor who had access to revised macroeconomic data.     

Investor attention,psychological anchors,and stock return predictability

Motivated by psychological evidence on limited investor attention and anchoring, we propose two proxies for the degree to which traders under- and overreact to news, namely, the nearness to the Dow 52-week high and the nearness to the Dow historical high, respectively. We find that nearness to the 52-week high positively predicts future aggregate market returns, while nearness to the historical high negatively predicts future market returns. We further show that our proxies contain information about future market returns that is not captured by traditional macroeconomic variables and that our results are robust across G7 countries. Comprehensive Monte Carlo simulations and comparisons with the NYSE/Amex market cap index confirm the significance of these findings.     

The skewness risk premium in equilibrium and stock return predictability

In this study, we investigate the skewness risk premium in the financial market under a general equilibrium setting. Extending the long-run risks (LRR) model proposed by Bansal and Yaron (J Financ 59:1481–1509, 2004) by introducing a stochastic jump intensity for jumps in the LRR factor and the variance of consumption growth rate, we provide an explicit representation for the skewness risk premium, as well as the volatility risk premium, in equilibrium. On the basis of the representation for the skewness risk premium, we propose a possible reason for the empirical facts of time-varying and negative risk-neutral skewness. Moreover, we also provide an equity risk premium representation of a linear factor pricing model with the variance and skewness risk premiums. The empirical results imply that the skewness risk premium, as well as the variance risk premium, has superior predictive power for future aggregate stock market index returns, which are consistent with the theoretical implication derived by our model. Compared with the variance risk premium, the results show that the skewness risk premium plays an independent and essential role for predicting the market index returns.     

Habit formation,surplus consumption and return predictability: International evidence

On an international post World War II dataset, we use an iterated GMM procedure to estimate and test the Campbell and Cochrane (1999, By force of habit: a consumption-based explanation of aggregate stock market behavior. Journal of Political Economy 107, 205–251.) habit formation model with a time-varying risk-free rate. In addition, we analyze the predictive power of the surplus consumption ratio for future stock and bond returns. We find that, although there are important cross-country differences and economically significant pricing errors, for the majority of countries in our sample the model gets empirical support in a variety of different dimensions, including reasonable estimates of risk-free rates. Further, for the majority of countries the surplus consumption ratio captures time-variation in expected returns. Together with the price-dividend ratio, the surplus consumption ratio contains significant information about future stock returns, also during the 1990s. In addition, in most countries the surplus consumption ratio is also a powerful predictor of future bond returns. Thus, the surplus consumption ratio captures time-varying expected returns in both stock and bond markets.     

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.     

Exchange-rate return predictability and the adaptive markets hypothesis: Evidence from major foreign exchange rates

This study examines return predictability of major foreign exchange rates by testing for martingale difference hypothesis (MDH) using daily and weekly nominal exchange rates from 1975 to 2009. We use three alternative tests for the MDH, which include the wild bootstrap automatic variance ratio test, generalized spectral test, and Dominguez–Lobato consistent tests. We evaluate time-varying return predictability by applying these tests with fixed-length moving sub-sample windows. While exchange rate returns are found to be unpredictable most of times, we do observe a number of episodes of statistically significant return predictability. They are mostly associated with the major events such as coordinated central bank interventions and financial crises. This finding suggests that return predictability of foreign exchange rates occurs from time to time depending on changing market conditions, consistent with the implications of the adaptive markets hypothesis.     

Out‐of‐sample stock return predictability in emerging markets

This article builds on the widely debated issue of stock return predictability by applying a broad range of predictor variables and comprehensively considering the in‐sample and out‐of‐sample stock return predictability of ten advanced emerging markets. It compares forecasts from models with a single predictor variable, multiple predictor variables and a combination forecast approach. The results confirm the findings of Welch and Goyal (2008) for US data that only a limited number of individual predictor variables are able to deliver significant out‐of‐sample forecasts. However, a combination forecast approach provides statistically and economically significant out‐of‐sample forecast results.     

Stock return predictability and the adaptive markets hypothesis: Evidence from century-long U.S. data

This paper provides strong evidence of time-varying return predictability of the Dow Jones Industrial Average index from 1900 to 2009. Return predictability is found to be driven by changing market conditions, consistent with the implication of the adaptive markets hypothesis. During market crashes, no statistically significant return predictability is observed, but return predictability is associated with a high degree of uncertainty. In times of economic or political crises, stock returns have been highly predictable with a moderate degree of uncertainty in predictability. We find that return predictability has been smaller during economic bubbles than in normal times. We also find evidence that return predictability is associated with stock market volatility and economic fundamentals.     

Price informativeness and stock return synchronicity: Evidence from the pricing of seasoned equity offerings

We investigate what stock return synchronicity reflects in terms of price informativeness by examining its effect on the pricing of seasoned equity offerings (SEOs). Based on 5,087 SEOs from 1984 to 2007, we find a significantly negative relation between stock return synchronicity (estimated as the logit transformation of the R-squared statistic from a two-factor regression) and SEO discounts (the percentage differences between pre-offer day closing prices and offer prices). The negative relation is strongest when there is no analyst coverage, and it declines as analyst coverage increases. This shows that stock price is more informative when stock return synchronicity is higher and also that information asymmetry can be mitigated by analyst coverage. We further decompose stock return synchronicity into the market comovement and industry comovement components and find that both components are equally important in affecting SEO discounts.     

Risk,return, and liquidity during Ramadan: Evidence from Indonesian and Malaysian stock markets

Indonesia and Malaysia are common in religion; however, the two countries have different developments in their equity markets. This study investigates the risk, return, and liquidity during Ramadan for the Indonesia and Malaysia stock markets. We find that the volatility is higher around Ramadan for the Indonesia stock market, while displays dynamic patterns in different phases around the month of Ramadan for Malaysia. Despite the changing risk during Ramadan, the risk-adjusted return remains unchanged. Furthermore, this study finds that the liquidity in most stock index markets of the two countries is higher around Ramadan. These findings support the notion that Ramadan affects investors’ risk-taking attitude and facilitates the trade in stocks.     

Risk and return: Long-run relations,fractional cointegration,and return predictability

Univariate dependencies in market volatility, both objective and risk neutral, are best described by long-memory fractionally integrated processes. Meanwhile, the ex post difference, or the variance swap payoff reflecting the reward for bearing volatility risk, displays far less persistent dynamics. Using intraday data for the Standard & Poor's 500 and the volatility index (VIX), coupled with frequency domain methods, we separate the series into various components. We find that the coherence between volatility and the volatility-risk reward is the strongest at long-run frequencies. Our results are consistent with generalized long-run risk models and help explain why classical efforts of establishing a naïve return-volatility relation fail. We also estimate a fractionally cointegrated vector autoregression (CFVAR). The model-implied long-run equilibrium relation between the two variance variables results in nontrivial return predictability over interdaily and monthly horizons, supporting the idea that the cointegrating relation between the two variance measures proxies for the economic uncertainty rewarded by the market.     

The high-volume return premium: evidence from the Chinese stock market

Extreme trading activity contains valuable information about the future evolution of stock prices in the Chinese stock market. Over the next 30 trading days after the initial volume shocks, a high-low volume portfolio earns a net average cumulate return of 2.08% and a high-low volume and size portfolio earns 3.37%, suggesting that there exists a high-volume return premium and that Chinese investors favor high-volume small-size stocks. However, a volume momentum portfolio earns a −1.65% net average cumulative return, indicating that Chinese stocks exhibit a short-run reversal. Portfolio construction, market risk, and firm size do not seem to explain the results.     

Are international stock returns predictable?: An examination of linear and non-linear predictability using generalized spectral tests

This paper uses generalized spectral tests to examine whether international stock index returns are predictable using the history of the series. Unlike many other testing procedures, the generalized spectral tests used in this paper are robust to distributional assumptions, the presence of time-varying volatility, and allow for various forms of non-linear predictability. We find evidence of predictability in mean for over half of the international returns examined. In addition, we find most of the predictability to be non-linear in nature. The patterns of predictability are consistent with calendar effects and in some cases long-run dependence. Regardless of the implications of predictability of returns, this study is important because the generalized spectrum is defined for a range of different frequencies (corresponding to cycles of 2 days and greater), and we can therefore examine at what frequencies predictability occurs. This provides insight into whether there exists short-run, long-run, or both types of dependence.     

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.