Do emerging markets with consistent returns have better future performance?

Using monthly data for 25 emerging markets around the world, it is found that emerging markets with recently consistent stock returns tend to have future returns that continue in the same direction. The effects are long-lived for negative consistency, and imply that capital flows are much more sensitive to market downturns than market upturns. Additionally, the longer a market has had consistently negative (positive) stock returns, the more negative (positive) are future returns. These results serve as confirmation that the consistency effects of Grinblatt and Moskowitz [J. Finan. Econ., 2004 Grinblatt, M and Moskowitz, T. 2004. Predicting stock price movements from the pattern of past returns. J. Finan. Econ., 71: 541–579. [Crossref], [Web of Science ®] , [Google Scholar], forthcoming] and Watkins [J. Behav. Finan., 2003 Watkins, B. 2003. Riding the wave of investor sentiment: an analysis of consistency as a predictor of future stock returns. J. Behav. Finan., 4: 1–32.  [Google Scholar], 4, 1–32] exist in emerging markets around the world.     

Do dividend changes predict the future profitability of firms?

Many previous studies have been conducted to test whether corporate dividend changes predict the future profitability of firms. While the debate continues, we assess the information content of dividends (ICD) hypothesis in the Korean market as it provides an interesting experimental setting for testing the hypothesis in the context of corporate governance. We find that it is difficult to support the ICD hypothesis if one accepts nonlinear patterns in earnings. However, when we divide the sample in terms of Chaebol vs. non‐Chaebol and high‐growth vs. low‐growth firms, we find that the ICD hypothesis becomes valid, especially for non‐Chaebol firms and for low‐growth firms. Therefore, we suggest that the validity of the ICD hypothesis may be dependent on firm characteristics such as the corporate governance structure and growth stage.     

Do hedge funds' exposures to risk factors predict their future returns?

This paper investigates hedge funds' exposures to various financial and macroeconomic risk factors through alternative measures of factor betas and examines their performance in predicting the cross-sectional variation in hedge fund returns. Both parametric and non-parametric tests indicate a significantly positive (negative) link between default premium beta (inflation beta) and future hedge fund returns. The results are robust across different subsample periods and states of the economy, and after controlling for market, size, book-to-market, and momentum factors as well as the trend-following factors in stocks, short-term interest rates, currencies, bonds, and commodities. The paper also provides macro-level and micro-level explanations of our findings.     

Do informed option investors predict stock returns? Evidence from the Taiwan stock exchange

In this paper, we set out to investigate the information content of options trading using a unique dataset to examine the predictive power of the put and call positions of different types of traders in the TAIEX option market. We find that options volume, as a whole, carries no information on TAIEX spot index changes. On the other hand, however, although foreign institutional investors do not engage in much trading, there is strong evidence to show that the trading in which they do engage has significant predictive power on the underlying asset returns. We also find that foreign institutional investors have greater predictive power with regard to in near-the-money and middle-horizon options.     

When do high stock returns trigger equity issues?

One of the most prominent stylized facts in corporate finance is that equity issues tend to follow periods of high stock returns. We document that firms exhibit such timing behavior only in response to high returns that coincide with strong institutional investor demand. When not accompanied by institutional purchases, stock price increases have little impact on the likelihood of equity issuance. The results highlight the importance of market reception for the timing of equity issues.     

Do changes in the SG&A ratio provide different information about changes in future earnings,analyst forecast revisions,and stock returns under different circumstances?

In fundamental analysis, increases (decreases) in the ratio of selling, general and administrative (SG&A) costs to sales (SG&A ratio) are perceived as negative (positive) signals regarding future firm performance. However, this interpretation focuses on the overall change in the SG&A ratio and ignores the underlying changes in the components of the ratio (sales and SG&A costs). Although prior research examines the changes in the SG&A ratio under some different circumstances, there is no study that examines all the ways that managers adjust costs in reaction to changes in sales. Therefore, I create six subsamples representing all possible combinations of changes in sales, SG&A costs, and the SG&A ratio and test whether changes in the SG&A ratio are informative about future earnings, analyst forecast revisions, and stock returns under these different circumstances. I find that changes in the SG&A ratio in four of my six subsamples provide information about changes in future earnings. I also find that analysts do not impound all of the information contained in the signals into their forecast revisions and in some cases investors appear to understand this fact.     

Do oil futures prices predict stock returns?

This paper explores stock return predictability by exploiting the cross-section of oil futures prices. Motivated by the principal component analysis, we find the curvature factor of the oil futures curve predicts monthly stock returns: a 1% per month increase in the curvature factor predicts 0.4% per month decrease in stock market index return. This predictive pattern is prevailing in non-oil industry portfolios, but is absent for oil-related portfolios. The in- and out-of-sample predictive power of the curvature factor for non-oil stocks is robust and outperforms many other predictors, including oil spot prices. The predictive power of the curvature factor comes from its ability to forecast supply-side oil shocks, which only affect non-oil stocks and are hedged by oil-related stocks.     

Do fear indices help predict stock returns?

This study investigates the forecasting power of implied volatility indices on forward looking returns. Prior studies document that negative innovations to returns are associated with increasing implied volatility of the underlying indices; thus, suggesting a possible relationship between extremely high levels of implied volatility and positive short term returns. We investigate this issue by examining the predictive power of three implied volatility indices, VIX, VXN and VDAX, on the underlying index returns. We extend previous research by also focusing on characterised selected stocks and examine the relationship between implied volatility indices and future returns across different sectors and classified portfolios. Our findings suggest that implied volatility indices are good predictors of 20-days and 60-days forward looking returns and illustrate insignificant predictive power for very short term (1-day and 5-days) returns.     

Can margin traders predict future stock returns in Japan?

A growing body of literature suggests that investor sentiment affects stock prices both at the firm level and at the market level. This study examines the relationship between investor behavior and stock returns focusing on Japanese margin transactions using weekly data from 1994 to 2003. Margin trading is dominated by individual investors in Japan. In analysis at the firm level, we find a significant cross-sectional relationship between margin buying and stock returns. Both market-level and firm-level analyses show that margin buying traders follow herding behavior. They seem to follow positive feedback trading behavior for small-firm stocks and negative feedback trading behavior for large firm stocks. Our results show that information about margin buying helps predict future stock returns, especially for small-firm stocks at short horizons. The predictive power does not diminish even after controlling for firm size and liquidity.     

Does long-term disequilibrium in stock price predict future returns?

We propose a trading strategy based on error correction term (ECT), the residuals from the cointegration relation between the levels of security and the market portfolio. We find that buying stocks in the top 10 % ECT and selling stocks in the bottom 10 % ECT generates 1.09 % a month for 6-month holding period over 1965–2005. The monthly return increases to 1.57 % when the above trading strategy is applied to stocks with insignificant cointegration with the market portfolio. This profit is robust to three and four factor models. Moreover, this profit is neither driven by small and illiquid stocks nor is the result of any inherent positive serial correlation.     

Do asset impairments and the associated disclosures resolve uncertainty about future returns and reduce information asymmetry?

The objective of this study is to provide insights into how Australian listed firms are implementing AASB 136 Impairments of Assets. Our first concern is whether uncertainty about future returns and information asymmetry motivates the recognition of asset impairments. We find no evidence that the recognition of asset impairments is associated with higher uncertainty about future returns. Furthermore, we find no evidence that the recognition of asset impairments is associated with higher information asymmetry. Our second concern is whether asset impairments and the associated disclosures provide information that reduces uncertainty about future returns and information asymmetry. While we find some evidence that asset impairments are associated with decreases in information asymmetry before the financial crisis, during the financial crisis, asset impairments are associated with increases in both measurement uncertainty and information asymmetry.     

Can stochastic discount factor models explain the cross-section of equity returns?

We propose a multivariate test of the capital asset pricing model (C-CAPM) of the cross-sectional variation in equity returns in which we compare cross-sectional variation in equity returns to the cross-sectional variation in their conditional covariance with stochastic discount factors. We use a multivariate generalized heteroskedasticity in mean model to estimate 25 portfolios that are formed on size and the book-to-market ratio. Each portfolio is allowed to have its own no-arbitrage condition. We find that although the conditional covariances of returns with consumption exhibit negative variation across size, they do not vary across the book-to-market ratio. Thus, C-CAPM can capture the size effect, but not the value effect. The fit is, however, improved by allowing the coefficients on the consumption covariances to be different. The value effect appears to be associated with the book-to-market ratio as well as size. On its own the book-to-market ratio does not generate additional information about average returns to C-CAPM. A possible explanation for these findings is that both small and low book-to-market ratio firms are expected to have higher rates of growth.     

Fluctuations in the UK equity market: what drives stock returns?

Present value parameters from a state-space model are estimated for the UK FT All-Share Index. The estimated parameters are used to construct a time series of expected future returns and expected future values of dividend growth, both of which are found to be time-varying with persistent components. Variations in the price-dividend ratio appear to be driven primarily by the variance in expected returns. A comparison with the findings from a present value-constrained vector autoregression model indicates that the latter forecasts future realized returns and dividend growth better than the series constructed using a state-space approach. Furthermore, when the model is estimated for monthly and quarterly data, expected dividend growth is found to be more persistent.     

Do FOMC minutes matter to markets? An intraday analysis of FOMC minutes releases on individual equity volatility and returns

This paper examines the 2006 to 2007 time period to determine the extent to which the release of the Federal Reserve minutes affects equity volatility and returns for 2832 individual firms. Using intraday data, we find that equity returns are essentially unaffected by FOMC minutes releases. We do find evidence of volatility effects, in that conditional volatility is lower prior to the minutes release and higher after the minutes release on release days, relative to a “control” day one week prior to the release date. These differences manifest at the 2:00–2:05 pm interval, and generally dissipate within 15 min. Consistent with previous literature, we also find evidence of both industry-specific and firm size effects in our data. Finally, we see that volatility is higher (lower) when the minutes are released after the Federal Reserve engages in restrictive (expansionary) monetary policy. Our results are robust to a variety of different definitions of the “control” dates, as well as differing industry definitions.     

Do commodities make effective hedges for equity investors?

The purpose of this paper is to evaluate whether commodities are effective hedges for equity holders. We employ three different methodologies to calculate time varying hedge ratios. First, we examine time-varying hedge ratios and how much portfolio risk can be reduced relative to a long position in the S&P 500. We calculate hedge ratios from realized variances and covariances; second, we estimate a recursive multivariate GARCH (BEKK) model and calculate the hedge ratios from the estimated covariances; and thirdly, we calculate the hedge ratios by estimating recursive OLS regressions. The results of our paper are very clear. First, commodities are not effective hedges for the S&P 500. Equity market investors and asset managers looking for a way to manage and reduce portfolio risk will be well advised to search for alternative hedges for the S&P 500 than commodities. Second, our results do not support the claim that commodities were a good hedge for the equity market during the financial crisis.     

The output gap and stock returns: Do cyclical fluctuations predict portfolio returns?

This study examines whether the output gap leads portfolio stock returns. The paper conducts in-sample and out-of-sample forecasting of US stock portfolios formed on the basis of size and value. First, the paper finds cross-sectional portfolios are predictable in-sample by the output gap. Out-of-sample evidence is weaker but still generally supports the finding that the historical average benchmark can be beaten. Secondly and most importantly, we find mixed evidence that the Fama–French factor mimicking portfolios can be forecasted by the output gap. In particular, there is some out-of-sample predictability of the size effect (SMB) suggesting this lags the output gap. However, the output gap, a key business cycle indicator, cannot predict the value effect (HML) either in-sample or out-of-sample. Our results add to the prior literature which finds that the factor mimicking returns are related contemporaneously (Petkova and Zhang, 2005) or lead (Liew and Vassalou, 2000) economic indicators.     

Do economic statistics contain information to predict stock indexes futures prices and returns? Evidence from Asian equity futures markets

This research examines the impact of local and international market factors on the pricing of stock indexes futures in East Asian countries. The purpose of this paper is to present a study of the significant factors that determine the major stock indexes futures’ prices of Hong Kong, Malaysia, Singapore, South Korea and Taiwan. This study first investigates the relationships between Hang Seng Index Futures, KLCI Futures, SiMSCI Futures, KOSPI Futures, Taiwan Exchange Index Futures and local interest rates, dividend yields, local exchange rates, overnight S&P500 index and a newly constructed index, Asian Tigers Malaysia Index (ATMI). 11 years historical data of stock indexes futures and the economic statistics are studied; 10 years in-sample data are used for testing and developing the pricing models, and 1 year out-of-sample data is used for the purpose of verifying the predicted values of the stock indexes futures. Using simple linear regressions, local interest rates, dividend yields, exchange rates, overnight S&P500 and ATMI are found to have significant impact on these futures contracts. In this research, the next period close is predicted using simple linear regression and non-linear artificial neural network (ANN). An examination of the prediction results using nonlinear autoregressive ANN with exogenous inputs (NARX) shows significant abnormal returns above the passive threshold buy and hold market returns and also above the profits of simple linear regression (SLR). The empirical evidence of this research suggests that economic statistics contain information which can be extracted using a hybrid SLR and NARX trading model to predict futures prices with some degree of confidence for a year forward. This justifies further research and development of pricing models using fundamentally significant economic determinants to predict futures prices.

     

Is size dead? A review of the size effect in equity returns

Beginning with Banz (1981), I review 30 years of research on the size effect in equity returns. Since Fama and French (1992), there has been a vigorous, ongoing debate on whether the size premium is a compensation for systematic risk. Since the late 1990s, research on the size effect has been characterized by two developments that are seemingly contradictory. At last, theoretical models have emerged in which the size effect arises endogenously as a result of systematic risk. However, recent empirical studies assert that the size effect has disappeared after the early 1980s. In this review, I address this disconnect between recent theoretical and empirical research.     

Do political factors affect stock returns during presidential elections?

This study investigates whether or not political factors such as government policy and political connections affected stock returns during the 2008 Taiwanese presidential election. We find that firms that benefitted from (were threatened by) the proposed Three-Links policy of the winning party experienced positive (negative) stock returns during the election. We use the sensitivities of firms’ returns to bilateral trade flows between Taiwan and China to measure the government-policy effect. Our results show that the effects of political connections weakly exist, but they become more significant when the support ratio of the winning party increased in polling data. We also find that only the government-policy effect holds for different crash-risk and corporate-governance levels. Finally, investment strategies based on both political factors can generate positive abnormal returns with respect to the Fama-French Three-factor Model.     

Do equity financing cycles matter? evidence from biotechnology alliances

In periods characterized by diminished public market financing, small biotechnology firms appear to be more likely to fund R&D through alliances with major corporations rather than with internal funds (raised through the capital markets). We consider 200 alliance agreements entered into by biotechnology firms between 1980 and 1995. Agreements signed during periods of limited external equity financing are more likely to assign the bulk of the control to the larger corporate partner, and are significantly less successful than other alliances. These agreements are also disproportionately likely to be renegotiated if financial market conditions subsequently improve.