Are Gulf stock markets efficient? Evidence from new multiple variance ratio tests

The purpose of this article is to test for the Random Walk Hypothesis (RWH) for seven stock markets in Gulf Cooperation Council (GCC) countries, and to determine the effect of the correction for thin trading. Three new multiple variance ratio tests are applied to both observed returns and returns corrected for thin trading. It is found overall that the RWH does not hold for the GCC stock markets at both daily and weekly frequencies. This evidence is particularly strong when daily returns are used, where the RWH is soundly rejected for both observed and corrected returns.     

Does extracting inflation from stock returns solve the purchasing power parity puzzle?

In a recent study by Chowdhry et al. (American Economic Review 95: 255–276, 2005), they suggest that the empirical failure of relative purchasing power parity (PPP) may be because the official inflation data are too sticky. Thus, after extracting the unobservable pure price inflation from equity markets, they find strong evidence supporting relative PPP in the short run. As a replication study, this paper first replicates their original findings successfully. We further investigate whether long-run relative PPP holds using the pure price inflation data constructed by Chowdhry et al. (2005). After constructing pure real exchange rate series using their pure price inflation data, we implement both unit root and cointegration tests on the pure real exchange rates. According to the test results, the evidence suggests that relative PPP does not hold in the long run. Thus, it may be too early to suggest a resolution of the PPP puzzle.     

Accruals quality,managers’ incentives and stock market reaction: evidence from Europe

We investigate if accruals quality is a valuable indicator of earnings quality for stock market investors. Our particular focus is on the incremental informative value of taking into account managers’ incentives for using accruals. We propose a market-based approach for assessing the usefulness of this indicator to improve investors’ decisions. Specifically, we examine the association between accruals quality and information asymmetry among stock market participants. Our empirical study uses data on European firms and our results are consistent with a positive association between poor earnings quality and high information asymmetry. However, given some previous studies suggesting that accruals-based measures may be noisy indicators of earnings quality, we develop a method to increase the informational content of the accruals quality measure. Based on our results, we find that combining accruals quality with the dispersion in analysts’ forecasts provides a better indicator of earnings quality rather than only accruals quality.     

Early warning signals using AVaRs of infinitely divisible GARCH models — evidence from stock index markets

Classical time series models have failed to properly assess the risks that are associated with large adverse stock price behaviour. This article contributes to autoregressive moving average model–GARCH (ARMA–GARCH) models with standard infinitely divisible innovations and assesses the performance of these models by comparing them with other time series models that have normal innovation. We discuss the limitations of value at risk (VaR) and aim to develop early warning signal models using average value at risk (AVaRs) based on the ARMA–GARCH model with standard infinitely divisible innovations. Empirical results for the daily Dow Jones Industrial Average Index, the England Financial Times Stock Exchange 100 Index and the Japan Nikkei 225 Index reveal that estimating AVaRs for the ARMA–GARCH model with standard infinitely divisible innovations offers an improvement over prevailing models for evaluating stock market risk exposure during periods of distress in financial markets and provides a suitable early warning signal in both extreme events and highly volatile markets.     

Do stock market returns predict changes to output? Evidence from a nonlinear panel data model

Recent empirical work suggests a predictive relationship between stock returns and output growth. We employ quarterly data from a panel of 27 countries to test whether stock returns as useful in predicting growth. Unlike previous research, our approach allows for the possible non-linear effect of recessions on the growth-return relationship. There is strong evidence to suggest that a linear model would be misspecified and provide potentially misleading inference. Using a switching regression approach, we find evidence that returns are most useful in predicting growth when the economy is in recession.First version received: November 2002/Final version received: April 2003This paper benefited greatly from discussions with Kalvinder Shields, Mark Harris, Pete Summers, and Vance Martin. Two anonymous referees provided useful comments on an earlier version of the paper for which we are grateful. The usual disclaimer applies to any errors and omissions. Funding from The University of Melbourne greatly assisted in the completion of this paper.     

What does tax aggressiveness signal? Evidence from stock price reactions to news about tax shelter involvement

We study the stock price reaction to news about corporate tax aggressiveness. We find that, on average, a company's stock price declines when there is news about its involvement in tax shelters. We find some limited evidence for cross-sectional variation in the reaction. For example, the reaction is more negative for firms in the retail sector, suggesting that part of the reaction may be a consumer/taxpayer backlash. In addition, the reaction is less negative for firms that are viewed to be generally less tax aggressive, as proxied by the firm's cash effective tax rate. We interpret this as being consistent with the market reacting positively to evidence that a firm is trying to reduce taxes when their financial reports would lead one to believe the firm is not tax aggressive.     

Analyst coverage and stock return synchronicity: evidence from regulation changes in China’s IPO market

This article investigates the relation between analyst coverage and stock return synchronicity in the IPO market. Using a unique data set in China from 2005 to 2012, we find a significantly different effect of analyst coverage on synchronicity before and after the implementation of important 2009 IPO regulation changes in China. Specifically, we document that analyst coverage reduces synchronicity but that this effect is significant only after 2009. In addition, we extend this research to further distinguish the information production role of underwriter and independent analysts. We find that prior to 2009, underwriter analysts’ coverage decreases synchronicity but independent analysts’ coverage does not. However, in the post-2009 period, both types of analyst coverage are significantly and inversely associated with synchronicity. Overall, our results support analysts’ role as producers of firm-specific information in an emerging IPO market and shows that this role depends on the institutional environment.     

Does reference point matter in the leverage–return relationship? Evidence from the US stock market

The leverage–return relationship is supported by inconclusive empirical evidence in terms of its sign and significance. In this study, we argue that such a puzzling relationship can be understood by extending the traditional theoretical framework in a way that captures the reference dependence characteristics of prospect theory. We postulate that a firm’s leverage position relative to its reference point (i.e. target leverage) combined with market conditions places firms in either a gain or a loss domain, thereby resulting in different leverage–return relationships. Leverage and expected equity returns generally exhibit positive and negative relationships in gain and loss domains, respectively. Three hypotheses are derived and tested using 1998–2013 empirical data from the US stock market. This article contributes to the existing literature by confirming the applicability of prospect theory in explaining expected returns in the stock market.     

Did bubbles migrate from the stock to the housing market in China between 2005 and 2010?

The speculative nature of both stock and housing markets in China has attracted the attention of observers. However, while stock market data are easily available, the low frequency and low quality of publicly available housing price data hampers the study of the relationship between the two markets. We use original hedonic weekly resale housing prices of a major Chinese housing market and study them in conjunction with Shanghai's stock market index in the second half of the 2000s. The use of the Phillips et al. (2015 a,b) recursive explosive‐root test enables us to detect and date speculative episodes in both markets. We then implement the Greenaway‐McGrevy and Phillips (2016) methodology to detect the presence of migration between the two types of bubbles. We detect significant migration from the stock to the housing market bubble in 2009 and a temporary spillover in 2007.     

Does the market care about investor protection practices in China?

This study develops a scorecard with which to measure the investor protection practices of major listed firms in China during 2007–2010. We use time-series data to examine the relationship between the change in firm investor protection practices and market performance. Our results show that firms exhibiting improvements in investor protection practices manifest a subsequent increase in buy-and-hold abnormal returns. The results further indicate that the changes in the sub-index have different effects on a firm’s future performance. Shareholder rights to be rewarded seem to have the most significant and positive effect on a firm’s future performance for both local and international investors. Moreover, international investors pay attention to their rights to information. Our results provide evidence in support of the notion that the market does care about firm’s investor protection practices. The findings are robust to other measures of firm performance.     

Individual investor’s limited attention and IPO performance

The paper models and verifies the spread and decay of investor’s attention before listing on the stock market by using the Baidu Index as a proxy for investor attention of the frequency of searches. We find that individual investor’s attention has a significant influence on the first-day IPO return. We empirically study the allocation of investor attention among several stocks and discover that the more stocks going public on the same day, the milder and more similar their performance tends to be. This paper is the first to research IPO performance and individual attention.     

Do macroeconomic variables have regime-dependent effects on stock return dynamics? Evidence from the Markov regime switching model

The predictability of stock return dynamics is a topic discussed most frequently in empirical studies; however, no unanimous conclusion has yet been reached due to the ignorance of structural changes in stock price dynamics. This study applies various regime switching GJR-GARCH models to analyze the effects of macroeconomic variables (interest rate, dividend yield, and default premium) on stock return movements (including conditional mean, conditional variance, and transition probabilities) in the U.S. stock market, so as to clearly compare the predictive validity of stable and volatile states, as well as compare the in-sample and out-of-sample portfolio performance of regime switching models. The empirical results show that macro factors can affect the stock return dynamics through two different channels, and that the magnitude of their influences on returns and volatility is not constant. The effects of the three economic variables on returns are not time-invariant, but are closely related to stock market fluctuations, and the strength of predictability in a volatile regime is far greater than that in a stable regime. It is found that interest rate and dividend yield seem to play an important role in predicting conditional variance, and out-of-sample performance is largely eroded when the effects of these two factors on volatility are ignored. In addition, the three macro factors do not play any role in predicting transition probabilities.     

Has co-movement dynamics in emerging stock markets changed after global financial crisis? New evidence from wavelet analysis

In this article, we revisit the issue of contagion, interdependence and changes in correlation structure after the Global Financial Crisis (GFC) of 2008 between developed and emerging markets in a time-frequency domain using a wavelet-based approach for the period spanning over 1 January 1999 to 8 November 2016. We report evidences of: (a) weaker contagion for Latin American emerging markets during GFC, (b) a strong contagion effect for emerging markets in Europe and the Middle East and (c) a fall in long-run co-movements after GFC, which means by investing in emerging markets, the diversification benefits can be derived in the long run. We report evidence of coexistence of contagion and permanent change in correlation structure.     

What determines stock liquidity in Australia?

Using an index of corporate governance quality (CGQ), we provide the first robust evidence of the determinants of stock liquidity in Australia. We assume that CGQ affects stock liquidity because effective governance decreases information asymmetries between insiders (e.g. managers) and outsiders (e.g. investors), as well as among outsiders, by improving information transparency of a firm. Consistent with agency theory, this study, using 435 large capitalization firms over the period from 2001 to 2008, finds a significant positive relationship between CGQ and stock liquidity, suggesting that better governed firms have a higher level of stock liquidity. These findings are robust to alternative proxies of CGQ, stock liquidity and endogeneity bias.     

Did Baltic stock markets offer diversification benefits during the recent financial turmoil? Novel evidence from a nonparametric causality-in-quantiles test

Motivated by financial liberalization investors seek for new investment opportunities through international portfolio diversification. To this end we explore any asymmetric causal relationship between developed European stock markets (Germany, France and UK) and emerging Baltic markets namely; Estonia, Latvia and Lithuania. Our analysis focuses on the period before and after countries’ EU accession and pre- and post the global financial crisis. For this purpose, both the standard parametric test for causality and a novel nonparametric test for causality-in-quantiles are employed. The results of both the parametric and nonparametric Granger causality test support a causal relationship in mean that runs from all of the major markets to the Baltic markets across both samples. The results imply the existence of significant nonlinear return and volatility spillover from European markets to Baltic markets. Policy implications for international investors are also discussed.     

Return threshold model analysis of two stock markets： Evidence study of Italy and Germany＇s stock returns

This paper discusses the model construction and the association between the Italy and the Germany＇s stock markets. The period of study data is from January 3, 2000 to June 30, 2008. This paper also utilizes Student＇s t distribution to analyze the proposed model. The empirical results show that the two stock markets are mutually affected each other, and the dynamic conditional correlation （DCC） and the bivariate asymmetric-GARCH （1, 2） model is appropriate in evaluating the relation between them. The empirical result also indicates that Italy and Germany＇s stock markets show a positive relationship. The average value of correlation coefficient equals to 0.8424, which implies that the two stock markets return volatility have a synchronized influence on each other. In addition, the empirical result also shows that there is an asymmetrical effect between Italy and the Germany＇s stock markets, and demonstrates that the good news and bad news of the stock returns＇ volatility will produce the different variation risks for Italy and the Germany＇s stock price markets.     

Testing for long memory in Chinese stock market

This paper proposes a long memory analysis based on wavelet transform of financial data. This method treats return series and volatility series in the stock market as a fractional differenced noise process, and analyzes it by MODWT（maximal overlap discrete wavelet transform）. The result shows there is a lineal relationship between wavelet variance logarithm and scale logarithm, so a long memory parameter can be obtained by using the relationship. This method is proved to be effective and feasible by analyzing the return series and volatility series of composite indexes of Shanghai and Shenzhen stock market.     

Currency exposures of the oil and natural gas stock prices in the Hushen-300 stock market： A nonlinear model approach

The paper embarks to investigate the relationship between currency risk and stock prices of the oil and natural gas exploitation industry in the value-weighted Hushen-300 stock market, by applying the standard Capital Asset Pricing Model （CAPM） and nonlinear exchange rate exposure model to the Renminbi against US dollar. The results show that the currency exposure does vary in the oil-gas stock prices throughout the bull and bear market. The study suggests that the models of the equilibrium exchange rate exposure must be extended to considering the nonlinear exchange rate exposure, the regime periods of bull and bear market, and the industry types that is sensitive to the currency exposures. The nonlinear dynamic relationship between the exchange rate changes and the Chinese energy stock prices throughout the bull and bear market add to the recent empirical evidences that foreign exchange markets and stock markets are closely correlated.     

Are Islamic stock markets efficient? A time-series analysis

This article investigates the weak-form informational efficient hypothesis for three major Islamic stock markets (world, emerging and developed). Unlike previous studies, we applied different parametric and nonparametric tests to investigate efficiency in the short and long horizons. Using recent data over the period May 2002–June 2012, we developed a time-series analysis of Islamic stock price dynamics in the context of the recent global financial crisis (2008–2009). Our analysis offers two interesting results. First, emerging Islamic stock markets seem to be less efficient than developed Islamic markets, suggesting interesting investment opportunities and diversification benefits from this region in both the short run and the long run. Second, nonrejection of the cointegration hypothesis for developed Islamic markets and the global conventional stock market point to efficiency for the former in the long term, even if it is inefficient in the short term. This finding has at least two economic and political implications: (i) investors who seek moderate risk would do well to opt for Islamic funds in developed countries, particularly as they share the same tendency and provide similar expected returns in the long term as conventional funds, (ii) Islamic financial systems can offer a useful model that can help to reform and remodel conventional financial institutions.