DYNAMIC STOCK RETURN–VOLUME RELATION: EVIDENCE FROM EMERGING ASIAN MARKETS

This paper empirically examines the dynamic stock return–volume relations for six emerging Asian markets: Indonesia, Malaysia, Singapore, South Korea, Taiwan, and Thailand. Evidence is found that trading volume Granger causes stock return in quantiles and the causal effects of volume are heterogeneous across quantiles. This shows that volume carries some information to the return and could be interpreted in light of theoretical models. In addition, we find that there is bi‐directional causality between stock return and trading volume in most of the markets. The finding indicates that those Asian emerging markets with different institutions and information flows than more mature markets have present similar causal effects on the stock return–volume relation. Furthermore, the cross‐country evidence shows that the US market helps to predict the returns of the emerging Asian markets.     

Does speculation Granger cause return in Chinese commodity markets?

We test the Granger causal relations between speculation and returns in Chinese commodity markets using quantile regression method. We find that speculation Granger causes returns in rebar, bean pulp and rapeseed oil markets. At lower quantiles, estimates are negative; but estimates are positive at upper quantiles. This indicates that larger speculation results in larger return volatility.     

Causal effects of the United States and Japan on Pacific-Rim stock markets: nonparametric quantile causality approach

This article adopts a nonparametric quantile causality approach to examine the causal effects of the U.S. and Japan stock markets on the stock markets of the Pacific-Rim region. This approach allows us to detect not only nonlinear causalities in conditional return (mean) and conditional volatility (variance) but also the asymmetries of causalities under extreme market conditions (bullish vs. bearish states). Our results provide significant evidence of causality in return and volatility at different points of the conditional distributions of returns, with the greater effects from the U.S. than from Japan. Asymmetric quantile causality patterns are particularly pronounced in the case of Japan.     

Nonlinear causality relationship between stock and real-estate returns in PIGS countries: wealth effect or credit-price effect

It is the first research to investigate for nonlinear interdependence of these two markets in the PIGS (Portugal, Italy, Greece and Spain) countries based on the quantile causality test. The results reveal the existence of the nonlinear causality relationship between the stock returns and real-estate returns in the PIGS countries.

The empirical results of the quantile causality test suggest a significant causal relationship between these two markets in the PIGS countries, especially in the tail quantile. The existence of a significant tail interdependence implies that investors are unable to hedge the risk across the real-estate and stock markets when they are extremely volatile. Therefore, when there exist extreme returns between the two markets in the PIGS countries, both continuous negative impacts imply that instability in the real-estate market drives instability in the stock market and vice versa. It could be one of the major reasons why it deepened the systemic risk of the European sovereign debt crisis.     

The heterogeneous dependence between global crude oil and Chinese commodity futures markets: evidence from quantile regression

This paper explores the dependence between global crude oil and Chinese commodity futures markets across different quantiles of the return distributions. Based on weekly data from 11 June 2004 to 7 July 2017, we address this issue by applying a quantile regression method. This technique provides a more detailed investigation of the dependence. Moreover, considering the structural breaks caused by market turmoil or financial crises, we divide the full period of every commodity sector market into sub-periods based on these break dates to further explore the dependence changes. The empirical results indicate that the dependence between global crude oil and Chinese commodity futures markets is different across quantiles in different commodity sectors. The dependence is significantly positive, except in markets with high expected returns. Additionally, the effects caused by structural breaks are distinctly heterogeneous across quantiles. The effect of the same break on the degree of dependence exhibits an increasing tendency as the quantile level increases, which suggests that markets with high expected returns are more susceptible to crises. Finally, we apply a prediction analysis to further verify the heterogeneity of the commodity sectors, which may be the cause of the heterogeneous dependence.     

Asymmetric spillover effects between the Shanghai and Hong Kong stock markets: evidence from quantile lagged regression

This article surveys the asymmetric spillover effects between the mainland China-based Shanghai Composite Index (SCI) and the Hong Kong based Hang Seng Index (HSI) using a quantile lagged regression model. Compared to previous studies, this article, based on data before and after the 2008 global financial crisis, presents a more detailed analysis, as we investigate the spillovers in terms of returns, volatilities and exchange rates between the renminbi (RMB) and the Hong Kong dollar (HKD) throughout the entire conditional return distribution, including the central quantiles, which are closely related to the normal circumstances, and the extreme quantiles, which correspond to the bear and bull markets. First, we find that the return spillovers from its lagged returns or from the other index not only vary across time but also depend on stock state. Second, while return volatility may boost the stock market in a bull market, it accelerates the decline in a bear market. Third, the depreciation of the RMB relative to the HKD does not significantly affect current returns for the HSI, while it negatively affects current returns for the SCI in a bad state after the crisis. The findings presented in this article will facilitate investors’ understanding of the two stock markets.     

Analysts’ Forecast Dispersion and Stock Returns: A Quantile Regression Approach

Prior research has not provided conclusive evidence on the association between analysts’ forecast dispersion and subsequent stock returns. Since inferences from prior studies may be confounded by research design choices, we use the quantile regression (QR) approach and assess the hidden non-monotonic relations between dispersion and stock returns within a broader sample. The empirical results show that dispersion is negatively associated with subsequent stock returns when the latter is in lower quantiles. In contrast, when the stock returns are in high quantiles, dispersion is positively associated with subsequent stock returns. Moreover, the association between dispersion and stock returns is trivial when the mid-range return quantiles are concerned. These non-uniform connections between dispersion and stock returns reflect the different status of overpricing correction process. Our findings help to reconcile the mixed results reported by prior research concerning the relation between analysts’ forecast dispersion and subsequent stock returns.     

Spillovers from the USA to stock markets in Asia: a quantile regression approach

This article analyses return spillovers from the USA to stock markets in Asia by means of quantile regressions. Traditional studies consider spillovers as effects of the conditional means of foreign returns onto the conditional means of chronologically succeeding domestic markets’ returns. We, by contrast, study the full range of quantiles of the conditional distribution of the domestic markets’ returns. This enables us to document the detailed structure of spillovers across return quantiles. Generally, we find spillovers from the USA to Asia to be negative. Specifically, however, we reveal an asymmetric structure of spillovers with an increasing negative magnitude from lower to upper return quantiles. Theoretically, this pattern is consistent with an asymmetric overreaction of traders in Asia to news from the US market. Extensions from the baseline model further suggest the presence of contagion throughout the financial crisis of 2007–2008 as well as of calm-down effects over weekends.     

Investor sentiment and the prediction of stock returns: a quantile regression approach

We employ quantile regression to provide a detailed picture of the stock return forecasting ability of investor sentiment. We find that investor sentiment predicts aggregate stock returns at lower quantiles. However, the forecasting power is lost at upper quantiles. The results are robust after controlling for a comprehensive set of macroeconomic and financial predictors and for characteristic portfolios. We also show that investor sentiment consists mainly of cash flow news and contains little information about discount rate news. The ability to forecast cash flows increases gradually from the lower quantiles to upper quantiles. Our results do not support that the ability of investor sentiment to predict stock returns comes from a rational forecast of future cash flows.     

Does economic policy uncertainty matter for commodity market in China? Evidence from quantile regression

ABSTRACT

This paper investigates the effect of economic policy uncertainty (EPU) on China’s agricultural and metal commodity futures returns across quantiles. We address this issue using the panel quantile regression approach, which allows for a more complete analysis of various conditions in the commodity market (i.e. bearish, normal, and bullish markets). Our empirical results reveal that domestic EPU shocks have a significantly negative effect on agricultural futures returns in bearish markets and a significantly positive effect on metal futures returns in bullish markets. The impacts of both domestic and U.S. EPU shocks on commodity markets are heterogeneous across quantiles and are sector specific. Additionally, by isolating positive and negative EPU shocks, the regression and test results indicate an asymmetric response of commodity futures prices in bullish markets. Moreover, our findings indicate that the metal futures market has a higher financialisation level than the agricultural futures market. The findings can be utilized by policymakers and investors.     

Stock returns and mutual fund flows in the korean financial markets: a system approach

ABSTRACT

This paper investigates dynamic and causal relations between stock returns and mutual fund flows in Korea using a system method that utilizes information from the stock, bond, and money markets. For this purpose, we employ the Dynamic Seemingly Unrelated Regression, the Seemingly Unrelated Regression Error Correction Model, and two causality tests in a system method to account for cross-equation correlations among markets that have a close relationship with one another. Furthermore, we use the information in the variance-covariance matrix of residual to improve the efficiency of the statistical estimates. The empirical evidence from the system method indicates that fund flows do not respond to eliminate deviations from long-run equilibrium, and stock prices cause net fund flows in the Korean market, implying that investors move their money to the securities that yield higher returns to rebalance their investment portfolios in the short-run. Thus, our findings do not support the popular notion of mutual fund flows as the driving force behind rallies in the Korean financial markets.     

Does international oil volatility have directional predictability for stock returns? Evidence from BRICS countries based on cross-quantilogram analysis

While numerous studies have investigated the relationship between oil volatility and stock returns, it is surprising that little research has examined the quantile dependence and directional predictability from oil volatility to stock returns in BRICS (Brazil, Russia, India, China, and South Africa) countries. We address this issue by using the cross-quantilogram model proposed by Han et al. (2016). The empirical results show that, overall, oil volatility has a directional predictability for the stock returns in BRICS countries. When the oil volatility is in a low quantile (lower than its 0.1 quantiles), it is less likely to show either a large loss or a large gain in the stock market. In contrast, there is an increased likelihood of either large loss or a large gain in the stock market when the oil volatility is in a high quantile (higher than its 0.9 quantiles). The directional predictability from the oil volatility to stock returns depends on the net position of oil imports and exports of these BRICS countries in the oil market. The net oil exporters (Russia and Brazil) are less likely to have large gains and large losses in the stock market than are the net oil importers (India, China, and South Africa) when the oil volatility is in a low quantile. The net oil exporters are more likely to have large gains and large losses than are the net oil importers when the oil volatility is in a high quantile. The results are robust to change in the variable of oil volatility and the sample interval.     

Evidence of Stock Returns and Abnormal Trading Volume: A Threshold Quantile Regression Approach

This paper presents a capital asset pricing model‐based threshold quantile regression model with a generalized autoregressive conditional heteroscedastic specification to examine relations between excess stock returns and “abnormal trading volume”. We employ an adaptive Bayesian Markov chain Monte Carlo method with asymmetric Laplace distribution to study six daily Dow Jones Industrial stocks. The proposed model captures asymmetric risk through market beta and volume coefficients, which change discretely between regimes. Moreover, they are driven by market information and various quantile levels. This study finds that abnormal volume has significantly negative effects on excess stock returns under low quantile levels; however, there are significantly positive effects under high quantile levels. The evidence indicates that each market beta varies with different quantile levels, capturing different states of market conditions.     

Insurance activity,real output,and geopolitical risk: Fresh evidence from BRICS

This paper fills some empirical gaps by evaluating the causal associations among insurance premiums, real output, and geopolitical risk in BRICS (Brazil, Russia, India, China, South Africa) from 1985 to 2017. We utilize a newly-developed Granger-causality quantile analysis to assess the causal relationships among the series under consideration in each distribution quantile. Our empirical results reveal unidirectional causality that runs from real output and geopolitical risk to insurance activities in Brazil and South Africa. We also observe bi-directional lower-tail causality among real output, insurance premiums, and geopolitical risk in Russia. Findings also present bi-directional causality among real output, insurance premiums, and geopolitical risk at different quantiles. Knowledge of these causal relationships can prevent governments from conducting a ‘one-size-fits-all’ policy.     

Exchange Rate Exposure of Chinese Firms at the Industry and Firm Level

This study investigates the exchange rate exposure of Chinese firms at the industry and firm level based on the conventional capital asset pricing model (CAPM) framework. At the industry level, the dynamic conditional correlation MGARCH (DCC MGARCH) estimates demonstrate that the market model and three‐factor model are appropriate for exposure measurements, and industry returns are more likely to be exposed to unanticipated changes in the real exchange rate and the trade‐weighted effective exchange rate, particularly for manufacturing industries. At the firm level, although the seemingly unrelated regression (SUR) estimates vary across markets, it is apparent that there is a relationship between firm size and exposure effects, which also show that lagged exchange rate changes have significant exposure effects on firm returns. This study finally suggests that non‐financial firms should set up special commissions to hedge currency risks of their future cash flows.     

Crude oil and BRICS stock markets under extreme shocks: New evidence

In this paper, we propose an extreme Granger causality analysis model to uncover the causal links between crude oil and BRICS stock markets. Instead of analyzing the average causal relationship, as is usually done, we first decompose the data into three cumulative components and investigate the causality between different combinations of extreme positive, extreme negative and normal shocks. These types of combinations can describe all facets of the interactions between crude oil and BRICS stock markets, especially under extreme shocks. In contrast to the results obtained by the traditional Granger causality test, our empirical findings demonstrate that the effect of oil price changes on the stock markets is stronger under extreme circumstances than under normal circumstances. Furthermore, large upward or downward oil price changes have an asymmetric impact on extreme upward or downward stock price changes. Finally, robustness checks verify the rationality and validity of the extreme Granger causality analysis.     

A nonlinear Granger causality test between stock returns and investor sentiment for Chinese stock market: a wavelet-based approach

In this article, we re-examine the causality between the stock returns and investor sentiment in China. The number of net added accounts is used as a proxy for investor sentiment. To mimic the different investment horizons of market participants, we use the wavelet method to decompose stock returns and investor sentiment into time series with different frequencies. Additionally, we test for nonlinear causal relationships based on Taylor series approximation. Our results indicate that there is a one-directional linear causality from stock returns to investor sentiment on the original series, while there is a strong bi-directional nonlinear causality between stock returns and investor sentiment at different timescales.     

The risk-return relations: evidence from the Korean and Taiwan stock markets

This article examines the risk-return relations conditional on up and down market periods in the Korean and Taiwan stock markets. Based on statistical tests adjusted for the effects of heteroskedasticity and autocorrelation of the residuals, beta is found positively (negatively) related to realized returns in up (down) markets. However, the results are sensitive to portfolio aggregation methods. Its role as a risk measure vanishes in down markets for the two-way (beta-size and size-beta) sorted portfolios. Unsystematic risk is significantly and positively priced only in up markets and mainly for beta-sorted portfolios while total risk is correctly priced except in Taiwan during down markets. Moreover, the impact of skewness and kurtosis on realized returns is not only sensitive to portfolio aggregation methods but also different across stock markets. They are found to be more relevant risk characteristics in the Korean than in the Taiwan stock market.     

The comovement between exchange rates and stock prices in the Asian emerging markets

This study investigates the comovement between exchange rates and stock prices in the Asian emerging markets. The sample covers major institutional changes, such as market liberalization and financial crises, so as to examine how the short-term and long-term relations change after such events. The autoregressive distributed lag (ARDL) model proposed by Pesaran et al. (2001) is adopted, which allows us to deal with structural breaks easily, and to handle data that have integrals of different orders. Interest rates and foreign reserves are also included in the analysis to reduce potential omitted variable bias. My empirical results suggest that the comovement between exchange rates and stock prices becomes stronger during crisis periods, consistent with contagion or spillover between asset prices, when compared with tranquil periods. Furthermore, most of the spillovers during crisis periods can be attributed to the channel running from stock price shocks to the exchange rate, suggesting that governments should stimulate economic growth and stock markets to attract capital inflow, thereby preventing a currency crisis. However, the industry causality analysis shows the comovement is not stronger for export-oriented industries for all periods, such as industrials and technology industries, thus implying that comovement between exchange rates and stock prices in the Asian emerging markets is generally driven by capital account balance rather than that of trade.     

Does investor sentiment dynamically impact stock returns from different investor horizons? Evidence from the US stock market using a multi-scale method

This article uses the investor sentiment index to investigate the Granger causality between investor sentiment and stock returns for the US economy using a multi-scale method. To focus on the local analysis of different investor horizons, bivariate empirical mode decomposition is used to decompose time series of investor sentiment and stock returns at different timescales. We employ the linear and nonlinear integrated Granger causality method to examine the causal relationship of decomposed series on similar timescales. The results indicate both strong bilateral linear and nonlinear causality between longer-term investor sentiment and stock returns. However, there is no strong evidence for correlation of stock returns and investor sentiment on shorter timescales.