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The Chinese stock market is a typical emerging market with special features that are very different from those of mature markets. The objective of this study is to investigate whether and how these features affect the volatility‐volume relation for Chinese stocks.

This paper examines the roles of the number of trades, size of trades, and share volume in explaining the volatility‐volume relation in the Shanghai Stock Exchange with high frequency trade data used.

The results confirm that the volatility‐volume relation is driven mainly by the number of trades on the Chinese stock market. The number of trades explains the volatility‐volume relation better than the size of trades. Furthermore, some results are obtained that differ from those of mature markets, such as the US market. The results show that the second largest sized trades affect the volatility more than other trades on the Chinese market.

The results show that, in the Shanghai Stock Exchange, informed traders camouflage their private information or manipulation behavior through the second largest sized trades. The results may have important implications for work explaining the volatility‐volume relation on the Chinese stock market, further providing a reference by which to regulate emerging markets.

The purpose of this paper is to examine the joint dynamics of volatility–volume relation in the high-yield (junk) corporate bond market during the 2007–2008 financial crisis.

The author proposes a new empirical model of three-stage equations to better estimate the volume–volatility relation that helps in alleviating three econometrical problems. In Stage 1, the author estimates the fitted values of trading volume using a censored regression model, to alleviate the truncation problems of using Transaction Reporting and Compliance Engine data. In Stage 2, the author calculates the fitted values of bond return volatility using asymmetric Sign-GARCH model, to control for the asymmetric volatility in return series. In Stage 3, the author uses the fitted values of trading volume from the censored regression model (Stage 1) and the fitted values of return volatility from the GARCH model (Stage 2), to better alleviate the endogeneity problems between both variables.

The central finding is that conclusions about the statistical significance and the direction of the volume–volatility relationship in the junk bond market are dependent on the econometric methodology used.

From a practitioner perspective, it is important for professional traders holding positions in fixed income securities in their trading accounts to be aware of their asymmetric time-varying volume–volatility shifting trends. Such knowledge helps traders diversify their positions and manage their portfolios more appropriately.

This study aims to revisit the stock price–volume relations, providing new evidence from the emerging market of Qatar. In particular, three main issues are examined using both aggregate market- and sector-level data. First, the return–volume relation and whether or not this relation is asymmetric. Second, the common characteristics of return volatility; and third, the nature of the relation between trading volume and return volatility.

The study uses the OLS and VAR modeling approaches to examine the contemporaneous and dynamic (causal) relations between index returns and trading volume, respectively, while an EGARCH-X(1,1) model is used to analyze the volatility–volume relation. The data set comprises daily index observations and the corresponding trading volumes for the entire market and the individual seven sectors of the Qatar Exchange (i.e. banks and financial services, consumer goods and services, industrials, insurance, real estate, telecommunications and transportation).

The empirical analysis reports evidence of a positive contemporaneous return–volume relation in all sectors barring transportation and insurance. This relation appears to be asymmetric for all sectors. For the market and almost all sectors, there is no significant causality between returns and volume. By and large, these findings lend support for the implications of the mixture of distributions hypothesis (MDH). Lastly, the information content of lagged volume seems to have an important role in predicting the future dynamics of return volatility in all sectors, with the industrials being the exception.

The findings provide important implications for portfolio managers and investors, given that the volume of transactions is generally found to be informative about the price movement of sector indices. Specifically, tracking the behavior of trading volume over time can give a broad portrayal of the future direction of market prices and volatility of equity, thereby enriching the information set available to investors for decision-making.

Based on both market- and sector-level data from the emerging stock market of Qatar, this study attempts to fill an important void in the literature by examining the return–volume and volatility–volume linkages.

This paper examines the information efficiency of KOSDAQ50 and KOSPI200 index futures markets. The study analyzes and compares both markets in three respects : 1) price discovery (lead-lag relationship between spot and futures markets.), 2) volatility-volume relationship, and 3) mispricings between spot and futures prices. The first, analysis shows the in the KOSPI200 market, futures price leads spot price. While spot price leads futures price in the KOSDAQ50 market. The second analysis shows that the volatility-volume relation is positive in the KOSPI200 futures market, supporting the hypothesis of mixture of distribution. In contrast, there is little relation between volume and volatility in the KOSDAQ50 futures market. This result casts doubt that the futures market price reflects information. The last analysis shows that the magnitude of mispricing becomes smaller with more volume in the KOSPI200 futures market, while it becomes larger with more volume in the KOSDAQ50 futures market. The overall results imply that the KOSDAQ50 futures market is less informationally efficient that the KOSPI200 market. The inefficiency appears due to the lack of institutional investor participation, especially securities firms, in making up the market.

The purpose of this paper is to re-examine the effectiveness of price limits on stock volatilities in China over a more recent time period spanning from 2007 to 2012. The motivation stems from the fact that very high stock market volatilities are observed in China and we are sceptical of the volatility mitigating effect claimed by advocates of price limits.

The effectiveness of price limits on volatilities is examined using an event study methodology and within an expanded framework of volatility-volume relationships. The sample stocks include the 300 component stocks of the CSI300 Index.

Both event study and regression analysis suggest that price limits exaggerate market volatilities by causing volatility spillovers. The destabilising effect is much more pronounced for small firm stocks and when the market falls. In addition to the informational source of volatilities (represented by volume), price limits create another non-trivial frictional source of volatilities in China’s stock market.

This research is the first to re-examine the price limit effect in China’s stock market in an expanded framework of volatility-volume relationships. It identifies price limits, in addition to information, as another non-trivial frictional source of volatilities. The findings derived from a recent sample period confirm the conventional view of inefficiency of price limits raised by Fama (1989) and provide evidence in support of the pervasive trend of stock market deregulations.

This study aims to examine whether global gold futures returns volatilities and trading activities are threshold cointegrated.

This study considers 11 gold futures markets, including 3 developed futures markets and 8 developing futures markets. This study also analyzes futures trading activities for speculators and hedgers. This study uses a nonlinear threshold vector error correction model (TVECM) and a threshold Lagrange multiplier (LM) test proposed by Hansen and Seo (2002).

The findings show that global gold futures return volatilities (FRV) and trading activities are not always threshold cointegrated. Most developed futures markets exhibit threshold cointegrated of gold FRV and trading activities for speculators and hedgers, whereas some developing futures markets exhibit threshold cointegrated. It suggests that speculators and hedgers trading activity conveys valuable information about changes in market volatility dynamics. On the other hand, responses to error-correction effect among gold FRV and trading activities for speculators and hedgers are dramatically different for developed and developing gold futures markets, respectively, particular in the unusual regime.

Research results show that threshold cointegration between global gold FRV and trading activities matters but not always. Thus, threshold relations have improved the authors’ understanding of global gold futures price discovery process with a threshold. For research limitations, this study uses only near month futures contracts, as it contains more information but not using far month contracts.

The findings may have important trading implications with additional insights in a(n) (un)usual regime further regulation may be detrimental to the price responsiveness in futures markets if increased price volatility and trading volume are attributed to liquid and efficient markets.

The findings may have important policy implications with additional insights. For example, in a(n) (un)usual regime greater regulatory restrictions may be warranted to decrease market inefficiencies if increased price fluctuations are caused by increased trading volume. Policymakers could enhance futures trading liquidity or restrict speculating positions.

This study examines whether global gold futures returns volatilities and trading activities are threshold cointegrated by using a nonlinear TVECM. The authors detect that some global gold futures returns volatilities and trading activities are threshold cointegrated but some are not. Hence, the findings determine whether the volatility–volume threshold relation holds across countries and investigate the determinants of cross-country differences in different traders.

We examine the informational roles of trades and time between trades in the domestic and overseas US Treasury markets. A vector autoregressive model is employed to assess the information content of trades and time duration between trades. We find significant impacts of trades and time duration between trades on price changes. Larger trade size induces greater price revision and return volatility, and higher trading intensity is associated with a greater price impact of trades, a faster price adjustment to new information and higher volatility. Higher informed trading and lower liquidity contribute to larger bid–ask spreads off the regular daytime trading period.

The purpose of this paper is to examine the linear and nonlinear relations between returns volatility and trading volume for the Indian currency futures market.

To examine the contemporaneous relation between returns volatility and volume, the author uses the generalized method of moment estimator. For the linear causal relation, the author makes use of Granger (1969) bivariate vector autoregression model. The author tests for nonlinear Granger causality between returns volatility and trading volume based on a modified version of the Baek and Brock (1992) nonparametric technique developed by Hiemstra and Jones (1994).

The results indicate a negative contemporaneous relation between returns volatility and trading volume; therefore, the mixture of distribution hypothesis is not supported. The results of both linear and nonlinear Granger causality between futures returns volatility and trading volume indicate a significant bidirectional relation between the two variables lending support to the sequential arrival of information hypothesis. The results are robust to divergence of opinions as proxied by open interest.

The findings of this paper are important for the participants in the market and regulators. The participants in the market require alternatives to diversify their risk. The significant causal relation between returns volatility and trading volume implies that trading volume helps predict the futures prices and should lead to creation of more reliable hedging strategies for investment purposes. Furthermore, it may interest the regulators who need to decide upon the appropriateness of their policies in the currency futures market.

To the best of the author’s knowledge, there is no study that investigates the forecast ability of trading volume to futures returns volatility in an emerging currency futures market. Given that currency futures market is one of the largest markets in the world, and Indian rupee has seen wide fluctuations in the recent years, it seems exciting to explore the price–volume relation in the Indian currency futures market.

Extending the extant literature and using Qatar’s equity market as a case study, this paper aims to look into the potential impacts of foreign investor groups’ trading activities on market volatility in comparison with those of Qatar’s domestic investor counterparts.

The dataset is comprised of daily aggregated values of stock purchases and sales made separately by four investor groups, namely, foreign individual investors, foreign institutional investors, domestic individual investors, and domestic institutional investors. An ex post measure of volatility introduced by Rogers and Satchell (1991) is employed. Four proxies for investor trading are considered separately in the analysis. The objective of the study is empirically addressed in the context of the Generalized Method of Moments estimation technique.

In general, there exists substantial contemporaneous price impact associated with foreign equity investment in the Qatari capital market, despite the fact that foreigners’ buy and sell trades are not as large as those of their domestic counterparts. More specifically, foreign institutional sales (purchases) tend to increase (reduce) market volatility. Like those of foreign institutions, the sell trades by foreign individuals have a positive impact on volatility. On the other hand, domestic institutional purchases are significantly negatively related with market volatility, whereas the sell trades by the same category have no impact on volatility. Finally, surprises in foreigners’ trading volumes turn out to be responsible for adding to volatility.

Although a sudden reversal of foreign capital flows can pose a real threat to the stability of the Qatari capital market, such capital flows are deemed to be an indispensable vehicle for enhancing the liquidity and efficiency of the market. Accordingly, policy makers in Qatar should overhaul the current foreign investment legislation to make it even more streamlined and better suited to achieving the country’s strategic vision for the market. Foremost in these reforms is relaxing the stringent 25 percent foreign ownership restriction. Such a relaxation process is highly recommended to be phased in only gradually, in order to weigh its pros and cons. In this regard, the authorities concerned should consider embarking on a range of procedures intended to ward off the adverse ramifications of foreign capital outflows.

To the author’s best knowledge, no study about the impact of foreign equity flows on domestic markets has been so far conducted using trading data from the Qatari market. This work presents one such attempt.

This study aims to find the relationship of stock market returns and selected financial market variables (market capitalization, earnings per share, price-earnings multiples, dividend yield and trading volume) of Malaysia grounded by the arbitrage pricing theories.

This study empirically examines the effects of selected financial market variables on stock market returns using 64 companies listed in Malaysia's stock market with data spanning from 2005 to 2018. A systematic empirical study based on the Generalized Method of Moments following Arellano and Bond (1991) has been taken to estimate the effect.

The regression result of the financial market variables and stock market return shows that, except for trading volume, all selected financial market variables play significant roles in the stock market returns. Furthermore, market capitalization, earnings per share, price-earnings ratio, dividend yield and trading volume have a positive impact on stock market returns.

The outcome of this study can contribute by helping domestic and global investors devise strategies to minimize their risks. Also, policy administrators can use the outcomes of this study to inform the micro- and macro-level policy formulation.

This study will contribute to filling the gap in knowledge concerning the new release of factors affecting the stock market returns of Malaysia.