Volume-return Relationship Research Articles

Expected return, volume, and mispricing: Evidence from China

We investigate the relation between trading volume and future stock returns across stocks with different levels of mispricing in the Chinese equity market. We first show a negative relation between trading volume and future stock returns. When replicating the main results reported in Han, Huang, Huang and Zhou (2022), we find no evidence of the volume amplification effect in Chinese equities. There is no strong evidence that mispricing plays a role in explaining the volume-return relation. Overall, the results from China suggest that the mechanism in the volume-return relation is somewhat different when compared to those documented in Han et al. (2022).

Volume and stock returns in the Chinese market

We propose and empirically investigate hypotheses regarding the volume-return relationship in the Chinese stock market, taking into account the impact of prevalent noise trading and short-selling restrictions. Our findings reveal a negative correlation between trading volume and returns specifically among overvalued stocks. However, no significant correlation is observed for undervalued stocks, nor is there a consistent volume amplification effect. In contrast to our findings, Han, Huang, Huang, and Zhou (2021) also reported a positive correlation between expected return and trading volume for undervalued stocks, and they highlighted the amplified impact of trading volume in the US market. Furthermore, we observe that stricter short-selling restrictions in the Chinese market for overvalued stocks result in a larger deviation from fundamental value as the trading volume increases accompanied by greater disagreement among noise investors. These findings suggest that comprehending market disparities necessitates considering noise trading and short-selling restrictions as crucial factors.

Effect of crypto-asset market-specific technological development on the asymmetric volume-return relationship in the presence of cross-sectional dependence and heterogeneity

Effect of crypto-asset market-specific technological development on the asymmetric volume-return relationship in the presence of cross-sectional dependence and heterogeneity

The Arrival of Information and Price Adjustment Across Extreme Quantiles: Global Evidence

This study investigates the impact of information arrival on prices for 21 major global market indices for the period 1998–2018, employing quantile regression methodology. The results show that there is a contemporaneous and causal effect of volume on returns. This return-volume relation is a manifestation of systematic market-wide information that is released in an autocorrelated manner to market participants. This information is absorbed by the market participants over short horizons, within a day. This leads to uniform expectations and, in turn, lower volatility levels. The effect of volume on return is heterogeneous across the conditional quantiles, reflecting the contrasting patterns in the transmission of positive and negative news. This evidence is more pronounced when the intensity of information arrival is high (the tails of return distribution), which is consistent with the mixture of distribution hypothesis and information asymmetry hypothesis.

Bubbles and Trading Frenzies: Evidence from the Art Market

The art market is subject to booms and busts in both prices and volume, which are difficult to reconcile with models where agents trade to consume. This paper shows that: (i) a high trading volume coincides with higher prices and more speculative trades, (ii) a high volume predicts negative returns, especially in the most volatile art schools, (iii) a substantial increase in transaction costs decreases art prices and can destroy the return-volume relation, and (iv) short-term transactions underperform and are riskier than long-term transactions. The evidence is consistent with a resale option model of speculative trading where the impossibility to sell short embeds a bubble component in prices. This paper suggests that speculative trading can generate significant price bubbles, even when trading costs are huge.

A Comparative Analysis on the Volume-Return Relationship of the ETF and Stock Market

This paper aims to examine the contemporaneous relationship between trading volume and returns in the ETF market taking the stock market as a contrast. While past research using correlation analysis and OLS method to specify a linear regression model only catches the average relationship between volume and return, this paper applies the quantile regression analysis to provide a more complete description for the volume-return relationship in the ETF and stock markets. The empirical results show that a symmetric volume-return relationship is found in the ETF market and an asymmetric volume-relationship, however, is discovered in the stock market. The volume-return relationship of the stock market has become more symmetric after the exempt for some stock from the short-sale restriction. The results demonstrate that the transaction cost and the short-sale restriction are important factors to influence the patter of volume-return relationship.

The asymmetric price-volume relation revisited: evidence from Qatar

PurposeThis 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.Design/methodology/approachThe 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).FindingsThe 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.Practical implicationsThe 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.Originality/valueBased 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.

Contemporaneous and asymmetric volume-return relationship: cross-product evidence from an emerging market

This paper demonstrates that both Taiwan’s exchange-traded funds (ETFs) and equities exhibit an asymmetric volume-return relationship in which the ETF display a mixed, negative or positive, asymmetry and the equity exhibits primarily a positive asymmetry. The positive asymmetry in equities and its decline with the progressive elimination of the short-sale restriction on equities support the costly short-sale hypothesis, which considers a costly short-sale restriction or asymmetric transaction costs on long and short trading to be the source of the asymmetry. The part of a less positive asymmetry in ETFs also consists with what the costly short-sale hypothesis predicts. The later information models that consider asymmetrically-informed traders or the heterogeneity of traders to be the source of the asymmetry explain the negative asymmetry in ETFs and the upward trend in the magnitude of volume-return correlation with the grow of volume quintiles. An important conclusion is that not a single hypothesis can be a universal explanation for the asymmetric volume-return relationship. Which hypothesis may explain the volume-return asymmetry depends largely on whether the short-sale restriction is present

Hedging or Speculation: What Can We Learn from the Volume-Return Relationship?

ABSTRACTWe investigate the volume-return relationship using data from the Chinese stock market. Drawing on a recent theoretical model on the volume-return relationship, we test empirically whether investors in China are hedging oriented or motivated by speculation. A two-state Markov-switching model is used to augment the basic model. Allowing the underlying model to switch between two regimes reveals further information that investors’ motivation in the Chinese stock market is sensitive to the general market conditions.

A Comparative Analysis on the Volume-Return Relationship of the Exchange-Traded Fund and the Stock Market

This article aims to examine the contemporaneous relationship between trading volume and returns in the Taiwan exchange-traded fund (ETF) market, taking the stock market as a contrast. Whereas past research using correlation analysis and ordinary least squares method to specify a linear regression model catches only the average relationship between volume and return, this article applies the quantile regression analysis to provide a more complete description for the volume-return relationship in the ETF and stock markets. The empirical results show a symmetric volume-return relationship in the ETF market and an asymmetric volume-relationship in the stock market when the short-sale uptick rule is still applicable for all listed stocks. The volume-return relationship of the stock market became more symmetric after the elimination of the uptick rule on short sales for high-cap stocks and, at last, for the entire listed stocks. The results demonstrate that transaction costs and the short-sale restriction are important factors in influencing the pattern of the volume-return relationship.

A Comparative Analysis on the Volume-Return Relationship of the Exchange-Traded Fund and Stock Market

A Comparative Analysis on the Volume-Return Relationship of the Exchange-Traded Fund and Stock Market

A Comparative Analysis on the Volume-Return Relationship of the ETF and Stock Market

This paper aims to examine the contemporaneous relationship between trading volume and returns in the Taiwan exchange-traded fund (ETF) market taking the stock market as a contrast. While past research using correlation analysis and ordinary least squares method to specify a linear regression model only catches the average relationship between volume and return, this paper applies the quantile regression analysis to provide a more complete description for the volume-return relationship in the ETF and stock markets. The empirical results show that a symmetric volume-return relationship is found in the ETF market and an asymmetric volume-relationship, however, is discovered in the stock market. The volume-return relationship of the stock market has become more symmetric after the exempt for some stocks from the short-sale restriction. The results demonstrate that the transaction cost and the short-sale restriction are important factors to influence the patter of volume-return relationship.

The Information Content of Stock Market Flows: Evidence from Thailand

This paper studies the impact of Thai stock market (SET) by examining the return-volume relation and the weekly volatility-volume relation, started 2003–2014. The results show that there is a positive relation in return-volume relation; although, there is a negative relation of volatility-volume. In addition, we differentiate the impact of fund inflow and outflow for each individual groups, including foreign, local and institution investors for finding the relations between fund flow and market return, between fund flow and market volatility. The analysis shows that only foreign investor impacts to stock market in both of trading-return relation and trading-volatility relation. There is a positive relation with market return, but has a negative relation with market volatility. However, it depends on direction of fund flow. Fund inflow has positive relation in market return while outflow has negatively. On the other hand, in part of trading-market volatility, the larger of cash outflow, the more volatility is the market.

Factor instrumental variable quantile regression

AbstractThis paper proposes a factor instrumental variable quantile regression (FIVQR) estimator and studies its asymptotic properties. The proposed estimators share with quantile regression the advantage of exploring the shape of the conditional distribution of the dependent variable. When there are a factor structure and co-movement for economic variables, the underlying unobservable factors (or common components) are more efficient instruments. The proposed estimators achieve the optimality in the following sense: The method of principal component consistently estimates the space spanned by the ideal instruments which are utilized to control the endogeneity in the quantile regression analysis. Analyzing the asymptotic properties of the estimator, we assume that a panel of observable instruments follows a factor structure and the endogenous variables also share the same unobservable factors. Using the estimated factors as instruments, we show that the FIVQR estimator is consistent and asymptotically normal. Furthermore, when compared in the GMM framework, the proposed estimator is more efficient than the GMM estimator using many observable instruments directly. Monte Carlo studies demonstrate that the proposed estimators perform well. For an empirical application, we use a firm-level panel data set consisting of trading volumes and returns on DJIA to explore the asymmetric return–volume relation, controlling the endogeneity problem with the estimated factor instruments.

Hedging or Speculation, What Can We Learn from the Volume-Return Relationship?

This study investigates the volume-return relationship using data from the Chinese stock market. Based on the model set up by Llorente et al. (2002), we test empirically whether investors in China are hedging oriented or motivated by speculation. A two-state Markov switching model was used to augment the basic model. Allowing the underlying model to switch between two regimes reveals further information that investors' motivation in the Chinese stock market is sensitive to the general market conditions.

“Does It Take Volume to Move the EUR/PLN FX Rates?” Evidence from Quantile Regressions

This study investigates the impact of trading volume on selected quantiles of the EUR/PLN return distribution. Empirical results obtained with the quantile regression approach confirm that an increase in the turnover is associated with a significant increase in the dispersion of the corresponding return distribution. We divided the trading volume into its expected (antici-pated) and unexpected (unanticipated) component and found that the unexpected volume shocks have a significantly larger impact on the dispersion of the return distribution. We also observed that the volume-return relationship is nonlinear; the dependence is stronger with more extreme quantiles. Moreover, after accounting for a conditional volatility measure as a controlling explan-atory factor for the quantile dynamics, the impact of the expected volume declines yet remains significant especially for the most extreme quantiles.

Price variation and volume dynamics of securitized timberlands

An increasing amount of timberlands have been securitized and made available to investors in the form of Master Limited Partnerships (MLPs) or Real Estate Investment Trusts (REITs). In this study, Generalized Autoregressive Conditional Heteroscedasticity (GARCH) and extreme value models were utilized to examine price variation and volume dynamics of six firms that have specialized in timberland investment. Total standing shares and average daily turnover rates for the MLPs were smaller than those for the timber REITs. Both the GARCH and extreme value models revealed a positive return–volume relation, which provided a strong empirical support for the mixture-of-distribution hypothesis. During extreme market movements, the MLPs had stronger and more stable return–volume relations than the timber REITs. Asymmetric return–volume relation was identified for the MLPs, while the relation was fairly symmetric for the timber REITs.

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

ABSTRACTThis 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.

Revisiting the empirical linkages between stock returns and trading volume

This paper investigates whether the empirical linkages between stock returns and trading volume differ over the fluctuations of stock markets, i.e., whether the return–volume relation is asymmetric in bull and bear stock markets. Using monthly data for the S&P 500 price index and trading volume from 1973M2 to 2008M10, strong evidence of asymmetry in contemporaneous correlation is found. As for a dynamic (causal) relation, it is found that the stock return is capable of predicting trading volume in both bear and bull markets. However, the evidence for trade volume predicting returns is weaker.

A Dynamic Volume-Return Relation and Investors' Positive Feedback Trading

With individual stocks, a larger increase in trading volume indicates a stronger short-term return persistence. A reason for this short-horizon ‘volume–return relation’ is that it can signal the existence of fundamental news, which can be gradually incorporated into stock price. In this study, we present another plausible explanation by considering investors' short-term positive feedback trading. First, through empirical analysis, we show that the volume–return relation remains strong among stocks for which there is little fundamental news. Through a model-based analysis, we demonstrate that positive feedback trading can cause this relation even when there is no news. Our findings raise the possibility that the short-horizon volume–return relation is also caused by short-term positive feedback trading.