Information Flow Dependence in Return and Trading Volume Across Different Stocks

2019 ◽  
Author(s):  
Markus Michaelsen
2014 ◽  
Vol 31 (4) ◽  
pp. 426-438 ◽  
Author(s):  
Saada Abba Abdullahi ◽  
Reza Kouhy ◽  
Zahid Muhammad

Purpose – The purpose of this paper is to examine the relationship between trading volume and returns in the West Texas Intermediate (WTI) and Brent crude oil futures markets. In so doing, the paper addresses two important issues. First, whether there is a positive relationship between returns and trading volume in the crude oil futures markets. Second, whether information regarding trading volume contributes to forecasting the magnitude of return in the markets, an important issue because the ability of trading volume to predict returns imply market inefficiency. Design/methodology/approach – The paper used daily closing futures price and their corresponding trading volumes for WTI and Brent crude oil markets during the sample period January 2008 to May 2011. Both the log volume and the unexpected component of the detrended volume are used in the analysis in other to have robust alternative conclusion. The generalized method of moments (GMM) approach is used to examine the contemporaneous relationship between returns and trading volume while the Granger causality approach, impulse response and variance decomposition analysis are used to investigate the ability of trading volume to predict returns in the oil futures markets. Findings – The results reject the postulation of a positive relationship between trading volume and returns, suggesting that trading volume and returns are not driven by the same information flow which contradicts the mixture of distribution hypothesis in all markets. The results also show that neither trading volume nor returns have the power to predict the other and therefore contradicting the sequential arrival hypothesis and noise trader model in all markets. Finally, the findings support the weak form efficient market hypothesis in the crude oil futures markets. Originality/value – The findings has important implications to market regulators because daily price movement and trading volume do not respond to the same information flow and therefore the measures that control price volatility should not focused more on volume; otherwise they may not provide fruitful outcomes. Additionally, traders and investors who participate in oil futures should not base their decisions on past trading volume because it will lead to profit loss. The results also have implications for market efficiency as past information cannot assist speculators to forecast returns in all the oil markets. Finally, investors can benefit from portfolio diversification across the two markets.


2011 ◽  
Vol 27 (3) ◽  
pp. 55
Author(s):  
Alexis Cellier ◽  
Waël Louhichi

<span>This paper aims to study the relationship between public information arrival and Euronext Paris intraday activity. The information flow is measured as the number of news items recorded by Reuters and conditional volatility is modeled by an EGARCH process. Our results reveal a strong positive relationship between public information flow and trading volume and a moderate positive relation between stock returns volatility and the information flow. These results are available for the CAC40 Index as well as for individual stocks and are robust even after controlling for the impact of the intraday patterns.</span>


Author(s):  
Megan Y. Sun

<p class="normal15" style="line-height: normal; text-indent: 0in; margin: 0in 0.5in 0pt;"><span style="font-family: &quot;Times New Roman&quot;,&quot;serif&quot;; font-size: 10pt;">This paper constructs a theoretical mixture of distributions model to describe the impacts of permanent fundamental, transitory fundamental, and non-fundamental shocks on returns, volatility and volume.<span style="mso-spacerun: yes;">&nbsp; </span>Under the assumption that informed traders share homogenous fundamental information, we find that only contemporaneous noise trading contributes to the generation of trading volume.<span style="mso-spacerun: yes;">&nbsp; </span>This theoretical model provides us with three identifying restrictions that can be readily imposed on a trivariate SVAR model to empirically estimate the impacts of the three shocks on returns, volatility, and volume.<span style="mso-spacerun: yes;">&nbsp; </span>Using this model, we find that Microsoft stock prices are not very sensitive to noise trading. </span></p>


2020 ◽  
Vol 23 (05) ◽  
pp. 2050029
Author(s):  
MARKUS MICHAELSEN

In response to empirical evidence, we propose a continuous-time model for multivariate asset returns with a two-layered dependence structure. The price process is subject to multivariate information arrivals driving the market activity modeled by nondecreasing pure-jump Lévy processes. A Lévy copula determines the jump dependence and allows for a generic multivariate information flow with a flexible structure. Conditional on the information flow, asset returns are jointly normal. Within this setup, we provide an estimation framework based on maximum simulated likelihood. We apply novel multivariate models to equity data and obtain estimates which meet an economic intuition with respect to the two-layered dependence structure.


2014 ◽  
Vol 49 (1) ◽  
pp. 33-49 ◽  
Author(s):  
Xiaojun He ◽  
Raja Velu

AbstractThis paper develops a multi-asset mixture distribution hypothesis model to investigate commonality in stock returns and trading volume. The model makes two main predictions: First, the factor structures of returns and trading volume are independent although they stem from the same valuation fundamentals and jointly depend on a latent information flow; second, cross-sectional positive volatility-volume relations arise solely from the dynamic features of the information flow. Empirical analyses at the market level support these predictions. Furthermore, the results indicate that removing the information flow significantly reduces the return volatility persistence and the extent of the reduction exhibits a size pattern.


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