Relationship between Stock Returns and Trading Volume at the Bourse Régionale des Valeurs Mobilières, West Africa

Abstract

The objective of this paper is to study the contemporaneous relationship and the dynamic relationship between the stock index return and the trading volume on the Bourse Régionale des Valeurs Mobilières using daily data from 5 January 2015 to 31 October 2022. Estimations are made using the generalized method of moments (GMM) and generalized autoregressive conditional heteroscedasticity or GARCH (1,1) specifications for the contemporaneous regressions and the vector autoregressive specification for the dynamic (causal) relationship. The contemporaneous specifications show that there is no significant relationship between stock returns and trading volume. Neither of the two variables significantly influences the other. Furthermore, the dynamic specification shows a causality running from stock returns to trading volume but the reverse is not true. For the period covered by the study, the results invalidate both the mixture of distribution hypothesis and the sequential information arrival hypothesis and open the way for other considerations such as behavioral models.

Exploring the relation between realised volatility and Trading volume: Evidence from international stock market

“…These findings extents the proposition put forth by Enow (2022) who contends that the volatility between stock market prices are independent of each other. Considering that some authors (Gueyie, Mouhamadou & Mamadou, 2022;Alhussayen, 2022;Chiang, Qiao & Wong, 2009) also found an insignificant bi-directional relationship between RV and VOL, it can be suggested that the relationship between RV and VOL is not static but dynamic in nature. The table below highlights the forecast proportions for each variable.…”

“…The results of this study reveal that there is no meaningful relationship between RV and VOL; hence, they cannot be used as estimators to predict one another. Contrary to the study of Chiang, Qiao & Wong (2009) and in line with the study of Gueyie, Mouhamadou & Mamadou (2022); Alhussayen (2022), sequential information theory and mixed distribution theory are irrelevant, at least in the current dispensation. The findings of this study suggest that new information entering financial markets tends to be disseminated faster to active market participants, probably due to regional and global integration.…”

“…Modelling the relationship between realised volatility and trading volume encapsulates a major part of price formation due to the volume of information flow in financial markets (O'Hara, 2015). This idea is postulated by the sequential information flow hypothesis which contends that new information is transmitted systematically to market participants trading in financial markets (Gueyie, Mouhamadou & Mamadou, 2022). In essence, new information reaches security traders at varying times giving rise to information asymmetry (An, Huang & Li, 2022).…”

Understanding price-volume dynamics: An analysis of healthcare and consumer durables sectors of nifty 50 index

“…These findings suggest that the JSE exhibits characteristics of mature stock markets, potentially attracting foreign investors. Gueyie, Diallo, and Diallo (2022) [11] assessed the relationship between trading volume and stock returns in the West African stock market at the Bourse Régionale des Valeurs Mobilières (BRVM) from 2015 to 2022. Their study investigated whether there was a causal relationship between trading volume and stock returns, and if so, the direction of this relationship.…”

Exploring the Relation between Realised Volatility and Trading Volume: Evidence from International Stock Market

“…Modelling the relationship between realised volatility (RV) and trading volume (VOL) encapsulates a major part of price formation due to the volume of information flow in financial markets (O'hara, 2015). This idea is postulated by the sequential information flow hypothesis which contends that new information is transmitted systematically to market participants (Gueyie et al, 2022). In essence, new information reaches security traders at varying times giving rise to information asymmetry (An et al, 2022).…”