Trading volume and exchange rate volatility: Evidence for the sequential arrival of information hypothesis

Mougoué, Mbodja; Aggarwal, Raj

doi:10.1016/j.jbankfin.2011.02.028

Cited by 60 publications

(68 citation statements)

References 87 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Their results indicated the presence of bidirectional nonlinear Granger causality between aggregate daily stock prices and trading volume. These findings were confirmed by Mougoué and Aggarwal (2011) in foreign exchange markets. Puri and Philippatos (2008) showed that volume and returns on LIFFE interest rates and currency futures exhibit an asymmetrical relationship.…”

Section: Introductionsupporting

confidence: 60%

“…However, as for the MDH, conclusions regarding the SIH are also relatively heterogeneous. Indeed, while Lee and Rui (2000) showed that volume does not Granger-cause stock returns, Mougoué and Aggarwal (2011) recently documented significant lead-lag relations between trading volume and return volatility using nonlinear causality tests. This finding was also confirmed by Chen et al (2001) and Louhichi (2012).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Intraday jumps and trading volume: a nonlinear Tobit specification

Jawadi

Louhichi

Cheffou

et al. 2015

Rev Quant Finan Acc

View full text Add to dashboard Cite

This paper investigates the relationship between trading volume and volatility for four international stock markets (US: S&P500, UK: FTSE100, France: CAC40 and Germany: DAX30) in a context of global financial crisis. Unlike previous related studies, we use intraday data and apply a nonlinear econometric model to assess this relationship. In particular, we first break down intraday realized volatility into its continuous and jump components using the non-parametric approach developed by Barndorff-Nielsen and Shephard (J Financ Econom 4:1-30, 2006). Second, we investigate the volume-volatility relationship and test whether it varies according to volatility components (jumps and continuous component). While Giot et al. (J Empir Finance 17:168-175, 2010), among others, investigated the volume-volatility relationship in a linear context, our study contributes by estimating different nonlinear specifications (threshold model, nonlinear Tobit model) that enable us to capture further asymmetry and time-variation to better apprehend the effect of trading volume on realized volatility. Accordingly, our study yields two interesting findings. On the one hand, as expected there is a significant and positive relationship between trading volume and realized volatility, as well as with its components, confirming the importance of trading volume as a key to characterizing volatility. On the other hand, we show that this relationship exhibits asymmetry and nonlinearity, and that threshold models are more appropriate than linear model to characterize the volume volatility relationship.

show abstract

Section: Introductionsupporting

confidence: 60%

Section: Introductionmentioning

confidence: 99%

Intraday jumps and trading volume: a nonlinear Tobit specification

Jawadi

Louhichi

Cheffou

et al. 2015

Rev Quant Finan Acc

View full text Add to dashboard Cite

show abstract

“…It is evident from Table 5 The relation between futures return volatility and volume of trading is extensively investigated in the research that tests for the mixture of distribution hypothesis (MDH) and the sequential arrival of information (SAI) hypothesis (Mougoué and Aggarwal, 2011). Volume of trading (open interest) can be used to measure speculative (hedging) demand in the futures market (Lucia and Pardo, 2010) and to measure futures-trading activity (Bessembinder and Seguin, 1992).…”

Section: Futures Volume and Open Interest Spilloversmentioning

confidence: 99%

“…Trading volume measures speculative demand for futures (Lucia and Pardo, 2010). Further, open interest is an important variable and is regarded as a proxy for dispersion of beliefs (Bessembinder et al, 1996;Mougoué and Aggarwal, 2011); it is an important determinant of volume (Mougoué and Aggarwal, 2011). Open interest is the total number of futures contracts which have not been closed out (i.e.…”

mentioning

confidence: 99%

“…For example, the causal relationship between futures volatility and trading volume reported in this study implies that knowledge of current trading volume improves the ability to forecast futures prices. This may lead to the construction of more accurate hedge ratios and improvements in investment strategies (Mougoué and Aggarwal, 2011). This is not the case for open interest, which means that the flow of money into the futures market is not so important, as it is the trading volume which measures the pressure or intensity behind a price up or down trend (Sari et al, 2012).…”

mentioning

confidence: 99%

See 1 more Smart Citation

Dynamic spillover effects in futures markets: UK and US evidence

Antonakakis

Floros

Kizys

2016

International Review of Financial Analysis

View full text Add to dashboard Cite

Previous studies on spillover effects in future markets have so far confined themselves to static analyses. In this study, we use a newly introduced spillover index to examine dynamic spillovers between spot and futures market volatility, volume of futures trading and open interest in the UK and the US. Based on a dataset over the period February 25, 2008 to March 14, 2013, that encompasses both the global financial crisis and the Eurozone debt crisis, we find that spot and futures volatilities in the UK (US) are net receivers (net transmitters) of shocks to volume of futures trading and open interest. The analysis also sheds light on the dynamic interdependence of spot and futures market volatilities between the US and the UK. Specifically, the spot and futures volatility spillovers between the UK and US markets are of bidirectional nature, however, they are affected by major economic events such as the global financial and Eurozone debt crisis. Several robustness checks endorse our main findings. Overall, these results have important implications for various market participants and financial sector regulators.

show abstract

Does volume really matter? A risk management perspective using cross‐country evidence

Patra¹,

Bhattacharyya

2019

Int. J Fin Econ

View full text Add to dashboard Cite

This paper examines the impact of volume on conditional volatility and value at risk (VaR) in the context of mixture of distribution hypothesis (MDH). We test whether the support for or against the hypothesis is unconditional and holds true universally irrespective of the time period under study, the stock market under study, and the distributional assumptions so made on the residuals of the returns. We find that the persistence in volatility shows negligible reduction in all the indices across subperiods, thus refuting the claims of the MDH: that volume can explain the heteroscedasticity of returns. However, we do find that volume can act as a proxy for information post the sub‐prime financial crisis, and it does impact VaR as the estimates improve significantly for some of these indices, which exhibit a strong correlation between volume and volatility.

show abstract

Trading volume and exchange rate volatility: Evidence for the sequential arrival of information hypothesis

Cited by 60 publications

References 87 publications

Intraday jumps and trading volume: a nonlinear Tobit specification

Intraday jumps and trading volume: a nonlinear Tobit specification

Dynamic spillover effects in futures markets: UK and US evidence

Does volume really matter? A risk management perspective using cross‐country evidence

Contact Info

Product

Resources

About