The Volume-Price Relationship at the High-Frequency Scale: Evidence From DCC-GARCH

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Stephan Unger

Abstract

This article investigates the time-varying high-frequency price-volume relationship from two perspectives. At the high-frequency time scale, we show that the time varying conditional correlation between price and volume changes exhibits distinct excitational spike regimes that provide a rich set of patterns unexplored before. Impulse response analysis based on a high-frequency Vector-autoregressive specification show that volume has greater impact on price than vice versa. Our results therefore suggests that volume can be seen as a proxy for information flows. Due to market micro-structure contamination, we show that smoothing and pre-averaging is necessary to uncover the high-frequency relationship between price and volume.

Article Details

Section
Articles
Author Biography

Stephan Unger, Saint Anselm College

Department of Business and Economics, Assistant Professor

References

A Christie ‘The Stochastic Behaviour of Common Stock Variances: Value, Leverage and Interest Rate Effects’ (1982) Journal of Financial Economics Vol 10 pp 407-432

A R Gallant, P Rossi and G Tauchen ‘Stock Prices and Volume’ (1992) Review of Financial Studies Vol. 5 Issue 2 pp 199-242

A S Kyle ‘Continuous auctions and insider trading’ (1985) Econometrica: Journal of the Econometric Society pp 1315-1335

C Hiemstra and J Jones ‘Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation’ (1994) Journal of Finance Vol 49 Issue 5 pp 1639-1664

E Basci, S Özyildirim and K Aydogan, ‘A note on price-volume dynamics in an emerging stock market’ (1996) Journal of Banking and Finance Vol 20 Issue 2 pp 389-400

F Black ‘Studies of Stock Price Volatility Changes’ (1976) Proceedings of the 1976 Meetings of the American Statistical Association pp 171-181

H Lütkepohl New Introduction to Multiple Time Series Analysis (Springer, 2006)

I A Moosa and E Al-Loughani ‘Testing the Price-Volume Relation in Emerging Asian Stock Markets’ (1995) Journal of Asian Economics Vol 6 Issue 3 pp 407-422

J Karpoff ‘A Theory of Trading Volume’ (1986) The Journal of Finance Vol 41 Issue 5 pp 1069-1087

J Karpoff ‘The Relation between Price Changes and Trading Volume: A Survey’ (1987) Journal of Financial and Quantitative Analysis Vol 22 Issue 01 pp 109-126

J Tao and J C Green ‘Asymmetries, causality and correlation between FTSE100 spot and futures: A DCC-TGARCH-M analysis’ (2012) International Review of Financial Analysis Vol 24 pp 26-37

K Saatcioglu and L Starks ‘The stock price-volume relationship in emerging stock markets: the case of Latin America’ (1998) International Journal of Forecasting Vol 14 Issue 2 pp 215-225

L Cappiello, R F Engle, and Sheppard K. ‘Asymmetric dynamics in the correlations of global equity and bond returns’ (2006) Journal of Financial econometrics 4 pp 537-572

L Guillermo, R Michaely, G Saar and J Wang ‘Dynamic Volume-Return Relation of Individual Stocks’(2015) Review of Financial Studies Vol 15 Number 4 p 1005

L Zhang, P Mykland and Y Ait-Sahalia ‘A Tale of Two Time Scales: Determining Integrated Volatility With Noisy High-Frequency Data’ (2005) Journal of the American Statistical Association Vol. 100 Issue 472 pp 1394-1411

M Majand and K Yung ‘A GARCH examination of the relationship between volume and price variability in futures markets’ (1991) Journal of Futures Markets Vol 11 Issue 5 pp 613-621

M Smirlock and L Starks ‘An empirical analysis of the stock price-volume relationship’ (1988) Journal of Banking and Finance Vol 12 Issue 1 pp 31-41

N Hautsch and R Huang ‘Limit Order Flow, Market Impact and Optimal Order Sizes: Evidence from NASDAQ TotalView-ITCH Data’ (2012) Market Microstructure: Confronting Many Viewpoints - Conference Proceedings, F Abergel, J P Bouchaud, T Foucault, C Lehal, M Rosenbaum (eds.), Wiley.

N Hautsch N. and R Huang ‘The market impact of a limit order’ (2012) Journal of Economic Dynamics and Control Vol 36 Issue 4 pp 501-522

P B Andreassen ‘Explaining the price-volume relationship: The difference between price changes and changing prices’ (1988) Organizational Behavior and Human Decision Processes Vol 41 Issue 3 pp 371-389

P Hansen, A Lunde ‘Realized variance and market microstructure noise’ (2006) Journal of Business and Economic Statistics Vol 24 Issue 2 pp 127-161

P M Jones and E Olson ‘The time-varying correlation between uncertainty, output, and inflation: Evidence from a DCC-GARCH model’ (2013) Economics Letters Vol 118 Issue 1 pp 33-37

P Silvapulle and J Choi ’Testing for linear and nonlinear Granger causality in the stock price-volume relation: Korean evidence’ (1999) The Quarterly Review of Economics and Finance Vol 39 Issue 1 pp 59-76

R Engle ‘The use of ARCH/GARCH models in applied econometrics’ (2001) The Journal of Economic Perspectives Vol 15 Issue 4 pp 157-168

R Engle ‘Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models’ (2002) Journal of Business & Economic Statistics 20 pp 339-350

R Jennings, L Starks and J Fellingham ‘An equilibrium model of asset trading qith sequential information arrival’ (1981) The Journal of Finance Vol 36 pp 143-161

S Gervais, R Kaniel, D H Mingelgrin ‘The High-Volume Return Premium’ (2001) Journal of Finance Vol 56 Issue 3 pp 877-919

S Thorp and G Milunovich ‘Symmetric versus asymmetric conditional covariance forecasts: Does it pay to switch?’ (2007) Journal of Financial Research Vol 30 Issue 3 pp 355-377

Y Amihud, ‘Illiquidity and stock returns: cross-section and time-series effects’ (2002) Journal of financial markets Vol 5 pp 31-56

Y Ait-Sahalia, F Jianqing, and L Yingying ‘The Leverage Effect Puzzle: Disentangling Sources of Bias at High Frequency’ (2013) Journal of Financial Economics Vol 109 Issue 1 pp 224-249

Y Ait-Sahalia, P Mykland and L Zhang ‘How often to sample a continous-time process in the presence of market microstructure noise’ (2005) Review of Financial Studies Vol 18 Issue 2 pp 351-416