Volatility and trading activity in Short Sterling futures

The objective of the present study is to examine the interplay between information, trading volume and volatility in Short Sterling futures. More specifically, the paper concentrates on the role of liquidity variables as conduits of information arrival and whether such variables could be an exclusive platform of the market's information set. The analytical framework employed to examine the interaction among those factors is based on the conditional volatility family of techniques. The approach is well suited as it naturally leads to examine the interaction among volatility and sources of information. In an attempt to identify proxies of information and their role in determining volatility, four main conclusions have emerged. First, the empirical findings suggest that both volume and open interest exhibit a positive correlation with volatility. Second, based on the current methodology, one can observe the persistence and importance of GARCH effects after accounting for liquidity. Third, the liquidity variables remain significantly exogenous compared with other studies. Finally, although both liquidity variables are found significant, their role as vehicles of transmitting information is proved to be weak with respect to the information itself.

[1]  Avanidhar Subrahmanyam,et al.  Market Liquidity and Trading Activity , 2000 .

[2]  Peter E. Rossi,et al.  Stock Prices and Volume , 1992 .

[3]  H. Bessembinder,et al.  Price Volatility, Trading Volume, and Market Depth: Evidence from Futures Markets , 1993, Journal of Financial and Quantitative Analysis.

[4]  Futures Price Variability: A Test of Maturity and Volume Effects , 1986 .

[5]  Neil D. Pearson,et al.  Differential Interpretation of Public Signals and Trade in Speculative Markets , 1995, Journal of Political Economy.

[6]  Maureen O'Hara,et al.  Market Statistics and Technical Analysis: The Role of Volume , 1994 .

[7]  M. Mougoué,et al.  Linear dependence, nonlinear dependence and petroleum futures market efficiency , 1997 .

[8]  L. Harris Cross-Security Tests of the Mixture of Distributions Hypothesis , 1986, Journal of Financial and Quantitative Analysis.

[9]  Hung-Gay Fung,et al.  Volatility, global information, and market conditions: a study in futures markets , 2001 .

[10]  P. Clark A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices , 1973 .

[11]  George Tauchen,et al.  THE PRICE VARIABILITY-VOLUME RELATIONSHIP ON SPECULATIVE MARKETS , 1983 .

[12]  Michael L. Smirlock,et al.  A FURTHER EXAMINATION OF STOCK PRICE CHANGES AND TRANSACTION VOLUME , 1985 .

[13]  Mohammad Majand,et al.  A GARCH examination of the relationship between volume and price variability in futures markets , 1991 .

[14]  Benoit B. Mandelbrot,et al.  A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices: Comment , 1973 .

[15]  Jonathan M. Karpoff The Relation between Price Changes and Trading Volume: A Survey , 1987, Journal of Financial and Quantitative Analysis.

[16]  G. Geoffrey Booth,et al.  Conditional Dependence in Precious Metal Prices , 1991 .

[17]  Lawrence Harris,et al.  Transaction Data Tests of the Mixture of Distributions Hypothesis , 1987, Journal of Financial and Quantitative Analysis.

[18]  Mbodja Mougoué,et al.  Heteroscedasticity in stock market indicator return data: volume versus GARCH effects , 1996 .

[19]  A. Kyle Continuous Auctions and Insider Trading , 1985 .

[20]  M. Richardson,et al.  A Direct Test of the Mixture of Distributions Hypothesis: Measuring the Daily Flow of Information , 1994, Journal of Financial and Quantitative Analysis.

[21]  T. W. Epps,et al.  The Stochastic Dependence of Security Price Changes and Transaction Volumes: Implications for the Mixture-of-Distributions Hypothesis , 1976 .

[22]  A. I. McLeod,et al.  DIAGNOSTIC CHECKING ARMA TIME SERIES MODELS USING SQUARED‐RESIDUAL AUTOCORRELATIONS , 1983 .

[23]  Rex Thompson,et al.  A test of dividend irrelevance using volume reactions to a change in dividend policy , 1986 .

[24]  The relationship between volume and price variability in futures markets , 2000 .

[25]  J. Wooldridge,et al.  A Capital Asset Pricing Model with Time-Varying Covariances , 1988, Journal of Political Economy.

[26]  Richard J. Rogalski,et al.  The Dependence of Prices and Volume , 1978 .

[27]  Jonathan M. Karpoff A Theory of Trading Volume , 1986 .

[28]  Bronwyn H Hall,et al.  Estimation and Inference in Nonlinear Structural Models , 1974 .

[29]  J. Ord,et al.  An Investigation of Transactions Data for NYSE Stocks , 1985 .

[30]  Jiang Wang,et al.  A Model of Competitive Stock Trading Volume , 1994, Journal of Political Economy.

[31]  Christopher G. Lamoureux,et al.  Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects , 1990 .

[32]  Russell P. Robins,et al.  Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model , 1987 .

[33]  R. Crouch The Volume of Transactions And Price Changes on The New York Stock Exchange , 1970 .

[34]  Thomas E. Copeland,et al.  A Model of Asset Trading under the Assumption of Sequential Information Arrival , 1976 .

[35]  Andrew Harvey,et al.  Forecasting, Structural Time Series Models and the Kalman Filter , 1990 .