Abstract
We consider the null distribution of empirical autocorrelation coefficients of stationary time series under nonstandard circumstances. We show that this null distribution is not robust to ARCH-effects and to non-existing variances, both of which are typical for common stock returns. These results are then applied to several stocks traded on the Frankfurt stock exchange, with the result that the ”significance” of empirical autocorrelations is in general reduced.
We are grateful to “Deutsche Finanzdatenbank” (DFDB), in particular to Torsten Lüdeke, for the data used in this report, to an unknown referee for helpful insights and comments, to Victor Ng for providing us with his EZARCH software for the estimation of ARCH-models, and to “Deutsche Forschungsgemeinschaft” (DFG) for additional support.
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References
Akgiray V (1989) Conditional Heteroskedasticity in Time Series of Stock Returns: Evidence and Forecasts, Journal of Business 62, 54–80
Arad R W (1980) Parameter Estimation for Symmetric Stable Distributions, Interna-tional Economic Review 21, 209–220
Bollerslev T, Chou R Y and Kroner K P (1992) ARCH Modelling in Finance: A Reviewof the Theory and Empirical Evidence, Journal of Econometrics 52, 5–59
Brown B N (1971) Martingale Central Limit Theorems, Annals of Mathematical Statistics42, 59–66
Davis R and Resnick S (1986) Limit Theory for Moving Averages of Random Variableswith Regularly Varying Tail ProbabilitiesThe Annals of Statistics 14, 533–558
de Vries C G (1991) On the Relation between GARCH and Stable Processes, Journal of Econometrics 48, 313–324
Engle R F and Bollerslev T (1986) Modelling the Persistence of Conditional Variances, Econometric Reviews 5, 1–50
Fama E (1965) The Behaviour of Stock Market Prices, Journal of Business 36, 394–419
Funke G (1992) The Message in Daily German Stock Returns: Empirical Evidence Using GARCH, Paper given at ESEM 1992, Brussels
Heyde C C (1981) Invariance Principles in Statistics, International Statistical Review 49, 143–152
Krämer W and Runde R (1990) Die Autokorrelation von Aktienkursen, Forschungsbericht Nr. 90/10, Department of Statistics, University of Dortmund
Krämer W and Runde R (1991) Testing for Autocorrelation among Common Stock Returns, Statistical Papers 32, 311–320
Mandelbrot B (1963) The Variation of Certain Speculative Prices, Journal of Business 36, 394–419
Milhoj A (1985) The Moment Structure of ARCH Processes, Scandinavian Journal of Statistics 12, 281–292
Schlag C (1991) Return Variances of Selected German Stocks: An Application of ARCH and GARCH Processes, Statistical Papers 32, 353–361
Takayama A (1985) Mathematical Economics (2nd ed.), Cambridge (Cambridge University Press)
Taylor S (1986) Modelling Financial Times Series, New York (Wiley)
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© 1994 Physica-Verlag Heidelberg
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Krämer, W., Runde, R. (1994). Some Pitfalls in Using Empirical Autocorrelations to Test for Zero Correlation among Common Stock Returns. In: Kaehler, J., Kugler, P. (eds) Econometric Analysis of Financial Markets. Studies in Empirical Economics. Physica-Verlag HD. https://doi.org/10.1007/978-3-642-48666-1_1
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DOI: https://doi.org/10.1007/978-3-642-48666-1_1
Publisher Name: Physica-Verlag HD
Print ISBN: 978-3-642-48668-5
Online ISBN: 978-3-642-48666-1
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