Abstract
Analyzing a financial time series it is of great interest to monitor changes in its structure. In this paper it is shown how control charts can be used to detect such positions. Several control schemes for GARCH processes are introduced and compared with each other. Furthermore these methods are applied to stock market returns.
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References
Alwan, L. C. and Roberts, H. V. (1988): Time-series modeling for statistical process control. Journal of Business and Economic Statistics, 6(1), 87–95.
Bollerslev, T. (1986): Generalized autoregressive conditional heteroscedasticity. Journal of Econometrics, 31, 307–327.
Brockwell, P. J. and Davis, R. A. (1991): Time Series: Theory and Methods. Springer, New York.
Cox, D. R., Hinkley, D. V. and Bamdorff-Nielsen, O. E. (1996): Time Series Models. Chapman & Hall.
Engle, R. F. (1982): Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007.
Engle, R. F. and Rothschild M. (1992): ARCH Models in Finance. Journal of Econometrics, 52.
Harris, T. J. and Ross, W. H. (1991): Statistical process control procedures for correlated observations. Canadian Journal of Chemical Engineering, 69, 48–57.
Kramer (1997):On Control Charts for Time Series. Dissertation, Universität Ulm, Germany.
Ljung, G. M. and Box, G. E. P. (1978): On a measure of lack of fit in time series models. Biometrika, 65(2), 297–303.
McLeod, A. I. and Li, W. K. (1983): Diagnostic checking ARMA time series models using squared-residual autocorrelations. Journal of Time Series Analysis, 4, 269–273.
Milhøj, A. (1985): The moment structure of ARCH processes. Scand. J. Statist., 12, 281–292.
Montgomery, D. C. and Mastrangelo, C. M. (1991): Some statistical process control methods for autocorrelated data. Journal of Quality Technology, 23(3), 179–204.
Pagan, A. (1996): The econometrics of financial markets. Journal of Empirical Finance, 3, 15–102.
Page, E.S. (1954): Continuous inspection schemes. Biometrika, 41, 100–114.
Roberts, S. W. (1959): Control chart test based on geometric moving averages. Technometrics, 1(3), 239–250.
Schmid, W. (1995): On the run length of a Shewhart chart for correlated data. Statistical Papers, 36, 111–130.
Schmid, W. (1997a): On EWMA charts for time series. Frontiers in Statistical Quality Control. Lenz, H.-J. and Wilrich, P.-Th. (eds.), Physica Verlag, Heidelberg.
Schmid, W. (1997b): CUSUM control schemes for Gaussian processes. Statistical Papers, 38(2), 191–217.
Severin, T. and Schmid, W. (1996): Monitoring changes in GARCH models. Technical Report No. 64, Europe-University Viadrina, Frankfurt (Oder), Germany.
Vasilopoulos, A. V. and Stamboulis, A. P. (1978): Modification of control chart limits in the presence of data correlation. Journal of Quality Technology, 10(1), 20–30.
Yashchin, E. (1993): Performance of CUSUM control schemes for serially correlated observations. Technometrics, 35(1), 35–52.
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© 1998 Springer-Verlag Berlin Heidelberg
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Severin, T., Schmid, W. (1998). Statistical Process Control and its Application in Finance. In: Bol, G., Nakhaeizadeh, G., Vollmer, KH. (eds) Risk Measurement, Econometrics and Neural Networks. Contributions to Economics. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-58272-1_7
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DOI: https://doi.org/10.1007/978-3-642-58272-1_7
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1152-0
Online ISBN: 978-3-642-58272-1
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