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Sequentielle Überwachung von Finanzzeitreihen anhand von Residuenkarten

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  • Robert Garthoff

Abstract

In this paper, the focus is on sequential analysis of financial time series. Mean and variance of time series are simultaneously monitored. Initially, conventional control charts, well-known tools of statistical process control, are combined with the previously introduced characteristic quantity. The considered characteristic quantity is a vector including the residuals of the fitted model and their squares. Further, the respective control procedures are calibrated via simulation. The effectiveness of control schemes is demonstrated in the empirical example, where the main German share price index is studied during the financial crisis from 2006 until 2008. The main purpose is the identification of structural changes in mean or variance using predictions based on linear regression with time series errors applied to the considered price index and the GARCH model applied to logarithmic returns. Structural breaks are visualized by signals of the considered residual charts. Therefore, fluctuations on the capital market during financial crises are illustrated. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • Robert Garthoff, 2014. "Sequentielle Überwachung von Finanzzeitreihen anhand von Residuenkarten," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 8(3), pages 91-113, September.
  • Handle: RePEc:spr:astaws:v:8:y:2014:i:3:p:91-113
    DOI: 10.1007/s11943-014-0145-6
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    References listed on IDEAS

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    1. Markus Spiwoks & Oliver Hein, 2007. "Die Währungs-, Anleihen- und Aktienmarktprognosen des Zentrums für Europäische Wirtschaftsforschung," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 1(1), pages 43-52, June.
    2. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
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    5. Dominik Wied & Matthias Arnold & Nicolai Bissantz & Daniel Ziggel, 2013. "Über die Anwendbarkeit eines neuen Fluktuationstests für Korrelationen auf Finanzzeitreihen," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 6(3), pages 87-103, March.
    6. Robert Garthoff & Iryna Okhrin & Wolfgang Schmid, 2014. "Statistical surveillance of the mean vector and the covariance matrix of nonlinear time series," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 98(3), pages 225-255, July.
    7. Chu, Chia-Shang James & Stinchcombe, Maxwell & White, Halbert, 1996. "Monitoring Structural Change," Econometrica, Econometric Society, vol. 64(5), pages 1045-1065, September.
    8. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    1. Ralf Thomas Münnich, 2014. "Vorwort des Herausgebers," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 8(3), pages 89-90, September.

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    More about this item

    Keywords

    Statistische Prozesskontrolle; CUSUM-Karten; EWMA-Karten; Lineare Regression mit Zeitreihenfehlern; GARCH-Prozesse; Prognosen; C12; C15; C22; Statistical process control; CUSUM charts; EWMAcharts; Linear regression with time series errors; GARCH models; Prediction;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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