Dependence Structures of Financial Time Series Martin Gartner - PowerPoint PPT Presentation

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Motivation Pearsons Correlation Coefficient Copulae Copula-based dependence measures Estimation and Calibration of a Copula Empirical Results Research Outlook Dependence Structures of Financial Time Series Martin Gartner December 14,

Motivation Pearson’s Correlation Coefficient Copulae Copula-based dependence measures Estimation and Calibration of a Copula Empirical Results Research Outlook Dependence Structures of Financial Time Series Martin Gartner December 14, 2007 Martin Gartner Dependence Structures of Financial Time Series
Motivation Pearson’s Correlation Coefficient Copulae Copula-based dependence measures Estimation and Calibration of a Copula Empirical Results Research Outlook Inhaltsverzeichnis Motivation Pearson’s Correlation Coefficient Copulae Copula-based dependence measures Estimation and Calibration of a Copula Empirical Results Research Outlook Martin Gartner Dependence Structures of Financial Time Series
Motivation Pearson’s Correlation Coefficient Copulae Introduction Copula-based dependence measures Empirical Evidence Estimation and Calibration of a Copula Consequences Empirical Results Research Outlook Motivation Financial Models often require iid. random variables Models assume: ◮ Constant variance ◮ Absence of autocorrelation ◮ Normal Distribution Do empirical data hold these assumptions? Martin Gartner Dependence Structures of Financial Time Series
Motivation Pearson’s Correlation Coefficient Copulae Introduction Copula-based dependence measures Empirical Evidence Estimation and Calibration of a Copula Consequences Empirical Results Research Outlook Emprical Evidence of Constant Variance? Abs. Std.Dev. Siemens Abs. Std.Dev. BAYER Abs. Std.Dev. BMW 0.30 0.30 0.30 0.20 0.20 0.20 0.10 0.10 0.10 0.00 0.00 0.00 2002 2004 2006 2002 2004 2006 2002 2004 2006 Date Date Date Figure: Absolute Returns Martin Gartner Dependence Structures of Financial Time Series
Motivation Pearson’s Correlation Coefficient Copulae Introduction Copula-based dependence measures Empirical Evidence Estimation and Calibration of a Copula Consequences Empirical Results Research Outlook Emprical Evidence of Autocorrelation? Autocorrelation Siemens Autocorrelation BAYER Autocorrelation BMW 0.10 0.10 ● 0.10 ● 0.05 0.05 ● 0.05 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0.00 ● ● ● ● 0.00 0.00 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● −0.10 −0.10 −0.10 ● ● ● 0 5 10 15 20 25 30 0 5 10 15 20 25 30 0 5 10 15 20 25 30 Lag Lag Lag Figure: Autocorrelation of Return Series Martin Gartner Dependence Structures of Financial Time Series

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