KTH Matematik  

Matematisk Statistik

Tid: 4 juli 2017 kl 11.00-11.45.

Seminarierummet 3418, Institutionen för matematik, KTH, Lindstedtsvägen 25, plan 4. Karta!

Föredragshållare: Johan Viktorsson

Title: The GARCH-copula model for gaugeing time conditional dependence in the risk management of electricity derivatives

Abstract: In the risk management of electricity derivatives, time to delivery can be divided into a time grid, with the assumption that within each cell of the grid, volatility is more or less constant. This setup however does not take in to account dependence between the different cells in the time grid. This thesis tries to develop a way to gauge the dependence between elec- tricity derivatives at the different places in the time grid and different de- livery periods. More specifically, the aim is to estimate the size of the ratio of the quantile of the sum of price changes against the sum of the marginal quantiles of the price changes. The approach used is a combination of Generalised Autoregressive Con- ditional Heteroscedasticity (GARCH) processes and copulas. The GARCH process is used to filter out heteroscedasticity in the price data. Copulas are fitted to the filtered data using pseudo maximum likelihood and the fitted copulas are evaluated using a goodness of fit test. GARCH processes alone are found to be insufficient to capture the dy- namics of the price data. It is found that combining GARCH with Au- toregressive Moving Average processes provides better fit to the data. The resulting dependence is the found to be best captured by elliptical copulas. The estimated ratio is found to be quite small in the cases studied. The use of the ARMA-GARCH filtering gives in general a better fit for copulas when applied to financial data. A time dependency in the dependence can also be observed.

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Sidansvarig: Filip Lindskog
Uppdaterad: 25/02-2009