Statistics Seminar-Localising Temperature Risk

Event Details
  • Date/Time:
    • Thursday January 19, 2012
      10:00 am - 11:00 am
  • Location: ISyE Executive Classroom
  • Phone:
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  • Fee(s):
    N/A
  • Extras:
Contact

Jeff Wu

Summaries

Summary Sentence: Localising Temperature Risk

Full Summary: No summary paragraph submitted.

TITLE: Localising Temperature Risk

SPEAKER: Professor Wolfgang Haerdle

ABSTRACT:

On the temperature derivative market, modeling temperature volatility is an important issue for pricing and hedging. In order to apply pricing tools of financial mathematics, one needs to isolate a Gaussian risk factor. A conventional model for temperature dynamics is a stochastic model with seasonality and intertemporal autocorrelation. Empirical work based on seasonality and autocorrelation correction reveals that the obtained residuals are heteroscedastic with a periodic pattern. The object of this research is to estimate this heteroscedastic function so that after scale normalisation a pure standardised Gaussian variable appears. Earlier work investigated this temperature risk in different locations and showed that neither parametric component functions nor a local linear smoother with constant smoothing parameter are flexible enough to generally describe the volatility process well. Therefore, we consider a local adaptive modeling approach to find at each time point, an optimal smoothing parameter to locally estimate the seasonality and volatility. Our approach provides a more flexible and accurate fitting procedure of localised temperature risk process by achieving excellent normal risk factors.

Contact: "Wolfgang Haerdle" wolfgang.k.haerdle@me.com

Additional Information

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Groups

H. Milton Stewart School of Industrial and Systems Engineering (ISYE)

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Seminar/Lecture/Colloquium
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Status
  • Created By: Anita Race
  • Workflow Status: Published
  • Created On: Jan 9, 2012 - 5:08am
  • Last Updated: Oct 7, 2016 - 9:56pm