Localising Temperature Risk

SFB 649 Discussion Paper 2011-001

31 Pages Posted: 9 Jan 2017

See all articles by Wolfgang K. Härdle

Wolfgang K. Härdle

Humboldt University of Berlin - Institute for Statistics and Econometrics; Xiamen University - Wang Yanan Institute for Studies in Economics (WISE); Charles University; Humboldt University of Berlin - Center for Applied Statistics and Economics (CASE)

Brenda López Cabrera

Humboldt University of Berlin

Ostap Okhrin

Humboldt University of Berlin - School of Business and Economics

Weining Wang

Humboldt University of Berlin

Date Written: December 6, 2010

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 inter temporal 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.

Keywords: weather derivatives, localising temperature residuals, seasonality, local model selection

JEL Classification: G19, G29, G22, N23, N53, Q59

Suggested Citation

Härdle, Wolfgang K. and Cabrera, Brenda López and Okhrin, Ostap and Wang, Weining, Localising Temperature Risk (December 6, 2010). SFB 649 Discussion Paper 2011-001. Available at SSRN: https://ssrn.com/abstract=2894234 or http://dx.doi.org/10.2139/ssrn.2894234

Wolfgang K. Härdle (Contact Author)

Humboldt University of Berlin - Institute for Statistics and Econometrics ( email )

Unter den Linden 6
Berlin, D-10099
Germany

Xiamen University - Wang Yanan Institute for Studies in Economics (WISE) ( email )

A 307, Economics Building
Xiamen, Fujian 10246
China

Charles University ( email )

Celetná 13
Dept Math Physics
Praha 1, 116 36
Czech Republic

Humboldt University of Berlin - Center for Applied Statistics and Economics (CASE)

Unter den Linden 6
Berlin, D-10099
Germany

Brenda López Cabrera

Humboldt University of Berlin

Unter den Linden 6
Berlin, AK Berlin 10099
Germany

Ostap Okhrin

Humboldt University of Berlin - School of Business and Economics ( email )

Unter den Linden 6
Berlin, AK Berlin 10099
Germany

Weining Wang

Humboldt University of Berlin ( email )

Unter den Linden 6
Berlin, AK Berlin 10099
Germany

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