Modelling of Temperature Dynamics for Weather Derivatives Pricing - - PowerPoint PPT Presentation

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Modelling of Temperature Dynamics for Weather Derivatives Pricing - - PowerPoint PPT Presentation

Modelling of Temperature Dynamics for Weather Derivatives Pricing Emmanuel Evarest Sinkwembe Department of Mathematics, University of Dar es Salaam Department of Mathematics, Link oping University First Network Meeting for Sida- and


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Modelling of Temperature Dynamics for Weather Derivatives Pricing Emmanuel Evarest Sinkwembe

Department of Mathematics, University of Dar es Salaam Department of Mathematics, Link¨

  • ping University

First Network Meeting for Sida- and ISP-funded PhD Students in Mathematics Stockholm 7–8 March 2017

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My Advisors

Martin Singull Fredrik Berntsson Xiangfeng Yang Wilson Charles

Main advisor Assistant advisor Assistant advisor Assistant advisor Link¨

  • ping University

Link¨

  • ping University

Link¨

  • ping University

UDSM

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Research Focus

In this project, we are trying to formulate a model that captures most of the features of temperature dynamics, and then use the model to price weather derivatives written on temperature indices. Definition Weather derivative is a financial instrument whose payoff is dependent on weather variable measured at specific weather station on given period of time. Weather variables are indexed in order to make them tradable like

  • ther index products such as stoke index.

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Temperature Indices

Given DAT Td(t), reference temperature Tref and contract period

  • f N days

Indices Definition accumulated indices HDD max{0, Tref − Td(t)}

N

  • t=1

max{0, Tref − Td(t)} CDD max{0, Td(t) − Tref }

N

  • t=1

max{0, Td(t) − Tref } CAT

N

  • t=1

Td(t) PRIM

1 N N

  • t=1

Td(t)

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Temperature dynamics

The dynamics of daily average temperature Td(t) is defined by Td(t) = ˜ Td(t) + Sd(t) (1) where ˜ Td(t) and Sd(t) are deseasonalized temperature values and seasonality components respectively.

Time(days)

1000 2000 3000 4000 5000 6000

Temperature[° C]

  • 25
  • 20
  • 15
  • 10
  • 5

5 10 15 20 25

Time(days)

1000 2000 3000 4000 5000 6000

Deseasonalized Temperature

  • 25
  • 20
  • 15
  • 10
  • 5

5 10 15

Figure: Td(t) for Malmsl¨ att superposed with Sd(t) (left) and ˜ Td(t) (right)

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Temperature dynamics continued...

The seasonal component is defined by Sd(t) = A1 sin 2π 365(t − A2)

  • + A3t + A4,

(2) where A1 is the amplitude, A2 is the phase angle, A3 and A4 are coefficients for linear trend. The deseasonalized temperature is given by ˜ Td(t) = ˜ Tt,1 : d ˜ Tt,1 = (µ1 − β ˜ Tt,1)dt + σ1 ˜ Tt,1dWt, ˜ Tt,2 : d ˜ Tt,2 = µ2dt + σ2dWt. (3) The pricing of WD contracts based temperature indices is carried

  • ut under the equivalent measure.

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Impact and Applications of My Research

Meteorology sector, Insurance and re-insurance companies, energy industry Contribution to teaching staff and research at UDSM, Contribution of knowledge in the field of derivatives pricing for non tradable underlying variables.

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Tack s˚ a mycket! Thank you!

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