Temperature modelling and weather derivatives pricing with application in Scottish electricity industry

Weather and more precisely average temperature is undoubtedly the most significant natural factor to which the electricity industry is vulnerable. Since late 1990s weather derivatives have been increasingly employed to hedge volumetric risk due to adverse temperature. This dissertation attempts to d...

Full description

Bibliographic Details
Main Author: Pang, Chuanqi
Format: Dissertation (University of Nottingham only)
Language:English
Published: 2012
Subjects:
Online Access:https://eprints.nottingham.ac.uk/25452/
_version_ 1848792982242721792
author Pang, Chuanqi
author_facet Pang, Chuanqi
author_sort Pang, Chuanqi
building Nottingham Research Data Repository
collection Online Access
description Weather and more precisely average temperature is undoubtedly the most significant natural factor to which the electricity industry is vulnerable. Since late 1990s weather derivatives have been increasingly employed to hedge volumetric risk due to adverse temperature. This dissertation attempts to discuss weather derivatives hedging in relation to the Scottish electricity market. To achieve this goal, we first deal with the most important issue, temperature modelling, in which we consider AR(1) and ARMA models for empirical temperature simulations. In the second part, we use statistical regressions to investigate the relationship between monthly temperature and electricity consumption in Scotland. The dependency and seasonality of electricity consumption is strongly evidenced. After the relation between electricity consumption and temperature is analysed, appropriate hedging strategies are illustrated using pricing techniques such as burn analysis and Monte Carlo simulation to determine fair prices of the temperature options. Although the hedging part is rather simple due to availability of data, the implications of our findings shed some light on hedging using temperature-based derivative contracts in the increasingly de-regulated Scottish electricity industry.
first_indexed 2025-11-14T18:53:03Z
format Dissertation (University of Nottingham only)
id nottingham-25452
institution University of Nottingham Malaysia Campus
institution_category Local University
language English
last_indexed 2025-11-14T18:53:03Z
publishDate 2012
recordtype eprints
repository_type Digital Repository
spelling nottingham-254522018-03-18T14:28:40Z https://eprints.nottingham.ac.uk/25452/ Temperature modelling and weather derivatives pricing with application in Scottish electricity industry Pang, Chuanqi Weather and more precisely average temperature is undoubtedly the most significant natural factor to which the electricity industry is vulnerable. Since late 1990s weather derivatives have been increasingly employed to hedge volumetric risk due to adverse temperature. This dissertation attempts to discuss weather derivatives hedging in relation to the Scottish electricity market. To achieve this goal, we first deal with the most important issue, temperature modelling, in which we consider AR(1) and ARMA models for empirical temperature simulations. In the second part, we use statistical regressions to investigate the relationship between monthly temperature and electricity consumption in Scotland. The dependency and seasonality of electricity consumption is strongly evidenced. After the relation between electricity consumption and temperature is analysed, appropriate hedging strategies are illustrated using pricing techniques such as burn analysis and Monte Carlo simulation to determine fair prices of the temperature options. Although the hedging part is rather simple due to availability of data, the implications of our findings shed some light on hedging using temperature-based derivative contracts in the increasingly de-regulated Scottish electricity industry. 2012-07 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/25452/1/WD_dissertation_final.pdf Pang, Chuanqi (2012) Temperature modelling and weather derivatives pricing with application in Scottish electricity industry. [Dissertation (University of Nottingham only)] (Unpublished) weather derivatives fair pricing temperature modelling Monte Carlo simulation hedging weather risk Scottish electricity
spellingShingle weather derivatives
fair pricing
temperature modelling
Monte Carlo simulation
hedging weather risk
Scottish electricity
Pang, Chuanqi
Temperature modelling and weather derivatives pricing with application in Scottish electricity industry
title Temperature modelling and weather derivatives pricing with application in Scottish electricity industry
title_full Temperature modelling and weather derivatives pricing with application in Scottish electricity industry
title_fullStr Temperature modelling and weather derivatives pricing with application in Scottish electricity industry
title_full_unstemmed Temperature modelling and weather derivatives pricing with application in Scottish electricity industry
title_short Temperature modelling and weather derivatives pricing with application in Scottish electricity industry
title_sort temperature modelling and weather derivatives pricing with application in scottish electricity industry
topic weather derivatives
fair pricing
temperature modelling
Monte Carlo simulation
hedging weather risk
Scottish electricity
url https://eprints.nottingham.ac.uk/25452/