The volatility of temperature and pricing of weather derivatives

Benth, Fred Espen; Benth, Jūratė Šaltytė

doi:10.1080/14697680601155334

Cited by 139 publications

(149 citation statements)

References 7 publications

(13 reference statements)

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“…The pricing mechanisms suggested in the literature (Alaton et al, 2002;Benth and Benth, 2005;Campbell and Diebold, 2002;Cao and Wei, 2004) are various, burn analysis, index modeling approaches, daily weather variable process models, and the so called daily simulation approaches to name a few. Burn analysis valuates a derivative simply by averaging all payoffs that would have been realized in the past.…”

Section: Introductionmentioning

confidence: 99%

“…Similar in a sense to Cao and Wei (1999), Shim and Hwang (2011) forecast volatility via conditional autoregressive value at risk model on the basis of support vector quantile regression. Benth and Benth (2005) follow up Cao and Wei (1999) with a detailed model for the temperature dynamics. Since weather factors are not assets and can not be traded, the traditional no-arbitrage approach, risk-neutral valuation is not directly applicable to weather derivatives.…”

Section: Introductionmentioning

confidence: 99%

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Pricing weather derivatives: An application to the electrical utility

Zou¹,

Lee²

2012

Journal of the Korean Data and Information Science Society

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Weather derivatives designed to manage casual changes of weather, as opposed to catastrophic risks of weather, are relatively a new class of financial instruments. There are still many theoretical and practical challenges to the effective use of these instruments. The objective of this paper is to develop a pricing approach for valuing weather derivatives and presents a case study that is practical enough to be used by the risk managers of electrical utility firms. Utilizing daily average temperature data of Guangzhou, China from 1 st January 1978 to 31 st December 2010, this paper adopted a univariate time series model to describe weather behavior dynamics and calculates equilibrium prices for weather futures and options for an electrical utility firm in the region. The results imply that the risk premium is an important part of derivatives prices and the market price of risk affects option values much more than forward prices. It also demonstrates that weather innovation as well as weather risk management significantly affect the utility's financial outcomes.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Pricing weather derivatives: An application to the electrical utility

Zou¹,

Lee²

2012

Journal of the Korean Data and Information Science Society

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“…Here, a yearly seasonality and a linear trend can be identified. Therefore, we use a temperature model closely related to the one proposed by Benth and Benth [2]. (6) with X (T ) t being an AR(3) process.…”

Section: Temperature Modelmentioning

confidence: 99%

Modeling the Price of Natural Gas with Temperature and Oil Price as Exogenous Factors

Müller

Hirsch

Müller

2015

Innovations in Quantitative Risk Management

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The literature on stochastic models for the spot market of gas is dominated by purely stochastic approaches. In contrast to these models, Stoll and Wiebauer [14] propose a fundamental model with temperature as an exogenous factor. A model containing only deterministic, temperature-dependent and purely stochastic components, however, still seems not able to capture economic influences on the price. In order to improve the model of Stoll and Wiebauer [14], we include the oil price as another exogenous factor. There are at least two fundamental reasons why this should improve the model. First, the oil price can be considered as a proxy for the general state of the world economy. Furthermore, pricing formulas in oil price indexed gas import contracts in Central Europe are covered by the oil price component. It is shown that the new model can explain price movements of the last few years much better than previous models. The inclusion of oil price and temperature in the regression of a least squares Monte Carlo method leads to more realistic valuation results for gas storages and swing options.

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“…In this setting, the cost of claims is also influenced by C m unobservable factors, independent from those driving the claims arrival process. These factors are modeled by a Markov state vector, (4) and (5). Otherwise, the multiplier is equal to its previous value…”

Section: Historical Std Simulated Meanmentioning

confidence: 99%

“…In Alaton et al (2002) or Campbell and Diebold (2005), the index of temperatures is modelled by a Brownian motion with a seasonal drift. Other climatic indexes are modeled by an Ornstein-Uhlenbeck process such as in Dornier and Queruel (2000) and Benth and Benth (2007) and (2009). In Hainaut (2010), we have used a similar approach to model the arrival process of seasonal claims.…”

Section: Introductionmentioning

confidence: 99%

Frequency and Severity Modelling Using Multifractal Processes: An Application to Tornado Occurrence in the USA and CAT Bonds

Hainaut

Boucher²

2013

Environ Model Assess

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This paper proposes a statistical model for claims related to climatic events that exhibit huge volatility both in frequency and intensity, such these caused by tornadoes hitting the US. To duplicate this volatility and the seasonality, we introduce a new claim arrival process modeled by a Poisson process of intensity equal to the product of a periodic function with a multifractal process. The amplitudes of claims are modeled in a similar way, with gamma random variables. We show that this method allows simulation of the peaks of damage. The two dimension multifractal model is also investigated. The work concludes with an analysis of the impact of the model on spreads of weather bonds related to claims caused by tornadoes.

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The volatility of temperature and pricing of weather derivatives

Cited by 139 publications

References 7 publications

Pricing weather derivatives: An application to the electrical utility

Pricing weather derivatives: An application to the electrical utility

Modeling the Price of Natural Gas with Temperature and Oil Price as Exogenous Factors

Frequency and Severity Modelling Using Multifractal Processes: An Application to Tornado Occurrence in the USA and CAT Bonds

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