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2013 | Buch

Weather Derivatives

Modeling and Pricing Weather-Related Risk

verfasst von: Antonis Alexandridis K., Achilleas D. Zapranis

Verlag: Springer New York

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Über dieses Buch

​Weather derivatives are financial instruments that can be used by organizations or individuals as part of a risk management strategy to minimize risk associated with adverse or unexpected weather conditions. Just as traditional contingent claims, a weather derivative has an underlying measure, such as: rainfall, wind, snow or temperature. Nearly $1 trillion of the U.S. economy is directly exposed to weather-related risk. More precisely, almost 30% of the U.S. economy and 70% of U.S. companies are affected by weather. The purpose of this monograph is to conduct an in-depth analysis of financial products that are traded in the weather market. Presenting a pricing and modeling approach for weather derivatives written on various underlying weather variables will help students, researchers, and industry professionals accurately price weather derivatives, and will provide strategies for effectively hedging against weather-related risk. This book will link the mathematical aspects of the modeling procedure of weather variables to the financial markets and the pricing of weather derivatives. Very little has been published in the area of weather risk, and this volume will appeal to graduate-level students and researchers studying financial mathematics, risk management, or energy finance, in addition to investors and professionals within the financial services industry. ​

Inhaltsverzeichnis

Frontmatter
Chapter 1. The Weather Derivatives Market
Abstract
In this chapter, the various aspects of the weather market are discussed. The applications and purpose of weather derivatives will be presented. Our aim is to analyze the weather market and emphasize in the factors that restrain the weather market to further evolve. At the end of the chapter, an outline of the book is given.
Antonis K. Alexandridis, Achilleas D. Zapranis
Chapter 2. Introduction to Stochastic Calculus
Abstract
The purpose of this chapter is to give the necessary background in stochastic calculus. It is not meant to provide a complete background in stochastic theory but rather present all the necessary theorems and results that will be used later on in order to derive the prices of various weather derivatives on different weather indexes. The reader, familiar or not to stochastic calculus, may use this chapter as a reference.
Antonis K. Alexandridis, Achilleas D. Zapranis
Chapter 3. Handling the Data
Abstract
Easy access to high-quality weather data for long periods and for various stations not only would help the market evolve and would offer liquidity but it is also vital for effective pricing of weather products and for weather risk management. However, the available datasets have many flaws, like missing data, gaps, and errors. In this chapter, techniques for data cleaning and preprocessing are presented and analytically discussed.
Antonis K. Alexandridis, Achilleas D. Zapranis
Chapter 4. Pricing Approaches of Temperature Derivatives
Abstract
This chapter reviews in detail the most important and more often cited models proposed in literature to represent the temperature driving process. In this chapter, the strengths and weaknesses of prior studies will be analyzed in order to develop an appropriate model that describes the temperature dynamics and that it can be used in pricing of various temperature derivatives.
Antonis K. Alexandridis, Achilleas D. Zapranis
Chapter 5. Modeling the Daily Average Temperature
Abstract
The purpose of this chapter is to develop a model that accurately describes the dynamics of the DAT. The statistical properties of the DATS will be examined in order to propose a process that exhibits the same behavior. Our model will be evaluated and compared in-sample and out-of-sample in seven locations against models previously proposed in literature.
Antonis K. Alexandridis, Achilleas D. Zapranis
Chapter 6. Pricing Temperature Derivatives
Abstract
In this chapter, pricing formulas for weather derivatives on various temperature indices will be derived. The model that developed in the previous chapter described the daily dynamics of the temperature. Hence, it can be applied in order to estimate the various indices. This model is used for the pricing on futures and options written on various temperature indices used in the weather market. First, the pricing formulas are derived under the assumption of normally distributed residuals. Next, since our results in the previous chapter indicate that the hyperbolic distribution provides the best fit to the residuals, the pricing formulas are derived under the assumption of a Lévy motion driven process.
Antonis K. Alexandridis, Achilleas D. Zapranis
Chapter 7. Using Meteorological Forecasts for Improving Weather Derivative Pricing
Abstract
Accurate weather forecasts can significantly improve both weather derivative pricing and weather risk management. Forecasters employ different techniques in developing weather forecasts. Common approaches include the numerical weather prediction methods, ensemble forecasts, and probabilistic forecasts. In this chapter, the most common approaches in producing meteorological forecasts are presented. Moreover, approaches for utilizing these forecasts in order to improve weather derivative pricing and weather risk management are presented.
Antonis K. Alexandridis, Achilleas D. Zapranis
Chapter 8. The Effects of the Geographical and Basis Risk
Abstract
This chapter reviews in detail the notion of basis risk in the weather market. In contrast to classical financial markets, basis risk in the sense of weather derivatives has a different definition. First, the notion of geographical basis risk is analyzed, and a spatial model for temperature is presented. Next, the basis risk between the revenues of a company from electricity sector that uses weather derivatives and a weather variable is discussed. The payoff of a weather derivative depends on a weather index and not on the actual amount of money lost due to weather; although temperature and electricity consumption are highly correlated, it is unlikely that the payoff will compensate exactly for the money lost.
Antonis K. Alexandridis, Achilleas D. Zapranis
Chapter 9. Pricing the Power of Wind
Abstract
Wind is considered to be a free, renewable, and environmentally friendly source of energy. However, wind farms are exposed to excessive weather risk since the power production depends on the wind speed and the wind direction. In this chapter, the dynamics of the wind-generating process are modeled using a nonparametric nonlinear wavelet network. Our model is validated in New York. Our results indicate that wavelet networks can model the wind process very well and consequently, and they constitute an accurate and efficient tool for wind derivatives pricing. Finally, we provide the pricing equations for wind futures written on two indices, the cumulative average wind speed index and the Nordix wind speed index.
Antonis K. Alexandridis, Achilleas D. Zapranis
Chapter 10. Precipitation Derivatives
Abstract
Rainfall is considered to be one of the major factors affecting the yield of farmers and the production of hydroelectric energy generators. On the other hand snowfall affects the revenues of ski industry. Rainfall and snowfall can be accounted as a form of precipitation. The aim of this chapter is to analyze the dynamics of the precipitation process and present a modeling procedure for precipitation. Precipitation modeling is separated in two components. The first step is to model the frequency process of precipitation and the second to model the magnitude process. In this chapter the dynamics of the precipitation generating process are modeled using a Markov chain model that define the frequency process and with a gamma distribution for the magnitude process. Our model is validated in Berlin, and the basis risk in the context of precipitation is also examined. Finally, we provide the pricing framework for rainfall futures.
Antonis K. Alexandridis, Achilleas D. Zapranis
Backmatter
Metadaten
Titel
Weather Derivatives
verfasst von
Antonis Alexandridis K.
Achilleas D. Zapranis
Copyright-Jahr
2013
Verlag
Springer New York
Electronic ISBN
978-1-4614-6071-8
Print ISBN
978-1-4614-6070-1
DOI
https://doi.org/10.1007/978-1-4614-6071-8