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Weather derivatives provide a tool for weather risk management, and
the markets for these exotic financial products are gradually
emerging in size and importance. This unique monograph presents a
unified approach to the modeling and analysis of such weather
derivatives, including financial contracts on temperature, wind and
rain. Based on a deep statistical analysis of weather factors,
sophisticated stochastic processes are introduced modeling the time
and space dynamics. Applying ideas from the modern theory of
mathematical finance, weather derivatives are priced, and questions
of hedging analyzed. The treatise contains an in-depth analysis of
typical weather contracts traded at the Chicago Mercantile Exchange
(CME), including so-called CDD and HDD futures. The statistical
analysis of weather variables is based on a large data set from
Lithuania. The monograph includes the research done by the authors
over the last decade on weather markets. Their work has gained
considerable attention, and has been applied in many contexts.
The markets for electricity, gas and temperature have distinctive
features, which provide the focus for countless studies. For
instance, electricity and gas prices may soar several magnitudes
above their normal levels within a short time due to imbalances in
supply and demand, yielding what is known as spikes in the spot
prices. The markets are also largely influenced by seasons, since
power demand for heating and cooling varies over the year. The
incompleteness of the markets, due to nonstorability of electricity
and temperature as well as limited storage capacity of gas, makes
spot-forward hedging impossible. Moreover, futures contracts are
typically settled over a time period rather than at a fixed date.
All these aspects of the markets create new challenges when
analyzing price dynamics of spot, futures and other
derivatives.This book provides a concise and rigorous treatment on
the stochastic modeling of energy markets. Ornstein-Uhlenbeck
processes are described as the basic modeling tool for spot price
dynamics, where innovations are driven by time-inhomogeneous jump
processes. Temperature futures are studied based on a continuous
higher-order autoregressive model for the temperature dynamics. The
theory presented here pays special attention to the seasonality of
volatility and the Samuelson effect. Empirical studies using data
from electricity, temperature and gas markets are given to link
theory to practice.
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