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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. "
The main purpose of this book is to resolve deficiencies and
limitations that currently exist when using Technical Analysis
(TA). Particularly, TA is being used either by academics as an
"economic test" of the weak-form Efficient Market Hypothesis (EMH)
or by practitioners as a main or supplementary tool for deriving
trading signals. This book approaches TA in a systematic way
utilizing all the available estimation theory and tests. This is
achieved through the developing of novel rule-based pattern
recognizers, and the implementation of statistical tests for
assessing the importance of realized returns. More emphasis is
given to technical patterns where subjectivity in their
identification process is apparent. Our proposed methodology is
based on the algorithmic and thus unbiased pattern recognition. The
unified methodological framework presented in this book can serve
as a benchmark for both future academic studies that test the null
hypothesis of the weak-form EMH and for practitioners that want to
embed TA within their trading/investment decision making processes.
The main purpose of this book is to resolve deficiencies and
limitations that currently exist when using Technical Analysis
(TA). Particularly, TA is being used either by academics as an
"economic test" of the weak-form Efficient Market Hypothesis (EMH)
or by practitioners as a main or supplementary tool for deriving
trading signals. This book approaches TA in a systematic way
utilizing all the available estimation theory and tests. This is
achieved through the developing of novel rule-based pattern
recognizers, and the implementation of statistical tests for
assessing the importance of realized returns. More emphasis is
given to technical patterns where subjectivity in their
identification process is apparent. Our proposed methodology is
based on the algorithmic and thus unbiased pattern recognition. The
unified methodological framework presented in this book can serve
as a benchmark for both future academic studies that test the null
hypothesis of the weak-form EMH and for practitioners that want to
embed TA within their trading/investment decision making processes.
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.
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