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Energy power risk : derivatives, computation and optimization / George Levy (RWE npower, UK).

By: Material type: TextTextPublisher: Bingley, U.K. : Emerald Publishing Limited, 2018Copyright date: ©2019Description: 1 online resource (xvii, 326 pages) ; cmContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781787435278 (e-book)
  • 9781787439566 (ePUB)
Subject(s): Additional physical formats: No titleLOC classification:
  • HD9502.A2 L48 2018
Online resources:
Contents:
Prelims -- Overview -- Brownian motion and stochastic processes -- Fundamental power price model -- Single asset European options -- Single asset American style options -- Multi-asset options -- Power contracts -- Portfolio optimization -- Example C++ classes -- The Greeks for vanilla European options -- Standard statistical results -- Statistical distribution functions -- Mathematical reference -- Answers to problems -- References -- Index.
Summary: 'Energy Power Risk: Derivatives, Computation and Optimization' is a comprehensive guide presenting the latest mathematical and computational tools required for the quantification and management of energy power risk. Written by a practitioner with many years' experience in the field, it provides readers with valuable insights in to the latest practices and methodologies used in today's markets, showing readers how to create innovative quantitative models for energy and power risk and derivative valuation. The book begins with an introduction to the mathematics of Brownian motion and stochastic processes, covering Geometric Brownian motion, Ito's lemma, Ito's Isometry, the Ornstein Uhlenbeck process and more. It then moves on to the simulation of power prices and the valuation of energy derivatives, before considering software engineering techniques for energy risk and portfolio optimization. The book also covers additional topics including wind and solar generation, intraday storage, generation and demand optionality. Written in a highly practical manner and with example C++ and VBA code provided throughout, 'Energy Power Risk: Derivatives, Computation and Optimization' will be an essential reference for quantitative analysts, financial engineers and other practitioners in the field of energy risk management, as well as researchers and students interested in the industry and how it works.
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Includes bibliographical references and index.

Prelims -- Overview -- Brownian motion and stochastic processes -- Fundamental power price model -- Single asset European options -- Single asset American style options -- Multi-asset options -- Power contracts -- Portfolio optimization -- Example C++ classes -- The Greeks for vanilla European options -- Standard statistical results -- Statistical distribution functions -- Mathematical reference -- Answers to problems -- References -- Index.

'Energy Power Risk: Derivatives, Computation and Optimization' is a comprehensive guide presenting the latest mathematical and computational tools required for the quantification and management of energy power risk. Written by a practitioner with many years' experience in the field, it provides readers with valuable insights in to the latest practices and methodologies used in today's markets, showing readers how to create innovative quantitative models for energy and power risk and derivative valuation. The book begins with an introduction to the mathematics of Brownian motion and stochastic processes, covering Geometric Brownian motion, Ito's lemma, Ito's Isometry, the Ornstein Uhlenbeck process and more. It then moves on to the simulation of power prices and the valuation of energy derivatives, before considering software engineering techniques for energy risk and portfolio optimization. The book also covers additional topics including wind and solar generation, intraday storage, generation and demand optionality. Written in a highly practical manner and with example C++ and VBA code provided throughout, 'Energy Power Risk: Derivatives, Computation and Optimization' will be an essential reference for quantitative analysts, financial engineers and other practitioners in the field of energy risk management, as well as researchers and students interested in the industry and how it works.

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