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Titlebook: Quantitative Energy Finance; Modeling, Pricing, a Fred Espen Benth,Valery A. Kholodnyi,Peter Laurenc Book 2014 Springer Science+Business Me

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發(fā)表于 2025-3-21 17:36:48 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Quantitative Energy Finance
副標(biāo)題Modeling, Pricing, a
編輯Fred Espen Benth,Valery A. Kholodnyi,Peter Laurenc
視頻videohttp://file.papertrans.cn/781/780835/780835.mp4
概述First comprehensive collection of current research in the new emerging field of quantitative energy finance.Offers a sophisticated theoretical approach to problems of interest in energy risk managemen
圖書(shū)封面Titlebook: Quantitative Energy Finance; Modeling, Pricing, a Fred Espen Benth,Valery A. Kholodnyi,Peter Laurenc Book 2014 Springer Science+Business Me
描述.Finance and energy markets have been an active scientific field for some time, even though the development and applications of sophisticated quantitative methods in these areas are relatively new—and referred to in a broader context as energy finance. Energy finance is often viewed as a branch of mathematical finance, yet this area continues to provide a rich source of issues that are fuelling new and exciting research developments. Based on a special thematic year at the Wolfgang Pauli Institute (WPI) in Vienna, Austria, this edited collection features cutting-edge research from leading scientists in the fields of energy and commodity finance. Topics discussed include modeling and analysis of energy and commodity markets, derivatives hedging and pricing, and optimal investment strategies and modeling of emerging markets, such as power and emissions. The book also confronts the challenges one faces in energy markets from a quantitative point of view, as well as the recent advances in solving these problems using advanced mathematical, statistical and numerical methods. By addressing the emerging area of quantitative energy finance, this volume will serve as a valuable resource for
出版日期Book 2014
關(guān)鍵詞Energy Finance; Energy Markets; Financial Engineering; Financial Mathematics; Quantitative Finance; Risk
版次1
doihttps://doi.org/10.1007/978-1-4614-7248-3
isbn_softcover978-1-4939-5223-6
isbn_ebook978-1-4614-7248-3
copyrightSpringer Science+Business Media New York 2014
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發(fā)表于 2025-3-21 23:34:01 | 只看該作者
Modelling Electricity Day-Ahead Prices by Multivariate Lévy Semistationary Processeslation structure of electricity day-ahead prices in the EEX market. The flexible structure of . processes is able to reproduce the stylized facts of such data rather well. Furthermore, these processes can be used to model negative prices in electricity markets which started to occur recently and cannot be described by many classical models.
板凳
發(fā)表于 2025-3-22 02:45:54 | 只看該作者
An Analysis of the Main Determinants of Electricity Forward Prices and Forward Risk Premiayse the behaviour of the ex-post electricity forward risk premia in Germany, France and Spain, and in particular we find a positive correlation between ex-post electricity risk premia in these three countries as well as between risk premia for electricity and natural gas futures prices.
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Electricity Options and Additional Informationof the premia. Here, we examine how the presence of an information premium alters the prices of options on forwards. Also, we apply the technique of enlargement of filtrations to show how to calculate the premium specifically for certain types of information and delivery periods. Furthermore, we illustrate the results in various stylised examples.
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發(fā)表于 2025-3-22 14:14:13 | 只看該作者
Mathematics of Swing Options: A Surveynd . methods. Martingale methods build on purely probabilistic properties of the models whereas Markovian methods draw on the interplay between stochastic control and partial differential equations. We also review other techniques available in the literature.
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發(fā)表于 2025-3-23 02:57:29 | 只看該作者
A Survey of Commodity Markets and Structural Models for Electricity Pricests merits over traditional . models. Building on several recent articles, we advocate a broad and flexible structural framework for spot prices, incorporating demand, capacity and fuel prices in several ways, while calculating closed-form forward prices throughout.
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