Energy Risk Modeling : Applied Modeling Methods for Risk Managers

by Nigel Da Costa Lewis

Energy Risk Modeling is a primer on statistical methods for managers, students and anybody interested in the field. Illustrated through elementary and more advanced statistical Methods, it is primarily aimed at those individuals who need a gentle introduction in how to go about using statistical methods for modeling energy price risk. Statistical ideas are presented by outlining the necessary concepts and illustrating how these ideas can be implemented. This is the first energy risk book on the market to focus specifically on the role of statistical methods. Its practical approach makes the book a very useful reference and an interesting read

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Year of publication:	2005
Authors:	Lewis, Nigel Da Costa
Publisher:	London : Palgrave Macmillan
Subject:	Energiewirtschaft \| Energy sector \| Risikomanagement \| Risk management \| Statistische Methode \| Statistical method
Description of contents:	Table of Contents [gbv.de]

Extent:	Online-Ressource (XIX, 247 p, online resource)
Series:	Finance and Capital Markets Series SpringerLink / Bücher Springer eBook Collection / Palgrave Economics & Finance Collection Springer ebook collection / Palgrave Economics and Finance Collection 2000 - 2013
Type of publication:	Book / Working Paper
Language:	English
Notes:	Includes bibliographical references (p. 238-241) and index Cover; Contents; List of Tables; List of Figures; Preface; 1 The Statistical Nature of Energy Risk Modeling; 1.1 Historical evolution of energy; 1.2 Financial risks of energy; 1.3 The role of economics-elements of price theory; 1.4 Energy markets and products; 1.5 The science of energy risk modeling; 1.6 Further reading and resources; 2 Introduction to Applied Probability for Energy Risk Management; 3 Descriptive Statistics of Energy Prices and Returns; 4 Inferential Statistical Methods for Energy Risk Managers; 5 Modeling and Fitting Price Distributions 6 Nonparametric Density Estimation for Energy Price Returns7 Correlation Analysis; 8 A Primer in Applied Regression Analysis; 9 Multiple Regression and Prediction; 10 Misspecification Testing; 11 Non-linear and Limited Dependent Regression; 12 Modeling Energy Price Volatility; 13 Stochastic Differential Equations for Derivative Pricing and Energy Risk Management; Appendix: Statistical Tables; Notes; Index 6 Nonparametric Density Estimation for Energy Price Returns7 Correlation Analysis; 8 A Primer in Applied Regression Analysis; 9 Multiple Regression and Prediction; 10 Misspecification Testing; 11 Non-linear and Limited Dependent Regression; 12 Modeling Energy Price Volatility; 13 Stochastic Differential Equations for Derivative Pricing and Energy Risk Management; Appendix: Statistical Tables; Notes; Index; A; B; C; D; E; F; G; H; I; J; K; L; M; N; O; P; Q; R; S; T; U; V; W;
ISBN:	978-0-230-52378-4 ; 978-1-349-51702-2
Other identifiers:	10.1057/9780230523784 [DOI]
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012054126