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 graduate-level students and researchers studying financial mathematics, risk management, or energy finance.
Modeling the dynamics of energy markets has become a challenging task. The intensification of their financialization since 2004 had made them more complex but also more integrated with other tradable asset classes. More importantly, their large and frequent fluctuations in terms of both prices and volatility, particularly in the aftermath of the global financial crisis 2008-2009, posit difficulties for modeling and forecasting energy price behavior and are primary sources of concerns for macroeconomic stability and general economic performance.This handbook aims to advance the debate on the theories and practices of quantitative energy finance while shedding light on innovative results and technical methods applied to energy markets. Its primary focus is on the recent development and applications of mathematical and quantitative approaches for a better understanding of the stochastic processes that drive energy market movements. The handbook is designed for not only graduate students and researchers but also practitioners and policymakers.
Given the design component it involves, financial engineering should be considered equal to conventional engineering. By adopting this complementary approach, financial models can be used to identify how and why timing is critical in optimizing return on investment and to demonstrate how financial engineering can enhance returns to investors. Metals and Energy Finance capitalizes on this approach, and identifies and examines the investment opportunities offered across the extractive industry's cycle, from exploration through evaluation, pre-production development, development and production. The textbook also addresses the similarities of a range of natural resource projects, whether minerals or petroleum, while at the same time identifying their key differences. This new edition has been comprehensively revised with a new chapter on Quantitative Finance and three additional case studies. Contemporary themes in the revised edition include the current focus on the transition from open pit to underground mining as well as the role of real option valuations applied to marginal projects that may have value in the future. This innovative textbook is clear and concise in its approach. Both authors have extensive experience within the academic environment at a senior level as well as track records of hands-on participation in projects within the natural resources and financial services sectors. Metals and Energy Finance will be invaluable to both professionals and graduate students working in the field of mineral and petroleum business management.
This book presents practical Risk Management and Trading applications for the Electricity Markets. Various methodologies developed over the last few years are considered and current literature is reviewed. The book emphasizes the relationship between trading, hedging and generation asset management.
This volume provides practical solutions and introduces recent theoretical developments in risk management, pricing of credit derivatives, quantification of volatility and copula modeling. This third edition is devoted to modern risk analysis based on quantitative methods and textual analytics to meet the current challenges in banking and finance. It includes 14 new contributions and presents a comprehensive, state-of-the-art treatment of cutting-edge methods and topics, such as collateralized debt obligations, the high-frequency analysis of market liquidity, and realized volatility. The book is divided into three parts: Part 1 revisits important market risk issues, while Part 2 introduces novel concepts in credit risk and its management along with updated quantitative methods. The third part discusses the dynamics of risk management and includes risk analysis of energy markets and for cryptocurrencies. Digital assets, such as blockchain-based currencies, have become popular b ut are theoretically challenging when based on conventional methods. Among others, it introduces a modern text-mining method called dynamic topic modeling in detail and applies it to the message board of Bitcoins. The unique synthesis of theory and practice supported by computational tools is reflected not only in the selection of topics, but also in the fine balance of scientific contributions on practical implementation and theoretical concepts. This link between theory and practice offers theoreticians insights into considerations of applicability and, vice versa, provides practitioners convenient access to new techniques in quantitative finance. Hence the book will appeal both to researchers, including master and PhD students, and practitioners, such as financial engineers. The results presented in the book are fully reproducible and all quantlets needed for calculations are provided on an accompanying website. The Quantlet platform quantlet.de, quantlet.com, quantlet.org is an integrated QuantNet environment consisting of different types of statistics-related documents and program codes. Its goal is to promote reproducibility and offer a platform for sharing validated knowledge native to the social web. QuantNet and the corresponding Data-Driven Documents-based visualization allows readers to reproduce the tables, pictures and calculations inside this Springer book.
An accessible introduction to quantitative finance by the numbers—for students, professionals, and personal investors The world of quantitative finance is complex, and sometimes even high-level financial experts have difficulty grasping it. Quantitative Finance For Dummies offers plain-English guidance on making sense of applying mathematics to investing decisions. With this complete guide, you'll gain a solid understanding of futures, options and risk, and become familiar with the most popular equations, methods, formulas, and models (such as the Black-Scholes model) that are applied in quantitative finance. Also known as mathematical finance, quantitative finance is about applying mathematics and probability to financial markets, and involves using mathematical models to help make investing decisions. It's a highly technical discipline—but almost all investment companies and hedge funds use quantitative methods. The book breaks down the subject of quantitative finance into easily digestible parts, making it approachable for personal investors, finance students, and professionals working in the financial sector –especially in banking or hedge funds who are interested in what their quant (quantitative finance professional) colleagues are up to. This user-friendly guide will help you even if you have no previous experience of quantitative finance or even of the world of finance itself. With the help of Quantitative Finance For Dummies, you'll learn the mathematical skills necessary for success with quantitative finance and tips for enhancing your career in quantitative finance. Get your own copy of this handy reference guide and discover: An easy-to-follow introduction to the complex world of quantitative finance The core models, formulas, and methods used in quantitative finance Exercises to help augment your understanding of QF How QF methods are used to define the current market value of a derivative security Real-world examples that relate quantitative finance to your day-to-day job Mathematics necessary for success in investment and quantitative finance Portfolio and risk management applications Basic derivatives pricing Whether you're an aspiring quant, a top-tier personal investor, or a student, Quantitative Finance For Dummies is your go-to guide for coming to grips with QF/risk management.
This volume is a collection of chapters covering the latest developments in applications of financial mathematics and statistics to topics in energy, commodity financial markets and environmental economics. The research presented is based on the presentations and discussions that took place during the Fields Institute Focus Program on Commodities, Energy and Environmental Finance in August 2013. The authors include applied mathematicians, economists and industry practitioners, providing for a multi-disciplinary spectrum of perspectives on the subject. The volume consists of four sections: Electricity Markets; Real Options; Trading in Commodity Markets; and Oligopolistic Models for Energy Production. Taken together, the chapters give a comprehensive summary of the current state of the art in quantitative analysis of commodities and energy finance. The topics covered include structural models of electricity markets, financialization of commodities, valuation of commodity real options, game-theory analysis of exhaustible resource management and analysis of commodity ETFs. The volume also includes two survey articles that provide a source for new researchers interested in getting into these topics.
Valuation and Risk Management in Energy Markets surveys the mechanics of energy markets and the valuation of structures commonly arising in practice. The presentation balances quantitative issues and practicalities facing portfolio managers, with substantial attention paid to the ways in which common methods fail in practice and to alternative methods when they exist. The material spans basic fundamentals of markets, statistical analysis of price dynamics, and a sequence of increasingly challenging structures, concluding with issues arising at the enterprise level. In totality, the material has been selected to provide readers with the analytical foundation required to function in modern energy trading and risk management groups.
Commodity markets present several challenges for quantitative modeling. These include high volatilities, small sample data sets, and physical, operational complexity. In addition, the set of traded products in commodity markets is more limited than in financial or equity markets, making value extraction through trading more difficult. These facts make it very easy for modeling efforts to run into serious problems, as many models are very sensitive to noise and hence can easily fail in practice. Modeling and Valuation of Energy Structures is a comprehensive guide to quantitative and statistical approaches that have been successfully employed in support of trading operations, reflecting the author's 17 years of experience as a front-office 'quant'. The major theme of the book is that simpler is usually better, a message that is drawn out through the reality of incomplete markets, small samples, and informational constraints. The necessary mathematical tools for understanding these issues are thoroughly developed, with many techniques (analytical, econometric, and numerical) collected in a single volume for the first time. A particular emphasis is placed on the central role that the underlying market resolution plays in valuation. Examples are provided to illustrate that robust, approximate valuations are to be preferred to overly ambitious attempts at detailed qualitative modeling.
The book describes both mathematical and computational tools for energy and power risk management, deriving from first principles stochastic models for simulating commodity risk and how to design robust C++ to implement these models.
A road map for implementing quantitative financialmodels Financial Derivative and Energy Market Valuation bringsthe application of financial models to a higher level by helpingreaders capture the true behavior of energy markets and relatedfinancial derivatives. The book provides readers with a range ofstatistical and quantitative techniques and demonstrates how toimplement the presented concepts and methods in Matlab®. Featuring an unparalleled level of detail, this unique workprovides the underlying theory and various advanced topics withoutrequiring a prior high-level understanding of mathematics orfinance. In addition to a self-contained treatment of appliedtopics such as modern Fourier-based analysis and affine transforms,Financial Derivative and Energy Market Valuation also: • Provides the derivation, numerical implementation, anddocumentation of the corresponding Matlab for each topic • Extends seminal works developed over the last four decadesto derive and utilize present-day financial models • Shows how to use applied methods such as fast Fouriertransforms to generate statistical distributions for optionpricing • Includes all Matlab code for readers wishing to replicatethe figures found throughout the book Thorough, practical, and easy to use, Financial Derivativeand Energy Market Valuation is a first-rate guide for readerswho want to learn how to use advanced numerical methods toimplement and apply state-of-the-art financial models. The book isalso ideal for graduate-level courses in quantitative finance,mathematical finance, and financial engineering.
This book reflects the state of the art on nonlinear economic dynamics, financial market modelling and quantitative finance. It contains eighteen papers with topics ranging from disequilibrium macroeconomics, monetary dynamics, monopoly, financial market and limit order market models with boundedly rational heterogeneous agents to estimation, time series modelling and empirical analysis and from risk management of interest-rate products, futures price volatility and American option pricing with stochastic volatility to evaluation of risk and derivatives of electricity market. The book illustrates some of the most recent research tools in these areas and will be of interest to economists working in economic dynamics and financial market modelling, to mathematicians who are interested in applying complexity theory to economics and finance and to market practitioners and researchers in quantitative finance interested in limit order, futures and electricity market modelling, derivative pricing and risk management.
