Mathematical Modelling of Contemporary Electricity Markets

Mathematical Modelling of Contemporary Electricity Markets
Author: Athanasios Dagoumas
Publisher: Academic Press
Total Pages: 444
Release: 2021-01-30
Genre: Business & Economics
ISBN: 0128218398

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Mathematical Modelling of Contemporary Electricity Markets reviews major methodologies and tools to accurately analyze and forecast contemporary electricity markets in a ways that is ideal for practitioner and academic audiences. Approaches include optimization, neural networks, genetic algorithms, co-optimization, econometrics, E3 models and energy system models. The work examines how new challenges affect power market modeling, including discussions of stochastic renewables, price volatility, dynamic participation of demand, integration of storage and electric vehicles, interdependence with other commodity markets and the evolution of policy developments (market coupling processes, security of supply). Coverage addresses all major forms of electricity markets: day-ahead, forward, intraday, balancing, and capacity. Provides a diverse body of established techniques suitable for modeling any major aspect of electricity markets Familiarizes energy experts with the quantitative skills needed in competitive electricity markets Reviews market risk for energy investment decisions by stressing the multi-dimensionality of electricity markets

Mathematical Modeling in Economics and Finance: Probability, Stochastic Processes, and Differential Equations

Mathematical Modeling in Economics and Finance: Probability, Stochastic Processes, and Differential Equations
Author: Steven R. Dunbar
Publisher: American Mathematical Soc.
Total Pages: 232
Release: 2019-04-03
Genre: Economics
ISBN: 1470448394

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Mathematical Modeling in Economics and Finance is designed as a textbook for an upper-division course on modeling in the economic sciences. The emphasis throughout is on the modeling process including post-modeling analysis and criticism. It is a textbook on modeling that happens to focus on financial instruments for the management of economic risk. The book combines a study of mathematical modeling with exposure to the tools of probability theory, difference and differential equations, numerical simulation, data analysis, and mathematical analysis. Students taking a course from Mathematical Modeling in Economics and Finance will come to understand some basic stochastic processes and the solutions to stochastic differential equations. They will understand how to use those tools to model the management of financial risk. They will gain a deep appreciation for the modeling process and learn methods of testing and evaluation driven by data. The reader of this book will be successfully positioned for an entry-level position in the financial services industry or for beginning graduate study in finance, economics, or actuarial science. The exposition in Mathematical Modeling in Economics and Finance is crystal clear and very student-friendly. The many exercises are extremely well designed. Steven Dunbar is Professor Emeritus of Mathematics at the University of Nebraska and he has won both university-wide and MAA prizes for extraordinary teaching. Dunbar served as Director of the MAA's American Mathematics Competitions from 2004 until 2015. His ability to communicate mathematics is on full display in this approachable, innovative text.

Mathematical Models of Financial Derivatives

Mathematical Models of Financial Derivatives
Author: Yue-Kuen Kwok
Publisher: Springer Science & Business Media
Total Pages: 541
Release: 2008-07-10
Genre: Mathematics
ISBN: 3540686886

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This second edition, now featuring new material, focuses on the valuation principles that are common to most derivative securities. A wide range of financial derivatives commonly traded in the equity and fixed income markets are analysed, emphasising aspects of pricing, hedging and practical usage. This second edition features additional emphasis on the discussion of Ito calculus and Girsanovs Theorem, and the risk-neutral measure and equivalent martingale pricing approach. A new chapter on credit risk models and pricing of credit derivatives has been added. Up-to-date research results are provided by many useful exercises.

Mathematical Modeling for the Marketplace

Mathematical Modeling for the Marketplace
Author: Helen Christensen
Publisher: Kendall/Hunt Publishing Company
Total Pages: 180
Release: 1988
Genre: Mathematics
ISBN: 9780840346612

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Mathematical Methods for Financial Markets

Mathematical Methods for Financial Markets
Author: Monique Jeanblanc
Publisher: Springer Science & Business Media
Total Pages: 754
Release: 2009-10-03
Genre: Business & Economics
ISBN: 1846287375

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Mathematical finance has grown into a huge area of research which requires a large number of sophisticated mathematical tools. This book simultaneously introduces the financial methodology and the relevant mathematical tools in a style that is mathematically rigorous and yet accessible to practitioners and mathematicians alike. It interlaces financial concepts such as arbitrage opportunities, admissible strategies, contingent claims, option pricing and default risk with the mathematical theory of Brownian motion, diffusion processes, and Lévy processes. The first half of the book is devoted to continuous path processes whereas the second half deals with discontinuous processes. The extensive bibliography comprises a wealth of important references and the author index enables readers quickly to locate where the reference is cited within the book, making this volume an invaluable tool both for students and for those at the forefront of research and practice.

Mathematical Modeling And Computation In Finance: With Exercises And Python And Matlab Computer Codes

Mathematical Modeling And Computation In Finance: With Exercises And Python And Matlab Computer Codes
Author: Cornelis W Oosterlee
Publisher: World Scientific
Total Pages: 1310
Release: 2019-10-29
Genre: Business & Economics
ISBN: 1786347962

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This book discusses the interplay of stochastics (applied probability theory) and numerical analysis in the field of quantitative finance. The stochastic models, numerical valuation techniques, computational aspects, financial products, and risk management applications presented will enable readers to progress in the challenging field of computational finance.When the behavior of financial market participants changes, the corresponding stochastic mathematical models describing the prices may also change. Financial regulation may play a role in such changes too. The book thus presents several models for stock prices, interest rates as well as foreign-exchange rates, with increasing complexity across the chapters. As is said in the industry, 'do not fall in love with your favorite model.' The book covers equity models before moving to short-rate and other interest rate models. We cast these models for interest rate into the Heath-Jarrow-Morton framework, show relations between the different models, and explain a few interest rate products and their pricing.The chapters are accompanied by exercises. Students can access solutions to selected exercises, while complete solutions are made available to instructors. The MATLAB and Python computer codes used for most tables and figures in the book are made available for both print and e-book users. This book will be useful for people working in the financial industry, for those aiming to work there one day, and for anyone interested in quantitative finance. The topics that are discussed are relevant for MSc and PhD students, academic researchers, and for quants in the financial industry.Supplementary Material:Solutions Manual is available to instructors who adopt this textbook for their courses. Please contact [email protected].

Mathematical Dynamics of Economic Markets

Mathematical Dynamics of Economic Markets
Author: Alexei Krouglov
Publisher: Nova Publishers
Total Pages: 136
Release: 2006
Genre: Business & Economics
ISBN: 9781594545283

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In this new book the author, Alexi Krouglov, examines real business cycles, financial markets, and economic growth with various mathematical models. Real business cycles are examined with three different models: one product and one supplier, one product and two suppliers, and n-products with n-suppliers. Financial markets are examined with more complex models because more complex topics, such as inflation and the stock market, are involved. Economic growth is examined through mathematical models that are specifically concerned with trade and arbitrage.

Mathematical Modeling of Collective Behavior in Socio-Economic and Life Sciences

Mathematical Modeling of Collective Behavior in Socio-Economic and Life Sciences
Author: Giovanni Naldi
Publisher: Springer Science & Business Media
Total Pages: 437
Release: 2010-08-12
Genre: Mathematics
ISBN: 0817649468

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Using examples from finance and modern warfare to the flocking of birds and the swarming of bacteria, the collected research in this volume demonstrates the common methodological approaches and tools for modeling and simulating collective behavior. The topics presented point toward new and challenging frontiers of applied mathematics, making the volume a useful reference text for applied mathematicians, physicists, biologists, and economists involved in the modeling of socio-economic systems.

Discrete Models of Financial Markets

Discrete Models of Financial Markets
Author: Marek Capiński
Publisher: Cambridge University Press
Total Pages: 193
Release: 2012-02-23
Genre: Business & Economics
ISBN: 110700263X

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An excellent basis for further study. Suitable even for readers with no mathematical background.

Mathematical Modeling and Methods of Option Pricing

Mathematical Modeling and Methods of Option Pricing
Author: Lishang Jiang
Publisher: World Scientific
Total Pages: 344
Release: 2005
Genre: Science
ISBN: 9812563695

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From the perspective of partial differential equations (PDE), this book introduces the Black-Scholes-Merton's option pricing theory. A unified approach is used to model various types of option pricing as PDE problems, to derive pricing formulas as their solutions, and to design efficient algorithms from the numerical calculation of PDEs.