Modeling Markets
Modeling Markets

Author: Peter S.H. Leeflang

Publisher: Springer

Published: 2014-11-12

Total Pages: 417

ISBN-13: 1493920863

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This book is about how models can be developed to represent demand and supply on markets, where the emphasis is on demand models. Its primary focus is on models that can be used by managers to support marketing decisions. Modeling Markets presents a comprehensive overview of the tools and methodologies that managers can use in decision making. It has long been known that even simple models outperform judgments in predicting outcomes in a wide variety of contexts. More complex models potentially provide insights about structural relations not available from casual observations. In this book, the authors present a wealth of insights developed at the forefront of the field, covering all key aspects of specification, estimation, validation and use of models. The most current insights and innovations in quantitative marketing are presented, including in-depth discussion of Bayesian estimation methods. Throughout the book, the authors provide examples and illustrations. This book will be of interest to researchers, analysts, managers and students who want to understand, develop or use models of marketing phenomena.

Advanced Methods for Modeling Markets
Advanced Methods for Modeling Markets

Author: Peter S. H. Leeflang

Publisher: Springer

Published: 2017-08-29

Total Pages: 725

ISBN-13: 3319534696

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This volume presents advanced techniques to modeling markets, with a wide spectrum of topics, including advanced individual demand models, time series analysis, state space models, spatial models, structural models, mediation, models that specify competition and diffusion models. It is intended as a follow-on and companion to Modeling Markets (2015), in which the authors presented the basics of modeling markets along the classical steps of the model building process: specification, data collection, estimation, validation and implementation. This volume builds on the concepts presented in Modeling Markets with an emphasis on advanced methods that are used to specify, estimate and validate marketing models, including structural equation models, partial least squares, mixture models, and hidden Markov models, as well as generalized methods of moments, Bayesian analysis, non/semi-parametric estimation and endogeneity issues. Specific attention is given to big data. The market environment is changing rapidly and constantly. Models that provide information about the sensitivity of market behavior to marketing activities such as advertising, pricing, promotions and distribution are now routinely used by managers for the identification of changes in marketing programs that can improve brand performance. In today’s environment of information overload, the challenge is to make sense of the data that is being provided globally, in real time, from thousands of sources. Although marketing models are now widely accepted, the quality of the marketing decisions is critically dependent upon the quality of the models on which those decisions are based. This volume provides an authoritative and comprehensive review, with each chapter including: · an introduction to the method/methodology · a numerical example/application in marketing · references to other marketing applications · suggestions about software. Featuring contributions from top authors in the field, this volume will explore current and future aspects of modeling markets, providing relevant and timely research and techniques to scientists, researchers, students, academics and practitioners in marketing, management and economics.

Modeling Financial Markets
Modeling Financial Markets

Author: Benjamin Van Vliet

Publisher: McGraw Hill Professional

Published: 2004-01-22

Total Pages: 400

ISBN-13: 007144288X

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Limitations in today's software packages for financial modeling system development can threaten the viability of any system--not to mention the firm using that system. Modeling Financial Markets is the first book to take financial professionals beyond those limitations to introduce safer, more sophisticated modeling methods. It contains dozens of techniques for financial modeling in code that minimize or avoid current software deficiencies, and addresses the crucial crossover stage in which prototypes are converted to fully coded models.

Mathematical Modelling of Contemporary Electricity Markets
Mathematical Modelling of Contemporary Electricity Markets

Author: Athanasios Dagoumas

Publisher: Academic Press

Published: 2021-01-30

Total Pages: 444

ISBN-13: 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

The Oxford Handbook of Computational Economics and Finance
The Oxford Handbook of Computational Economics and Finance

Author: Shu-Heng Chen

Publisher: Oxford University Press

Published: 2018-01-12

Total Pages: 785

ISBN-13: 0190877502

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The Oxford Handbook of Computational Economics and Finance provides a survey of both the foundations of and recent advances in the frontiers of analysis and action. It is both historically and interdisciplinarily rich and also tightly connected to the rise of digital society. It begins with the conventional view of computational economics, including recent algorithmic development in computing rational expectations, volatility, and general equilibrium. It then moves from traditional computing in economics and finance to recent developments in natural computing, including applications of nature-inspired intelligence, genetic programming, swarm intelligence, and fuzzy logic. Also examined are recent developments of network and agent-based computing in economics. How these approaches are applied is examined in chapters on such subjects as trading robots and automated markets. The last part deals with the epistemology of simulation in its trinity form with the integration of simulation, computation, and dynamics. Distinctive is the focus on natural computationalism and the examination of the implications of intelligent machines for the future of computational economics and finance. Not merely individual robots, but whole integrated systems are extending their "immigration" to the world of Homo sapiens, or symbiogenesis.

Financial Modelling in Commodity Markets
Financial Modelling in Commodity Markets

Author: Viviana Fanelli

Publisher: CRC Press

Published: 2020-01-14

Total Pages: 145

ISBN-13: 1351730959

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Financial Modelling in Commodity Markets provides a basic and self-contained introduction to the ideas underpinning financial modelling of products in commodity markets. The book offers a concise and operational vision of the main models used to represent, assess and simulate real assets and financial positions related to the commodity markets. It discusses statistical and mathematical tools important for estimating, implementing and calibrating quantitative models used for pricing and trading commodity-linked products and for managing basic and complex portfolio risks. Key features: Provides a step-by-step guide to the construction of pricing models, and for the applications of such models for the analysis of real data Written for scholars from a wide range of scientific fields, including economics and finance, mathematics, engineering and statistics, as well as for practitioners Illustrates some important pricing models using real data sets that will be commonly used in financial markets

Complementarity Modeling in Energy Markets
Complementarity Modeling in Energy Markets

Author: Steven A. Gabriel

Publisher: Springer Science & Business Media

Published: 2012-07-20

Total Pages: 637

ISBN-13: 1441961232

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This addition to the ISOR series introduces complementarity models in a straightforward and approachable manner and uses them to carry out an in-depth analysis of energy markets, including formulation issues and solution techniques. In a nutshell, complementarity models generalize: a. optimization problems via their Karush-Kuhn-Tucker conditions b. on-cooperative games in which each player may be solving a separate but related optimization problem with potentially overall system constraints (e.g., market-clearing conditions) c. conomic and engineering problems that aren’t specifically derived from optimization problems (e.g., spatial price equilibria) d. roblems in which both primal and dual variables (prices) appear in the original formulation (e.g., The National Energy Modeling System (NEMS) or its precursor, PIES). As such, complementarity models are a very general and flexible modeling format. A natural question is why concentrate on energy markets for this complementarity approach? s it turns out, energy or other markets that have game theoretic aspects are best modeled by complementarity problems. The reason is that the traditional perfect competition approach no longer applies due to deregulation and restructuring of these markets and thus the corresponding optimization problems may no longer hold. Also, in some instances it is important in the original model formulation to involve both primal variables (e.g., production) as well as dual variables (e.g., market prices) for public and private sector energy planning. Traditional optimization problems can not directly handle this mixing of primal and dual variables but complementarity models can and this makes them all that more effective for decision-makers.

Statistical Models and Methods for Financial Markets
Statistical Models and Methods for Financial Markets

Author: Tze Leung Lai

Publisher: Springer Science & Business Media

Published: 2008-09-08

Total Pages: 363

ISBN-13: 0387778276

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The idea of writing this bookarosein 2000when the ?rst author wasassigned to teach the required course STATS 240 (Statistical Methods in Finance) in the new M. S. program in ?nancial mathematics at Stanford, which is an interdisciplinary program that aims to provide a master’s-level education in applied mathematics, statistics, computing, ?nance, and economics. Students in the programhad di?erent backgroundsin statistics. Some had only taken a basic course in statistical inference, while others had taken a broad spectrum of M. S. - and Ph. D. -level statistics courses. On the other hand, all of them had already taken required core courses in investment theory and derivative pricing, and STATS 240 was supposed to link the theory and pricing formulas to real-world data and pricing or investment strategies. Besides students in theprogram,thecoursealso attractedmanystudentsfromother departments in the university, further increasing the heterogeneity of students, as many of them had a strong background in mathematical and statistical modeling from the mathematical, physical, and engineering sciences but no previous experience in ?nance. To address the diversity in background but common strong interest in the subject and in a potential career as a “quant” in the ?nancialindustry,thecoursematerialwascarefullychosennotonlytopresent basic statistical methods of importance to quantitative ?nance but also to summarize domain knowledge in ?nance and show how it can be combined with statistical modeling in ?nancial analysis and decision making. The course material evolved over the years, especially after the second author helped as the head TA during the years 2004 and 2005.

Modelling Prices in Competitive Electricity Markets
Modelling Prices in Competitive Electricity Markets

Author: Derek W. Bunn

Publisher: John Wiley & Sons

Published: 2004-04-02

Total Pages: 368

ISBN-13:

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Electricity markets are structurally different to other commodities, and the real-time dynamic balancing of the electricity network involves many external factors. Because of this, it is not a simple matter to transfer conventional models of financial time series analysis to wholesale electricity prices. The rationale for this compilation of chapters from international authors is, therefore, to provide econometric analysis of wholesale power markets around the world, to give greater understanding of their particular characteristics, and to assess the applicability of various methods of price modelling. Researchers and professionals in this sector will find the book an invaluable guide to the most important state-of-the-art modelling techniques which are converging to define the special approaches necessary for unravelling and forecasting the behaviour of electricity prices. It is a high-quality synthesis of the work of financial engineering, industrial economics and power systems analysis, as they relate to the behaviour of competitive electricity markets.

Modelling Spatial Housing Markets
Modelling Spatial Housing Markets

Author: Geoffrey Meen

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 279

ISBN-13: 1461516730

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Spatial fixity is one of the characteristics that distinguishes housing from most other goods and services in the economy. In general, housing cannot be moved from one part of the country to another in response to shortages or excesses in particular areas. The modelling of housing markets and the interlinkages between markets at different spatial levels - international, national, regional and urban - are the main themes of this book. A second major theme is disaggregation, not only in terms of space, but also between households. The book argues that aggregate time-series models of housing markets of the type widely used in Britain and also in other countries in the past have become less relevant in a world of increasing income dispersion. Typically, aggregate relationships will break down, except under special conditions. We can no longer assume that traditional location or tenure patterns, for example, will continue in the future. The book has four main components. First, it discusses trends in housing markets both internationally and within nations. Second, the book develops theoretical housing models at each spatial scale, starting with national models, moving down to the regional level and, then, to urban models. Third, the book provides empirical estimates of the models and, finally, the models are used for policy analysis. Analysis ranges over a wide variety of topics, including explanations for differing international house price trends, the causes of housing cycles, the role of credit markets, regional housing market interactions and the role of housing in urban/suburban population drift.