Modeling Software Markets

As social beings, humans are not living in isolation but rather interact and communicate within their social network via language, meant to convey parts of some conceptualization from the sender to a single recipient or a set of recipients. Communities of agents not only share a common language but also the individual conceptualizations of the world (real and abstract) have to overlap to a significant extent, allowing for efficient reference to whole conceptual structures like "the German constitution", "game theory" or "medical sciences". For "societies" of interacting technical devices or software agents the situation is not quite as Babylonian since although these agents are meant to act individually (and also have a private state and private knowledge) in most cases they are designed to refer to one common ontology or standardized protocol and thus do not have to deal with misunderstanding. However, the more these systems become interconnected, the more this situation resembles the one described for societies of human agents even though the misunderstanding might be easier to detect when the different reference ontologies are made explicit and published. Obviously, in both cases standardization of a common language or set of rules for interaction reduces the individual degree of freedom for the sake of compatibility and benefits derived from interaction. In his work, Falk Graf von Westarp addresses the software market as a domain strongly depending on compatibility effects of the individuals' decisions.

The customer base is an important value driver of software companies and a reliable prediction of its development is fundamental for investment decisions. A particularity in software markets is that an individual’s purchasing decision is often influenced by other users’ choices. Although such customer network effects are evident, their quantitative assessment remain elusive with conventional approaches. This book contributes to closing this gap by developing methods for measuring network effects and their implications for valuation in software markets. Based on the theory of complex networks the book reveals that such diffusion processes highly depend on structural properties of customer networks. Moreover, it depicts that such insights are contributions to improve the quality of valuations in software markets. But the implications of this research also comprise social and political aspects as they can be applied in order to prevent corporate failures in all network effect markets.

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.

"This book provides a clear and simple framework to help software companies understand enterprise-level information systems, and help them build software products compatible with organizations, humans, and complex customer environments"--Provided by publisher.

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.

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.

This pioneering book describes the applications of agent-based modeling to financial markets. It presents a new paradigm for finance, where markets are treated as complex systems whose behavior emerges as a result of interactions of market participants, market institutions, and market rules. This includes both a presentation of the conceptual model and its software implementation. It also summarises the result of the profound research on the successful practical application of this new approach to answer questions regarding the Nasdaq Stock MarketOCOs decimalization that was implemented in 2001. The book presents conceptual foundations for modeling markets as complex systems. It describes the agent-based model of the Nasdaq stock market, including strategies used by market-makers and investors, market participants interactions, and impacts of rules and regulations. It includes analyses of simulation behavior, comparison with the behaviors observed in the real-world markets (existence of fat tails, spread clustering, etc.), and predictions about possible outcomes of decimalization. A framework for calibrating the market behavior and individual market-makers strategies to historical data is also presented."