John Barnes' collection of essays, published over the past forty years, covers a variety of topics in sociology and anthropology, including lineage systems, social networks, colonialism, underlying assumptions of social science, and the significance of time in social analysis. Together they identify the author's particular view of social science as being primarily about what really happens. Rather than revamp articles written with a distinctive set of assumptions to bring them into line with current intellectual fashions, Professor Barnes has chosen to let them stand as they are, products of identifiable theoretical stances and modes of exposition. But introductory notes to each chapter explain the context in which the piece was originally written and draw attention to later publications and events that bear on it. A new introduction discusses in detail the author's view of social science as the construction of models rather than a search for social laws, while the final chapter presents a model of the modeling process itself.
This book presents a radically new approach to problems of evaluating and optimizing the performance of continuous-time stochastic systems. This approach is based on the use of a family of Markov processes called Piecewise-Deterministic Processes (PDPs) as a general class of stochastic system models. A PDP is a Markov process that follows deterministic trajectories between random jumps, the latter occurring either spontaneously, in a Poisson-like fashion, or when the process hits the boundary of its state space. This formulation includes an enormous variety of applied problems in engineering, operations research, management science and economics as special cases; examples include queueing systems, stochastic scheduling, inventory control, resource allocation problems, optimal planning of production or exploitation of renewable or non-renewable resources, insurance analysis, fault detection in process systems, and tracking of maneuvering targets, among many others.
"I've worked with simulation in business for over 20 years, and Allman really nails it with this book. I admit that I own his previous book on structured finance cash flows, but I was surprised by what I found in here. He addresses the fundamental questions of how decision makers react to simulations and his read was very much in accordance with what I've experienced myself. When it came to the nuts and bolts of describing the different types of simulation analysis the book becomes incredibly detailed. There is working code and models for a fantastic array of the most common simulation problems. If you're so inclined, the book very carefully steps through the tricky math needed to really understand the theory behind stochastic modeling in finance. If you're preparing models that include any kind of randomization or stochastic modeling component, this book is a must-read, a tremendous value and time-saver." ? David Brode of The Brode Group
A practical guide to understanding and implementing financial simulation modeling
As simulation techniques become more popular among the financial community and a variety of sub-industries, a thorough understanding of theory and implementation is critical for practitioners involved in portfolio management, risk management, pricing, and capital budgeting. Financial Simulation Modeling in Excel contains the information you need to make the most informed decisions possible in your professional endeavors.
Financial Simulation Modeling in Excel contains a practical, hands-on approach to learning complex financial simulation methodologies using Excel and VBA as a medium. Crafted in an easy to understand format, this book is suitable for anyone with a basic understanding of finance and Excel. Filled with in-depth insights and expert advice, each chapter takes you through the theory behind a simulation topic and the implementation of that same topic in Excel/VBA in a step-by-step manner.
Created for those with some background in finance and experience in Excel, this reliable resource shows you how to effectively perform sound financial simulation modeling, even if you've yet to do extensive modeling up to this point in your professional or academic career.
This is a Cute Fun Comic Book Especially for Those of You That need to get a good Laugh.
Mathematical Models of Distribution Channels identifies eight "Channel Myths" that characterize almost all analytical research on distribution channels. The authors prove that models that incorporate one or more Channel Myths generate distorted conclusions; they also develop a methodology that will enable researchers to avoid falling under the influence of any Channel Myth.
At the heart of their analysis is a single-manufacturer/multiple-retailer meta-model that embraces any degree of inter-retailer competition and any distribution of market shares. In Chapters 1 and 2 the authors provide an introduction to the current, analytical literature on distribution channels, and they present an intuitively appealing prologue to the Channel Myths that are developed rigorously in later Chapters. In Chapters 3, 4, and 10 they extend the literature by ascertaining the relationship between the manufacturer-optimal wholesale-price strategy and channel breadth. Specific analyses include multiple, non-competing retailers, multiple states-of-nature, and multiple, competing retailers. In Chapters 5-7 the authors determine the profitability of various wholesale-price strategies; this analysis culminates in Chapters 8 and 9 with the determination of the (very limited) conditions under which channel coordination can be optimal for the manufacturer. In Chapter 11 they prove that existing methods of measuring the effect of a change in the degree of inter-retailer substitutability are totally misleading. They then develop an original, theoretical basis for measuring the impact of a change in the degree of inter-retailer substitutability that yields insightful, intuitively appealing results. In Chapter 12 the authors set forth an agenda for future research based on a meta-model that embraces all existing models in the literature. They also issue an appeal for creation of a "Unifying Theory of Distribution Channels" that will enable researchers to work independently and yet to contribute toward the common goal of deepening the marketing science professions understanding of distribution channels."
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