Book Description
Agent-based computational modeling is changing the face of social science. In Generative Social Science, Joshua Epstein argues that this powerful, novel technique permits the social sciences to meet a fundamentally new standard of explanation, in which one "grows" the phenomenon of interest in an artificial society of interacting agents: heterogeneous, boundedly rational actors, represented as mathematical or software objects. After elaborating this notion of generative explanation in a pair of overarching foundational chapters, Epstein illustrates it with examples chosen from such far-flung fields as archaeology, civil conflict, the evolution of norms, epidemiology, retirement economics, spatial games, and organizational adaptation. In elegant chapter preludes, he explains how these widely diverse modeling studies support his sweeping case for generative explanation.
This book represents a powerful consolidation of Epstein's interdisciplinary research activities in the decade since the publication of his and Robert Axtell's landmark volume, Growing Artificial Societies. Beautifully illustrated, Generative Social Science includes a CD that contains animated movies of core model runs, and programs allowing users to easily change assumptions and explore models, making it an invaluable text for courses in modeling at all levels.
Customer Reviews:
Annie Wu -- Book #2.......2007-08-10
I am a purchasing agent who buys books for my faculty, and as far as I know, this faculty member is very impressed with this book.
Excellent example of cross-disciplinary social science using theory.......2007-08-07
It's refreshing and exciting, in a quiet intellectual kind of way, to encounter a book that includes philosophy of science, music theory, Anasazi disappearance mysteries, ethnic cleansing, and an explanation of why CEOs exist. Josh has produced the book I've been wanting to read any time during the last 20 years, which have been a bit barren from the theory and modeling perspective in social science. He also makes clear the mathematical and philosophical basis of the agent-based approach, producing a baseline both for future work in the field and for competing paradigms such as systems dynamics, discrete simulations, and cellular automata (Wolfram's New Kind of Science), however incommensurable. I was particularly interested in the occasional use of probability modeling (negative exponential distributions generated through simple rules are a very interesting advance in understanding the waiting times between civil violence outbursts) and I'd love to see a deeper relationship established, say between Bayesian models of dynamic systems and agent-based models. Keep up the great work, Josh! Also, kudos to the publisher for the sheer quality of the book: excellent paper, great color plates, and priced to sell rather than as the work of art it is.
Excellent survey of the author's work.......2007-07-27
This book did a good job of introducing me to the current state of agent-based modeling. It also, perhaps inadvertently, highlighted some of the current weaknesses of the field. In particular, the models shown in each paper rarely shared common features, and there was little consistency in method.
Epstein argues persuasively that agent-based modeling is a tool, not a methodological approach, and you should no sooner expect consistent usage here than with differential calculus. That said, it was a bit disconcerting.
Also, while the goal espoused here was to use the bare minimum of constraints that retain explanatory power, I was disappointed that relevant work from other fields was often abstracted away. For example, a few models used social networks; but the networks presented were static, not dynamic, and were not built around power-law ratios. Such additional complexity may well have distracted from the main point; but it would have been nice to see at least some discussion of why the models were simplified.
Regardless, I was very pleased with the book and would highly recommend it.
A Landmark Publication.......2007-03-08
Josh Epstein's new Opus is a landmark publication in the emerging field of multiagent-based simulation of dynamic social systems. Since Josh is not only one of this still nascent (though burgeoning) field's ablest and most creative practitioners, but also among its most thoughtful critics, the reader of has two treats in store: (1) a generous, and wide-ranging, sampling of case studies (including social networks and evolution, population growth, emergence of economic classes, civil unrest, timing of retirement, the dynamics of adaptive organizations and the spread of infectious disease), and (2) a cogent "meta" discussion of what multiagent models ARE, ARE NOT and how (when their properties and limitations are *not* properly taken account of) they can easily be MISAPPLIED.
Far from suggesting that multiagent-based models are a panacea solution to all (or most) social dynamical systems, Josh's book carefully articulates the conditions for which such an approach IS (and is NOT) appropriate; an approach rarely taken by other, similar, overviews of the field. Indeed, the cogent philosophical discussion in Chapter One - alone! - in which the generativist's position is defined and put into a broader modeling/simulation context, is worth the price of admission; I have not seen a better "manifesto" of multiagent-based modeling elsewhere.
Finally, without taking away any of the inherent "beauty" (in the technical sense) of the often exaggerated concept of "emergence," Josh succeeds admirably in both defining the term, and de-mystifying it, stripping it of some of its unnecessary "quasi-mystical" baggage (at least as it is often portrayed in lay publications).
Anyone who is interested in understanding how agent models may be used to help explore the dynamics of social dynamical systems, should have this book firmly on top of their "must read" list! Josh has generously provided future generations of agent explorers their go-to source of both inspiration and ideas. Well done Josh!
Book Description
CO-PUBLISHED WITH TELOS This book provides a beautiful overview of what mathematics and MATHEMATICA¿ can do for finance. Sophisticated theories are presented in a rigorous but user-friendly, practical style, which, with the programming capabilities of MATHEMATICA, help the reader develop good intuition in real trading. Key features: Entire book is on cross-platform CD written in MATHEMATICA * quick introduction to MATHEMATICA provided * minimal prerequisites: good understanding of calculus and some differential equations * a highly original presentation of optimal portfolio diversification. The book is designed for instructors and students, and most importantly, will meet the everyday trading needs of the professional¿the analytically inclined individual investor who wants to solve various problems encountered when investing and trading in stocks and stock options.
Customer Reviews:
it is a very action orientied book.......2007-01-10
i am planning to carry out the elabaorated calculation and their variations in this book to develop my model based investment strategy.
Best book on the subject I've read!.......2007-01-03
I've read a lot about financial math (I'm a physicist and love mathematics). This book is a gift. Just the tips (and code) on using Mathematica to process the data are worth the price alone. I don't buy into the Efficient Market Hypothesis and this book delivers (section 8.2) on fast markets. He correctly looks at the cash balance, something most folks gloss over, and sets up the various symbolic and numerical solutions in a useful way. The language is a bit terse and the structure drove me nuts until I got into the swing of the rhythm of the flow. I am grateful for the language now - we get a detailed look into the mind of someone who just plain KNOWS this subject. The fact you get the whole book as a series of Mathematica notebooks which are executible is a real plus. A few quick changes to the code and you have YOUR problem well on the way to solution. It is practical, explicitly direct, charmingly theoretical and powerfully presented. The only problem is I want a second volume and I want it NOW!
Tough book but very useful.......2006-08-08
This book is merciless; very complex, very dense. It is also, however, extremely useful. If Stojanovic were to publish ten more books on the topic, he would probably revolutionize the use of Mathematica in finance. The enclosed CD was also useful; such things are usually worthless but in this case, the book contains so much code that it would not be practical to implement without a digital copy.
The book is certainly a bargain at $70.
Best Book on Finance I have ever read........2006-05-19
Its a tough read, but well worth it, most of the work is origional or is an origional take on what has been done before. A bit like what Hamilitonian mechanics is to Newtonian mechanics
Average customer rating:
- Somewhat dated...but still helpful
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Computational Economics and Finance: Modeling and Analysis with Mathematica (Economic & Financial Modeling with Mathematica)
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Mathematica for Microeconomics
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An Introduction to Programming with Mathematica, Third Edition
ASIN: 0387945180 |
Book Description
As with the first volume, Volume Two of
Economic and
Financial Modeling with Mathematica is edited by Hal Varian, and its contributors are carefully selected by him to assure a high quality, practical work reflecting the efforts and expertise of an international cadre of Mathematica users from the economic, financial, investments, quantitative business and operations research communities.
Customer Reviews:
Somewhat dated...but still helpful.......2002-01-19
For the reader well-versed in Mathematica and in economic theory, this book gives a fairly good overview of how Mathematica can be used to study mathematical economics and finance. It is also assumed in the articles in the book that the reader has a strong background in mathematics. Since the book was published in 1993, Mathematica has considerably expanded, with many new features that make some of the accompanying code in the book somewhat dated, but the notebooks can still be used beneficially.In addition, economic theory is currently making more use of symbolic programming, and financial analysis has exploded as an area which is now making heavy use of high-performance computing. Although Mathematica cannot compete from a performance standpoint with the needs of financial engineering, it still has an advantage from a didactic standpoint. I did not read all of the articles in the book, so my comments will be limited to the ones that I did.
The article on "Mathematica and Diffusions" is an overview of how to use Mathematica to do stochastic calculus. The Ito calculus is reviewed briefly, and the authors begin with constructing a Weiner process. The Mathematica package they employ and on the disk accompanying the book is not discussed in detail, but is merely used to simulate realizations of the process. Readers who want a more in-depth view will have to go over the code themselves. The authors use the package to generate realizations of Weiner processes that are correlated with each other, and show this correlation via Mathematica graphics. The Black-Scholes formula is derived using the standard self-financing trading strategy and ignoring transaction costs and dividends. The algebraic manipulations are done with Mathematica, and this obscures (a little) the underlying concepts behind the derivation of this important formula. Since data structures in Mathematica are essentially lists, the authors outline the construction of the data structure that could be used to represent a diffusion, namely a list consisting of five terms: the diffusion, Weiner process name, expression for the drift and dispersion, and the initial value. For the reader familiar with OO-programming, accessor functions are used to extract the components of this data structure. This is a nice move by the authors, for it is an example of how Mathematica can be used to emulate OO-programming.
The article "Itovsn3: Doing Stochastic Calculus with Mathematica" is an overview of how to use the Itovsn3 package that is on the disk to implement Ito calculus. It is assumed that the reader has a background in stochastic calculus, since the author does not give a review. However, semimartingales, so important to those working in financial engineering, are discussed and their statistical behavior described using Mathematica. The Ito formula is presented as a semimartingale-type decomposition for smooth function of Brownian motion and the author shows using Mathematica plots how the higher order terms in the second-order Taylor expansion vanish asymptotically. This article is not merely Mathematica code for Ito calculus, for the author gives an example of how to use the package in a hedging problem.
The article "Option Valuation" is a more detailed overview of how to use Mathematica in the context of the Black-Scholes model to perform options valuation and risk management. Heavy use is made of the graphics capability of Mathematica to illustrate how option values change as a function of stock price and time of expiration. The author also shows how Mathematica can be used as a OO-language to treat options as self-contained objects with accessor functions. He does however state that Mathematica does not live up to the OO toolkits available elsewhere, contrary to my experience. He closes the article with a consideration of how to use Mathematica to value options that can be exercised before expiry, the binomial model playing the central role in the discussion. It is here in particular that the performance of Mathematica is readily felt. The numerical number-crunching needed to do the calculations in these types of models cannot be done in Mathematica efficiently and profitably.
The article "Time Series Models and Mathematica" gives a general treatment on how Mathematica can be used to study ARIMA models for time series. Mathematica is used more interactively than the other articles and the visualization obtained is quite nice in giving the reader insight into such concepts as the moving average and the spectral density function. The author shows how to estimate the spectral density function and why periodogram techniques fall short in this estimation. I would have liked to see other techniques for studying time series discussed, such as neural networks and hidden Markov models, but the author does do a fairly good job with the ARIMA models.
Book Description
This book presents a variety of computational methods used to solve dynamic problems in economics and finance. It emphasizes practical numerical methods rather than mathematical proofs and focuses on techniques that apply directly to economic analyses. The examples are drawn from a wide range of subspecialties of economics and finance, with particular emphasis on problems in agricultural and resource economics, macroeconomics, and finance. The book also provides an extensive Web-site library of computer utilities and demonstration programs.
The book is divided into two parts. The first part develops basic numerical methods, including linear and nonlinear equation methods, complementarity methods, finite-dimensional optimization, numerical integration and differentiation, and function approximation. The second part presents methods for solving dynamic stochastic models in economics and finance, including dynamic programming, rational expectations, and arbitrage pricing models in discrete and continuous time. The book uses MATLAB to illustrate the algorithms and includes a utilities toolbox to help readers develop their own computational economics applications.
Customer Reviews:
I've looked elsewhere and...others are worse.......2007-10-06
I bought this book b/c its required for a course I'm taking; my professor is one of the authors. Coding is a pain regardless of how good your instruction is, so I'm hesitant to criticize the book. That said, I didn't love it. However, I've looked at other books and this is by far the most relevant for using MATLAB for econ and finance.
Good but ..........2006-03-26
I was looking for a book that teaches how to use MATLAB to solve certain finance and economics problems, and purchased this book. The book covers very interesting topics and discusses many types of solution methods. However, the applications to MATLAB are not presented in a user-friendly way. In particular, they do not present things in a step-by-step manner and assume many things. The reader is then left to figure out how to complete programs either from some other part of the book or from prior knowledge. Thus, the book is successful in letting the reader become aware of the capabilities of MATLAB (i.e. what sort of computational techniques the program can do). However, it would havae been best if the authors wrote all the programs with complete codes. They often mention that the code assumes that the reader does this and does that.
Excellent for economists and financial analysts.......2004-07-16
This is one of the few books that covers the topics of numerical methods to solve finance and economics problems. It provides a large number of generic applications.
Readers that can use Matlab will especially benefit. If so, be sure to get the author's toolbox and see the errata on the author's page.
There are two other books that might be useful to those interested in this text: Dixit and Pindyck's Investment Under Uncertainty (1994), and Patrick Anderson's Business Economics and Finance (2004) [my book], which cites the Dixit and Miranda texts.
Readers should be prepared for some math, although it is much more accessible here than in most graduate texts in financial mathematics.
Fantastic book!.......2003-09-17
This book is a must for economists or financial engineers. I used the book in a course and refer to it often now that I work in the industry. The Matlab examples are also excellent.
Book Description
After a decade of development, genetic algorithms and genetic programming have become a widely accepted toolkit for computational finance.
Genetic Algorithms and Genetic Programming in Computational Finance is a pioneering volume devoted entirely to a systematic and comprehensive review of this subject. Chapters cover various areas of computational finance, including financial forecasting, trading strategies development, cash flow management, option pricing, portfolio management, volatility modeling, arbitraging, and agent-based simulations of artificial stock markets. Two tutorial chapters are also included to help readers quickly grasp the essence of these tools. Finally, a menu-driven software program, Simple GP, accompanies the volume, which will enable readers without a strong programming background to gain hands-on experience in dealing with much of the technical material introduced in this work.
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Network Economics: A Variational Inequality Approach (Advances in Computational Economics)
A. Nagurney
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The second and revised edition of Network Economics: A Variational Inequality Approach provides an updated treatment of network economics through the inclusion of new theoretical results and new applications, as well as problems for self-study purposes and/or for use in the classroom. This volume remains true to the first edition in that it provides a unified treatment of finite-dimensional variational inequalities, algorithms, and applications. Physical networks are pervasive in today's society in the form of transportation networks, telecommunication networks, energy networks, and financial networks, whereas mathematical networks provide a mechanism for studying a plethora of economic equilibrium problems through a common graphic structure. Network Economics establishes the connections among economic equilibrium problems through their network structure and demonstrates how the structure can then be used to address policy interventions, as well as to construct efficient numerical schemes for the computation of equilibria. The network framework provides not only a mechanism for the graphic representation of economic problems and a means for visualizing their similarities and differences, but, in addition, a novel theoretical approach. Problems treated include: congested transportation systems, oligopolistic market equilibrium problems, problems of human migration, and general financial and economic equilibrium problems. New applications covered in this second edition include environmental networks and knowledge networks.
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Optimal Control Models in Finance: A New Computational Approach (Applied Optimization)
Ping Chen , and
Sardar M.N. Islam
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ASIN: 0387235698 |
Book Description
The determination of optimal financing and investment strategies (optimal capital structure or optimal mix of funds, optimal portfolio choice, etc.) for corporations and the economy are important for efficient allocation of resources in the economy. Optimal control methods have useful applications to these areas in finance - some optimization problems in finance include optimal control, involving a dynamic system with switching times in the form of bang-bang control. Optimal control models for corporate finance and the economy are presented in this book and the analytical and computational results of these models are also reported. Such computational approaches to the study of optimal corporate financing are not well known in the existing literature. This book develops a new computational method where switching times are considered as variables in the optimal dynamic financial model represented by a second order differential equation. A new computer program named CSTVA (Computer Program for the Switching Time Variables Algorithm), which can compute bang-bang optimal financial models with switching time, is also developed. Optimal financing implications of the model results in the form of optimal switching times for changes in financing policies and the optimal financial policies are analyzed.
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Agent-Based Methods in Economics and Finance (Advances in Computational Economics)
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ASIN: 0792374193 |
Book Description
This volume on financial and economic simulations in Swarm marks the continued progress by a group of researchers to incorporate agent-based computer models as an important tool within their discipline.
Swarm promotes agent-based computer models as a tool for the study of complex systems. A common
language is leading to the growth of user communities in specific areas of application. Furthermore, by providing an organizing framework to guide the development of more problem-specific structures, and by dealing with a whole range of issues that affect their fundamental correctness and their ability to be developed and reused, Swarm has sought to make the use of agent-based models a legitimate tool of scientific investigation that also meets the practical needs of investigators within a community.
Swarm's principal foundation is an object-oriented representation of active agents interacting among themselves and with their environment. To this base layer it adds its own structures to drive, record and portrait the events that occur across this world. The specific contents of any world, however, are up to the experimenter to provide, either by building them from scratch or by tapping previous contributions.
This book is notable in assembling a rich array of such contributions, which are significant in their own right, but which can also be mined to extract the reusable elements in their respective areas of finance and economics. It also presents three interesting software additions with tutorials in the form of simple financial and economic applications. A Swarm meta-language closer to a `natural language', the use of internet-augmented Swarm for experimental economics, and a Swarm visual builder will meet the challenges launched by other agent-based modelling competitors.
The Swarm community at large can benefit greatly from the lead that the growing field of computational economics is taking to address its own needs, as represented by this book.
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Agent-Based Computer Simulation of Dichotomous Economic Growth (ADVANCES IN COMPUTATIONAL ECONOMICS Volume 13) (Advances in Computational Economics)
Roger A. McCain
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ASIN: 0792386884 |
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Agent-Based Computer Simulation of Dichotomous Economic Growth reports a project in agent-based computer stimulation of processes of economic growth in a population of boundedly rational learning agents.
The study is an exercise in comparative simulation. That is, the same family of growth models will be simulated under different assumptions about the nature of the learning process and details of the production and growth processes. The purpose of this procedure is to establish a relationship between the assumptions and the simulation results.
The study brings together a number of theoretical and technical developments, only some of which may be familiar to any particular reader. In this first chapter, some issues in economic growth are reviewed and the objectives of the study are outlined. In the second chapter, the simulation techniques are introduced and illustrated with baseline simulations of boundedly rational learning processes that do not involve the complications of dealing with long-run economic growth. The third chapter sketches the consensus modern theory of economic growth which is the starting point for further study. In the fourth chapter, a family of steady growth models are simulated, bringing the simulation, growth and learning aspects of the study together. In subsequent chapters, variants on the growth model are explored in a similar way. The ninth chapter introduces trade, with a spacial trading model that is combined with the growth model in the tenth chapter.
The book returns again and again to the key question: to what extent can the simulations `explain' the puzzles of economic growth, and particularly the key puzzle of dichotomization, by constructing growth and learning processes that produce the puzzling results? And just what assumptions of the simulations are most predictable associated with the puzzling results?
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Analyses in Macroeconomic Modelling (ADVANCES IN COMPUTATIONAL ECONOMICS Volume 12) (Advances in Computational Economics)
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ASIN: 0792385985 |
Book Description
Macroeconomic Modelling has undergone radical changes in the last few years. There has been considerable innovation in developing robust solution techniques for the new breed of increasingly complex models. Similarly there has been a growing consensus on their long run and dynamic properties, as well as much development on existing themes such as modelling expectations and policy rules. This edited volume focuses on those areas which have undergone the most significant and imaginative developments and brings together the very best of modelling practice.
We include specific sections on (I) Solving Large Macroeconomic Models, (II) Rational Expectations and Learning Approaches, (III) Macro Dynamics, and (IV) Long Run and Closures. All of the contributions offer new research whilst putting their developments firmly in context and as such will influence much future research in the area. It will be an invaluable text for those in policy institutions as well as academics and advanced students in the fields of economics, mathematics, business and government. Our contributors include those working in central banks, the IMF, European Commission and established academics.
Books:
- George Soros on Globalization
- Getting Things Done: The Art of Stress-Free Productivity
- Global Civil Society: An Answer to War
- Global Strategy (with World Map and InfoTrac )
- Green to Gold: How Smart Companies Use Environmental Strategy to Innovate, Create Value, and Build Competitive Advantage
- History: Fiction or Science? (Chronology, No. 1)
- History: Fiction or Science? (Chronology, No. 1)
- History: Fiction or Science? (Chronology, No. 1)
- History: Fiction or Science? (Chronology, No. 1)
- How Industries Evolve: Principles for Achieving and Sustaining Superior Performance
Books Index
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