Book Description
The main difference between this text and many others is that an attempt is made here to present material in a rather relaxed and informal way without omitting important concepts. The text demonstrates the wide range of relevant issues and questions that can be addressed with the help of statistical analysis techniques by presenting over 1,750 realistic problems that arise often in health care, the social and physical sciences, education, business and economics, engineering, and leisure activities. It also convinces your students that statistics is "do-able" by including real data that students have collected and analyzed for class assignments and projects. Additionally, the text utilizes an intuitive, common sense approach (including occasional humorous situation or ridiculous name) to develop concepts whenever possible. Statistics: A First Course employs widely available, inexpensive technologies--particularly Minitab and the TI-83 graphing calculator. We also explore the use of the World Wide Web to collect data, providing students with the means to obtain up-to-date information without leaving their desks.
In short this book is written to communicate with students rather than to lecture to them, and its intent is to convince readers that the study of statistics can be a lively, interesting, and rewarding experience!
Customer Reviews:
You don't need to be afraid of Statistics.......2000-12-15
This is a very friendly statistics book. It is easy to read and understand. The authors also throw in some humorous comments now and then that is something you wouldn't expect to find in a statistics book and this seemed to help with the reading. Many real world business examples are used in the book. The example problems and the end of section or chapter problems are from different areas of study such as business, political, social sciences, and science. This is great for understanding how to apply statistics in real life. I would have to say that all the topics and formulas are explained very well. In some cases there are more then one way to write a formula and Sanders and Smidt makes a point of giving you both formulas. You can decide which formula works for you. The book comes with a CD loaded with the data files for all the problems so you don't have to spend time keying in data. There are copies of the data files come in a variety of formats such as Minitab, Excel Windows, and Macintosh. For most of the example problems the book takes you through the steps using Minitab Statistical software and the TI-83 graphing calculator. You are not only learning statistics, but you are also learning how to use Minitab and the TI-83 graphing calculator. In this day and age if you are going to do statistics you need to be able to do it with a computer. I wish they would have also included examples using Microsoft Excel, which more people are apt to have then Minitab. Personally I use both Minitab and Excel. I actually enjoyed reading this book and looked forward to studying. Even though my statistics class is over this book will not be collecting dust for a while as I plan on going back through it to reread or finish reading what I missed or skimmed over. There are still a lot of the problems that I want to do to reinforce what I have already learned. This is a great statistics book to keep as a reference. More then once I have found coworkers looking up stuff in my book.
Book Description
Standard texts and research in economics and finance ignore the absence of evidence from the analysis of real, unmassaged market data to support the notion of Adam Smith's stabilizing Invisible Hand. In stark contrast, this text introduces a new empirically-based model of financial market dynamics that explains the volatility of prices options correctly and clarifies the instability of financial markets. The emphasis is on understanding how real markets behave, not how they hypothetically 'should' behave.
Customer Reviews:
So what? .......2007-03-26
I am a 3rd year PhD student in Financial Economics, and although I should confess that I only browsed the book, not having fully read it (sorry about that...), I must say that this approach totally misses the target. I recommend anyone who is interested in knowing why to look up the following book review:
[...]
Have fun.
Good summary of the literature.......2007-01-10
I think this book is nicely written and covers a variety of subjects. What I missed while reading it was more applied examples.
McCauley complements Keynes and Mandelbrot.......2005-02-01
McCauley's(M) book definitely should be in the library of any technically trained (BA or BS degree in mathematics or statistics and a BA or BS in economics or finance) reader who is aware of the constant failure of neoclassical economics(and its modern variates such as rational expectations,real business cycle theory,monetarism,or supplyside economics), econometrics(Tinbergen,Frisch,Haavelmo and ,unfortunately,"Keynesian"econometricians like Modigliani,Tobin,Klein,and Solow) and financial analysts(Fama,Black,Merton,Scholes,Sharpe,Osborne,Markowitz and Cootner)to explain and forecast turning points in the business cycles of various countries and/or turning points in various financial markets(stock,commodity,real estate,currency,bond,money or derivatives)at any time in the last century,at least,using the assumption of normality(normal,lognormal,bivariate normal,multivariate normal,approximately normal,etc.).M presents a stochastic model based on the application of Green's Theorem to predict the future values of different options contracts(pp.180-192)that avoids the incorrect assumption of normality.M emphasizes changes in returns,as opposed to changes in prices a la Mandelbrot(pp.73-75).Again, the incorrect assumption of normality is avoided.This reviewer views these developments as occurring within the framework established by Mandelbrot no later than 1966.M is developing and improving aspects of Mandelbrot's general approach.However,there are three areas of M's book that need to be revised in a future edition.The first is his analysis of the classical-neoclassical concept of equilibrium and the process of adjustment involved over time.The argument made by neoclassical economists is that the economy( and all markets)is self equilibrating and always tending to or converging toward the optimal equilibrium point,although in point of fact,due to a constant set of external shocks,this equilibrium position is never reached.Thus, all short-run transactions may or may not be made at disequilibrium prices with no recontracting possible.The result,in the short run,is non optimal.However, in the long run,all of the losses and/or gains from such disequilibrium positions cancel or average out so that the resulting process can be analyzed "as if" the different markets were actually attaining equilibriums.Of course,all changes in market prices are assumed to be normally distributed around the equilibrium,market clearing price which is the average(arithmetic mean)of a normal probability distribution.This argument also is incorrect,but is much more difficult to refute since it is much more sophisticated ,using(misusing)the law of large numbers and the central limit theorem without ever actually examining the basic data.M needs to fine tune his basically sound critique to deal with the more sophisticated version of the neoclassical argument.If he does not,the neoclassical response will be that he does not understand microeconomic price theory.Second, Mandelbrot should not be bracketed with the likes of Markowitz Osborne,Sharpe,Black,Scholes,Merton,etc., on p.4 .Mandelbrot has, in fact,been clearly opposed,since the early 1960's, to the type of theoretical and statistical analysis and result that has been published by this group of economists and financial analysts.Third,M appears to have never read Keynes's A Treatise on Probability(1921;TP) or the 1939-40 exchange between Tinbergen and Keynes over the logical foundations of the basic econometric technique of multiple regression and correlation analysis ,as it regards forecasting of the business cycle.Keynes's complete argument can be found in chapter 17,pp.205-214,and chapters 29,30, 32,and 33 of the TP.Keynes always argued that,outside of the fields of life and physical science,the normal distribution was rather special and limited in application. The use of it required clearcut empirical testing of the data before normality could be assumed.Finally,Keynes's analytic tool in the General Theory(1936) is to show that the general case in macroeconomics is the existence of multiple stable equiibria.This describes the commodity or output market.The labor market is a function of changes in the commodity market.The labor market is in a state of constant disequilibrium,equilibrium only possibly occurring in the special case of a global optimum being obtained in the commodity market.M is correct that the analysis in most markets should be based on excess demand functions.Keynes arrived at this approach in 1936.A set of D=Z functions(functions clearly defined by Keynes in the GT and analyzed by Keynes in chapters 20 and 21 of the GT) define a locus of points that Keynes called the AGGREGATE SUPPLY CURVE.Only one of these points gives a global optimum.The economics profession has made a bloody mess of Keynes's mathematical analysis since the publication of the GT in 1936,constantly confusing the expected aggregate supply function,Z,with the aggregate supply curve,D=Z.M's treatment of Keynes is deficient and needs to be fixed in a later edition.A complete mathematical analysis of Keynes's theory of effective demand is contained in Brady(2004),"Essays on JM Keynes and..."
Some strengths, some weaknesses .......2004-12-28
The book serves up a very interesting and enlightening alternative to traditional economic thought in a variety of different contexts. I would certainly recommend it to any graduate student of physics or economics seeking to have a well rounded view the financial world.
The great weakness of this text is that the author seems to more than simply disagree with traditional economic theory, he despises it. That might not by itself be so great a weakness if the theory offered up in its stead were compelling, but, the author's passion notwithstanding, that is not the case here. The math aside, in tone and method this book reminds me very much of books authored by Intelligent Design advocates, seeking more to destroy the prominent competing theory than to present a coherent theory of its own.
Perhaps such passion is needed to get the neoclassical economists to pay attention. As in many things, I suspect the two schools of thought have much to teach one another.
On a more practical level, this is not a book for those who have not had a very solid grounding in mathematics, and likely unsuitable for all but the brightest, and most mathematically inclined, undergraduates.
Dynamics of Markets - Econophysics and Finance.......2004-12-10
Dynamics of Markets - Econophysics and Finance
by Joseph McCauley
reviewed by: Enrico Scalas
In 1720, Newton invested his money in the South Sea bubble and lost £20000, a lot of money in those days [1].
So, physicists do not always do it better in financial markets.
Having said that, let us now go on and consider the merits and limits of this book by Joseph McCauley.
The book is divided into nine chapters. Chapters 1, 3, 8 and 9 cover material from epistemology (ch. 1), probability theory (ch. 3), fluid dynamics (ch. 8), and the theory of computation (ch. 9). Chapters 2, 4, 5,6 and 7 are mainly devoted to economics and finance. Namely, chapter 2 critically reviews the general theory of equilibrium, chapter 4 is on the dynamics of markets, chapter 5 and 6 present portfolio selection theory and
option pricing, respectively, and, finally, chapter 7 is a criticism of thermodynamic analogies in finance.
The range of interests of the author is overwhelming and this book is the first attempt to put together many concepts taken from various disciplines in a coordinate view. I am a fan of this method and I much appreciate the effort of the author. However, this is also a limit, as the reader looking for recipes to price options or to select a suitable portfolio will be somehow disappointed. In the very same way, those looking for a
rational criticism of neo-classical assumptions in economics are likely to read the chapters on option pricing without great passion.
In a short review, it is impossible to take into account all the aspects of McCauley's book.
I will just discuss one: equilibrium in economics. But, before that, let me underline that this is the first book in Econophysics where everything in finance is done by explicitly formulating and calculating Green functions. Second, the author presents the European option price predictions in a closed algebraic form and, third, Gaussian returns play no role in the predictions fully based on the empirical distribution.
The author presents a nice criticism of the concept of equilibrium in economics which, in itself, is worth
buying and reading the book. The arguments are scattered throughout the book, as the author is interested
in discussing the behaviour of financial market. For economics and finance, the author provides convincing evidence that the only legitimate form of equilibrium is vanishing excess demand. But price fluctuations in actual financial markets cannot be effectively explained by a sequence of different economic equilibria determined by varying exogenous factors. Then, the only possibility is that excess demand is considered as a stochastic process leading to diffusive models for price (or return) dynamics. Thus, the use of the Green-function formalism in Finance is a natural and logical choice.
McCauley's discussion on equilibrium would have been helped by reference to Kaldor's 1972 paper on the irrelevance of equilibrium economics [2]. Kaldor's point of view coincides with the one of McCauley when he argues that ultimately theories must be confronted with the real world. In discussing the difference between an axiomatic theorem and a scientific theory, Kaldor quotes Einstein: << Physics constitute a logical system of thought which is in a state of evolution, whose basis cannot be distilled, as it were, from experience by an inductive
method, but can only be arrived at by free invention. The justification (truth content) of the system rests in the verification of the derived propositions by sense experiences. The skeptic will say: "it may well be true that this system of equations is reasonable from a logical standpoint. But it does not prove that it corresponds to nature". You are right, dear skeptic. Experience alone can decide on truth. >> [3]
Also in this book, as in many contemporary books, there are various misprints and the constant reference to wrong equation numbers is disturbing.
I think that this book can be read with profit both by physicists interested in complex systems and by economists interested in the principles of their discipline. Economists can always refer to Newton's example mentioned above, when they read in the book about the success of physicists in finance.
References
[1] C. Reed, "The Damn'd South Sea" Britain's greatest financial speculation and its unhappy ending, documented in a rich Harvard collection. Harvard Magazine, May-June 1999.
[2] N. Kaldor, "The Irrelevance of Equilibrium Economics", The Economic Journal, vol. 82, n. 328, 1237-1255, 1972.
[3] A. Einstein, "Ideas and Opinions", Gramercy; Reprint edition (December 12, 1988).
Book Description
Financial markets are a fascinating example of 'complexity in action': a real-world complex system whose evolution is dictated by the decisions of crowds of traders who are continually trying to win in a vast global 'game'. This book draws on recent ideas from the highly-topical science of complexity and complex systems, to address the following questions: how do financial markets behave? Why do financial markets behave in the way that they do? What can we do to minimize risk, given this behavior? Standard finance theory is built around several seemingly innocuous assumptions about market dynamics. This book shows how these assumptions can give misleading answers to crucially important practical problems such as minimizing financial risk, coping with extreme events such as crashes or drawdowns, and pricing derivatives. After discussing the background to the concept of complexity and the structure of financial markets in Chapter 1, Chapter 2 examines the assumptions upon which standard finance theory is built. Reality sets in whith Chapter 3, where data from two seemingly different markets are analyzed and certain universal features uncovered which cannot be explained within standard finance theory. Chapters 4 and 5 mark a significant departure from the philosophy of standard finance theory, being concerned with exploring microscopic models of markets which are faithful to real market microstructure yet, which also reproduce real-world features. Chapter 6 moves to the practical problem of how to quantify and hedge risk in real world markets. Chapter 7 discusses deterministic descriptions of market dynamics, incorporating the topics of chaos and the all-important phenomenon of market crashes.
Customer Reviews:
Lucid, dense and sound econophysics book.......2004-06-01
This book is written in a very dense fashion and should be compared to a math or physics text and obviously not to the advertised get rich quick books.
The style is very clear and very dense. The introduction says more about the financial market as many long texts. Also the definitions are precise and do contain content. Alone this introduction is worthwhile for anybody in the business of specifying a financial software system. It saves literally weeks of work.
As a next step a very dense overview of the "standard" finance theory is presented (first order Markov...). The authors even succeed to explain the Black Scholes option-pricing model in a few pages. I am very thankful for this.
The main impetus of the authors is to apply complexity theory to financial markets and get in return a good and existing example of a complex system. They look deeply into the limits of the independent and identical distributed probability function assumption. Also higher order correlations, the effect of competing and partly collaborating agents is discussed.
The text is accessible to most graduate students with a corresponding background in mathematics, physics ....
Book Description
Statistical physics concepts such as stochastic dynamics, short- and long-range correlations, self-similarity and scaling, permit an understanding of the global behavior of economic systems without first having to work out a detailed microscopic description of the system. This pioneering text explores the use of these concepts in the description of financial systems, the dynamic new specialty of econophysics. The authors illustrate the scaling concepts used in probability theory, critical phenomena, and fully-developed turbulent fluids and apply them to financial time series. They also present a new stochastic model that displays several of the statistical properties observed in empirical data. Physicists will find the application of statistical physics concepts to economic systems fascinating. Economists and other financial professionals will benefit from the book's empirical analysis methods and well-formulated theoretical tools that will allow them to describe systems composed of a huge number of interacting subsystems.
Customer Reviews:
Excellent Introduction.......2004-12-01
This book is an excellent introduction to financial analitics for Physicists and also for others. Though a little out dated, but what can you expect from such a fast changing subject?
This is not the first book I have read in this subject, but it is my favorite right now. I could have saved myself a lot of trouble if this would have been the first.
Nevertheless, it should be considered as an intial reference point and not as to expect it to contain all the details. After all it only has 148 pages.
target audience not defined.......2003-09-22
I find the book rather poorly written in the aspect of providing links between statistical physics and its application in economics. As a physicist with a background in stochastic processes, I was looking for an introduction to their applications to economic analysis, complete with examples and discussion of the methods' limitations. The book was somewhat disappointing in this respect. Quite often, in many chapters, the necessary math is explained, then some aspects of how it is manefest in economical data are presented and then the chapter ends, leaving the reader wonder what the specific cases may be and if it is practical to use those methods at all. Above all, there is very little discussion as to what the results actually mean, in economical terms.
I believe the book may be helpful for reseachers active in this field but I would not recommend it as a first introduction to econophysics. For economists, the math may be rather difficult to go through as some of the fundamental concepts are not defined consistently. For physicists with no previous exposure to econophysics, I would prefer to see more economics.
Not bad, considering..........2002-08-13
The book is not bad considering the total lack of existence of intelligible literature in this supposedly vast field.
The content is really a collection of quickie crib-sheets on a sundry of topics with nominally common theme: Finance.
A lot of the actually useful stuff is the author's previously published papers on price-return distributions.
Aside from his own previously published work, he has a good tutorial on the GARCH scheme though with precious little follow up reading resources for delving in deeper (or even sideways).
This book is priced far too high given its content and depth.
Look for a used copy, and do not count on the author to answer questions by email.
First in the new field.......2002-06-05
I found several parts of this book useful while preparing lectures for an introductory econophysics course in Fall, 2001. The discussions of convolutions of distributions, Levy distributions and scaling are well-written and easy to follow. In the brief discussion of the St. Petersburg Paradox I missed a critical discussion of expected utility, which was invented by Bernoullli to 'resolve' that paradox. Spurred by von Neumann and Morgenstern, neo-classical economics relies on the idea of expected utility, which seems empirically to be wrong. The chapter on time correlations is also very readable (although Wiener processes are not 1/f^2 noise!). ARCH and GARCH methods are discussed, saving the student from the pain of reading badly-written papers by mathematically-minded economists, but the chapters on options are too brief with nothing new. The best introduction to options is still the original Black-Scholes paper (excepting their erroneous claim that CAPM and the delta-hedge strategy produce option pricing pdes that agree with each other). Also, it would have been nice to have seen a discussion of CAPM. The discussion of algorithmic complexity left me cold (see my earlier books and papers on nonlinear dynamics), and I would like to have seen a critical discussion of the EMH. These criticisms are ok, though, the gaps leave something for the rest of us to work on.
Physicists Land On Planet Economics.......2001-06-11
SINCE the last decade, physicists have been trying to cope with the issues traditionally approached by economics using their own tools and methodologies. This research has been dubbed 'econophysics'. One reason why this incursion should be welcomed is the failure of mainstream economics to recognise financial systems as complex systems. Take mainstream international finance, for instance. In the most respectable workhorse model--so-called 'new open economy macroeconomics model'--foreign exchange rates always reach some sort of stable equilibrium. To put it bluntly, this means that currencies do not exhibit complex behaviour.
However, financial markets do demonstrate several of the properties that characterise complex systems. What is more, they are highly complex, open systems in which many subunits interact nonlinearly in the presence of feedback and stable governing rules. Earlier attempts to find chaos in financial data, for instance, have been disappointing exactly because the phenomenon is likely to emerge in systems which are only moderately complex. Although it cannot be ruled out that financial markets follow chaotic dynamics, econophysics assumes that asset price dynamics are stochastic processes.
A fundamental commitment of the mainline model of international finance is to theory itself, and not to data. Modelling is devoted to equipping the discipline with an underlying rational behaviour at the individual level. Yet this is at odds with the fact that financial markets are prone to collective 'irrational exuberance'. Instead, econophysics attemps to build up stochastic models that encompass essential features observed in the financial data. Now that the time evolution of many financial markets is continually monitored, it is possible to test the accuracy and predictive power of the developed models using available data. One common objection to such a practice is that it is impossible to perform large-scale experiments in economics that could falsify any given theory. The authors note that this limitation is not specific to economics, but also affects such well developed areas of physics as astrophysics, atmospheric physics, and geophysics. By analogy with the activity in these more established areas, we are able to test and falsify any theories associated with the current available sets of financial data.
Complex systems can sometimes behave in remarkable simple ways. These are reflected in power law distributions and scaling. The authors illustrate these concepts and others, and apply them to the financial time series. The book is thus useful not only for physicists but also for economists and people in the financial world. Some familiarity with probability theory or statistical physics is required, though. Economists dissatisfied with the mainline approach of their discipline will find the book opportune. The others might end up welcoming econophysics as well. After all, economists implicitly see physics as nature's economics. What is then wrong with physicists thinking of economics as social physics?
Book Description
Summarizing market data developments, some inspired by statistical physics, this book explains how to better predict the actual behavior of financial markets with respect to asset allocation, derivative pricing and hedging, and risk control. Risk control and derivative pricing are major concerns to financial institutions. The need for adequate statistical tools to measure and anticipate amplitude of potential moves of financial markets is clearly expressed, in particular for derivative markets. Classical theories, however, are based on assumptions leading to systematic (sometimes dramatic) underestimation of risks.
Customer Reviews:
Five stars for the intended audience, two stars for the likely holder .......2006-10-16
Five stars for the intended audience, two stars for the likely holder (a theoretical approximation of the mathfin reader utility curve) give a three star average. Why? Practical utility skew is the operative third moment.
If you have no idea about what I just wrote, this book is not for you. If you do and it made you smile, keep reading.
In Theory of Financial Risk and Derivative Pricing: From Statistical Physics to Risk Management authors Bouchaud and Potters place an additional veneer on their previous edition titled Theory of Financial Risks: From Statistical Physics to Risk Management, adding the sexy "Derivative Pricing" no doubt in a forgivable attempt to increase sales in this Googlfied world. But this is their failure. While the original edition was a fine, even respectable voice on bridging the knowledge of the intended audience of physicists-turned financial quant, this edition fails on the over covered subject of derivative pricing simply because it is not theoretical, but an empirical and technical review of historical data sets and assumptions and pricing techniques with critiques of the observed differences between theory and empirical results. Needless to say, this fails the smell test in physics, but in finance is as common as Shinola.
Sorry, but critiques of B-S assumptions and better curve fitting is technical, not theoretical. In other words, the theory of why third and fourth moments (skew and kurtosis) become operative and currently present arbitrage opportunities or risk management concerns is not adequately addressed, merely observed, expressed, and called attention to. Moreover, third and fourth moments are approached from a formulaic perspective intended primarily for risk managers and those seeking to make a buck (such as the authors themselves) and have only dangers emphasized. So formulas and expression yes, pure theory no.
Other reviewers have complained about a thematic Gauss-Levy versus Bachelier tone. Ho hum. For the day to day market maker (readers of Baird) such arguments pale in comparison to managing simply the delta of your book. For the physicist, the ghastly collection of noise and spikes that passes for a data set in finance will likely simply better be explained by long periods of madness followed by fleeting moments of clarity than any Procrustean attempt at better curve fitting informed for the empirical work of observing the data signals of a star's decay. Perhaps the only person Bouchaud and Potters's theoretical practical bridge tweaking would have assistance for would be the risk manager of the completely non-correlated short duration portion of the balance sheet of an international bank. Who also happened to be very powerful and have actual accurate real-time data and could implement these ideas. Scale? North of 8 billion before this is useful. Yep, in such a theta world Bachelier's technique rules. But we don't live in such a world yet, although risk managers everywhere delude themselves that they do, often armed with the likes of this book.
Let me hasten to add that Theory is not a bad thing, but its utility best serves the finmath community when it is clearly and explicitly so, without attempting techne and erte. This book is a forgivable beast with two backs, strongly skewed to a good critique of Theory and with fat tails of empiricism, and a bad attempt to be practical. This work therefore, again forgivably, is bound to disappoint practitioners. Joshi is your better bet.
Who is this book not for? Readers and users of Baird, Joshi and Hull and coding front-line quants and risk managers who live in a world of imperfect and delayed data sets will likely find this pointless academic obfuscation. Whom is this book for? I'm a finance guy, not a physicist, and so I read this book in a cyber book group with a theoretical physicist friend. He characterized the book as easy reading for him, but with little new to add that wasn't already known by the reasonably informed physicist turned finquant. His take was that it was a painfully obvious work, curiously passed off as original thinking when in reality it was simply a useful synthesis of common, though specialized knowledge. My take was it was tough sledding to get to obvious conclusions that anyone who has ever run an options book knows through painful experience or wise counsel. Elegantly expressed at a high level for a well-educated readership, but not exactly a holy grail. In other words, the juice wasn't worth the squeeze.
Longs and Shorts of the Theory of Financial Risk.......2006-06-10
The major achievement of the book is concise presentation of the latest discoveries of the authors and their co-authors (Cont, Matacz). The discoveries are so significant that will lead in some 20 years to a Nobel Prize in Economics. They are: non-uniqueness of the option's price; role of kurtosis (the fourth moment of the price distribution) for volatility smile formula; a simple "square-root" formula for the FRC (forward rate curve of interest rate) accompanied by a simple explanation of a market mechanism behind it; deep "psychological" explanation (via Langevin equation) of the exponents 3-5 in the power-type tails of the price distributions; explanation of why VaR is systematically underestimated by Black-Scholes theory. However, all these discoveries require different mathematics and so far the authors are in search for the correct way to present them together coherently. There are several loose ends: many non-Gaussian approximations (which likely came from JPB's early works in physics and still beloved by him) without practical tools to estimate them; in the interesting chapter on random matrixes missing is a "market" explanation of the meaning of the eigenstates which stand behind 10% of "non-random" eigenvalues; absence of a serious discussion about exotic options points out to a difficulty to extend authors' methods toward more general options (while the regular PDE approach taken by other authors, like Wilmott, allows such an extension almost naturally).
Fat tails and more.......2002-06-05
This text has a nice discussion of Levy distributions and (important!) discusses why the central limit theorem does not apply to the tails of a distribution in the limit of many independent random events. An exponential distribution is given as an example how the CLT fails. I was first happy to see a chapter devoted to portfolio selection, but the chapter (like most of the book) is very difficult to follow (I gave up on that chapter, unhappily, because it looked interesting). The notation could have been better (to be quite honest, the notation is horrible), and the arguments (many of which are original) could have been made sharper and clearer. For my taste, too many arguments in the text rely on uncontrolled approximations, with Gaussian results as special limiting cases. The chapters on options are original, introducing their idea of history-dependent strategies (however, to get a strategy other than the delta-hedge does not not require history-dependence, CAPM is an example), but the predictions too often go in the direction of showing how Gaussian returns can be retrieved in some limit (I find this the opposite of convincing!). For an introduction to options, the 1973 Black-Scholes paper is still the best (aside from the wrong claim that CAPM and the delta-hedge yield the same results). The argument in the introduction in favor of 'randomness' as the origin of macroscopic law left me as cold as a cucumber. On page 4 a density is called 'invariant' under change of variable whereas 'scalar' is the correct word (a common error in many texts on relativity). The explanation of Ito calculus is inventive but inadequate (see instead Baxter and Rennie for a correct and readable treatment, one the forms the basis for new research on local volatility). Also, utlility is once mentioned but never criticized. Had the book been more pedagogically written then one could well have used it as an introductory text, given the nice choice of topics discussed.
Reply to the previous reviewer.......2001-07-29
Unfortunately, but not surprisingly, the previous reviewer prefered to remain anonymous. Otherwise, we would happily have argued with him privately. But his review contains so many erroneous and obnoxious statements that we feel we have to reply publicly, at least on the most important points.
a) After spending a full chapter (2) on empirical data and faithful models to describe them, we only price options using...the Brownian motion, says our reviewer (not even the Black-Scholes model, adds he). Well, either the reviewer has only casually browsed through our book, or this is total bad faith and disinformation. After discussing a general option pricing formula, we indeed illustrate it first (4.3.3) with the Black-Scholes model, then with Bachelier's (Brownian) model which, as we explain, is actually a better model for short term options. But the rest of the chapter is entirely devoted to non-Gaussian effects: a theory of the smile, its relation with kurtosis and long-ranged correlation in the volatility, and comparison with actual market smiles (4.3.4), and more importantly, the hedging strategies and residual risk (4.4), alternative hedging strategies for Value-at-Risk control (4.4.6), etc. The emphasis on risk, absent in the Black-Scholes world, is our main message, and partly justifies the title of our book.
b) "There is no statistical physics" in our book, moans the reviewer. Our aim was not to draw phoney analogies, but to present this field in the spirit of statistical physics, with what we feel is an interesting balance between intuition and rigour. (Many physicists feel stranded when reading standard mathematical finance books, where data is scarce, and rigour hides the inadequacies of the models). However, there are several genuine inputs from statistical physics, e.g. data processing, approximations, simple agent based models (2.8-9), functional derivatives to obtain optimal hedges (4.4), saddle point estimates of the Value at Risk for complex portfolios (5.4) and finally, Random Matrices that the reviewer finds unduly complex -- perhaps only because new to him. However, this is contained in "starred" section, indicating that it can be skipped at first reading, as many more advanced sections.
Two more details. We indeed sometimes consider independent random variables, sometimes only uncorrelated, hopefully not confusing the two. If the reviewer spotted incorrect statements, we would be grateful to him if we can correct them in further editions. Second, our book is not meant to provide ready to implement recipes but to present a different way of thinking about finance. Nevertheless, many of the ideas have already been implemented and are used by several (open minded?) financial institutions.
Can do more harm than good.......2001-07-26
This book is a supposedly new approach to financial modeling from the viewpoint of "statistical physics". In fact, it is far from being that. First, there is little or no content really related to statistical physics in it. Apart from the fact that random variables and stochastic processes are also used in physics, the only feature in common between statistical physics and this book is some notational similarities and a lack of rigour which, justified in the case where it is supplemented by physical intuition, leads here to numerous mistakes and sloppy reasoning.
The title, while promising, is quite arrogant: not only there is no "theory of financial risks" in the book but many of the main issues of risk management are not even mentioned: Value at Risk receives less than a page at the end, while hedging of exotic options is not even an issue.
Also, while the first part of the book insists on choosing the correct distribution for price returns, the chapter on options exclusively gives computations for the case of ...Brownian motion (not even exponential Brownian motion)! One is left wondering whether these fancy models presented in the first part were worth mentioning?
Another point is the readership of this book: given the notational complexity of the book and the analogies with physics, only a PhD in theoretical physics can possibly find this book readable. In fact, a finance student will find it too light on the finance side while a math-minded student will find it too sloppy and imprecise.
The surprisingly low level of mathematical rigour - one confuses regularly "uncorrelated" with "independence"- is nevertheless accompanied by an incredibly sophisticated set of tools such as random matrix theory, which are exotic even for professional researchers. Perhaps it would be better to spend more time explaining the concept of stochastic volatility or nonstationarity than rocketing the reader into unknown grounds...
I come to the conclusion that the aim of the book is more to impress the reader about the technical sophistication of the authors than to teach anything in a clear manner.
Although OK as a bedtime reader, this book certainly does not contain anything one can practically implement: in fact the presentation is so imprecise that one is lost in the successive and uncontroled approximations, not knowing at the end what is the algorithm proposed to solve a given problem.
Book Description
This book contains high-quality multi-disciplinary research contributions addressing theoretical and computational aspects of interaction and coordination of economic agents. It focuses on emergent phenomena and collective behavior in economic activities as well as on the development of analytical and computational tools in models with heterogeneous agents. The contributions are not restricted to any particular school of thought, but are based on rigorous theoretical models and supported by experimental validation.
Book Description
Complex behavior can occur in any system made up of large numbers of interacting constituents, be they atoms in a solid, cells in a living organism, or consumers in a national economy. Analysis of this behavior often involves making important assumptions and approximations, the exact nature of which vary from subject to subject. Foundations of Complex-system Theories begins with a description of the general features of complexity and then examines a range of important concepts, such as theories of composite systems, collective phenomena, emergent properties, and stochastic processes. Each topic is discussed with reference to the fields of statistical physics, evolutionary biology, and economics, thereby highlighting recurrent themes in the study of complex systems. This detailed yet nontechnical book will appeal to anyone who wants to know more about complex systems and their behavior. It will also be of great interest to specialists studying complexity in the physical, biological, and social sciences.
Customer Reviews:
4.5 Stars-The whole is not the sum of the parts;Excellent and scholarly.......2006-02-14
This is a very interesting book.The author demonstrates that she has command over a number of different fields.She exhibits a wide ranging scholarship in this book.In a nutshell,one can categorize the major conclusions she arrives at as the whole is not the sum of the parts alone.Neither a strictly micro or macro approach to the different fields she investigates,using a complex systems framework, yields the idealized types of scientific discovery and knowledge one finds postulated in some philosophy of science discourses that emphasize deductive closure laws.I have one slight criticism of the book,which is why I have subtracted one half a star.The author has a deep general understanding of the Keynes-Knight distinction between risk and uncertainty in economics(and in social sciences).However,she lacks an understanding of the specifics of Keynes's approach in the A Treatise on Probability(1921;TP).She is unaware of Keynes's interval estimate approach to probability,his index,w,used to measure the completeness of the evidence ,ranging from ignorance through partial knowledge to a complete information set,and Keynes's conventional coefficient of weight and risk,which treats risk, based on the purely deductive laws of probability, as a special case.This would be a very minor criticism if she had integrated the work of D.Ellsberg(Ellsberg's 2001 book,Risk,Ambiguity,and Decision gives a modern,improved and updated version of the TP) and B.Mandelbrot into her discussions involving economics,risk,and uncertainty(Ellsberg's Ambiguity with his rho and alpha indexes and the wild versus mild risk of the cauchy distribution versus normal distribution as discussed by Mandelbrot).Unfortunately,Ellsberg's contributions are not discussed at all while Mandelbrot receives a single footnote that completely ignores his contributions to economics.She can certainly obtain a 5-star rating by bringing out a revised edition in which the original,technical, pioneering work of Keynes is covered followed by the modern and updated contributions of Ellsberg and Mandelbrot.
a fascinating book -- recommended to philosophers.......2002-10-26
Philosophers of science need to read this book: the hands-on
account of how three sciences work is a healthy
corrective to the usual practice of writing philosophy of science
without actually knowing how the science is done.
A Professional work.......2000-03-30
This is an amazing work. Sunny Auyang has written an easily comprehenedible book on applications of complexity theories to economics, biology and physics. It is a professional writing to professionals in different fields.One needs college level maths and some physics to fully grasp it but she has made minimum use of mathematical symbols. Her writing flows, the examples are clear, some illuminate important issues in the applied fields, some are just homey bits that convey an idea insightfully. A lot of depth in her philosophical explorations of the complexity ideas. I consider this to be a must for any person studying or instructing in system thinking.
Book Description
The authors treat macroeconomic models as composed of large numbers of micro-units or agents of several types, and explicitly discuss stochastic dynamic and combinatorial aspects of interactions among them. In mainstream macroeconomics sound microfoundations for macroeconomics has meant incorporating sophisticated intertemporal optimization by representative agents into models. Optimal growth theory, once meant to be normative, is now taught as a descriptive theory in mainstream macroeconomic courses. In neoclassical equilibria flexible prices led the economy to the state of full employment and marginal productivities are all equated. Professors Aoki and Yoshikawa contrariwise show that such equilibria are not possible in economies with a large number of agents of heterogeneous types. The authors treat equilibria as statistical distributions and not as fixed points. They employ a set of statistical dynamical tools via continuous-time Markov chains, and statistical distributions of fractions of agents by types available in the new literature of combinatorial stochastic processes, to reconstruct macroeconomic models.
Book Description
This text provides a sound introduction to all aspects of combined heat and power (CHP) thermodynamics, design, economics, and utilization. Specific emphasis is placed on the performance of combined heat and power plants compared with conventional plants, and the economic considerations in combined heat and power utilization. There are numerous CHP installations now in commission and, where applicable, the text describes practical examples of CHP use.
Average customer rating:
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Application of Econophysics: Proceedings of the Second Nikkei Econophysics Symposium - Application of Econophysics
Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover
 Econometrics
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ASIN: 443114028X |
Book Description
Econophysics is a newborn field of science bridging economics and physics. A special feature of this new science is the data analysis of high-precision market data. In economics arbitrage opportunity is strictly denied; however, by observing high-precision data we can prove the existence of arbitrage opportunity. Also, financial technology neglects the possibility of market prediction; however, in this book you can find many examples of predicted events. There are other surprising findings.
This volume is the proceedings of a workshop on "application of econophysics" at which leading international researchers discussed their most recent results.
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