Market Models: A Guide to Financial Data Analysis Review

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(More customer reviews)If you are looking for detailed rigorous mathematical development then look elsewhere, that is not the reason to purchase this book. It is targeted towards application and there it excels. I have not seen any other book on this topic that so effectively presents a level-headed applied approach that keeps the basic assumptions of the models firmly in sight.
What tool fits when is nicely discussed.

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Market Models provides an authoritative and up-to-date treatment of the use of market data to develop models for financial analysis. Written by a leading figure in the field of financial data analysis, this book is the first of its kind to address the vital techniques required for model selection and development. Model developers are faced with many decisions, about the pricing, the data, the statistical methodology and the calibration and testing of the model prior to implementation. It is important to make the right choices and Carol Alexander's clear exposition provides valuable insights at every stage.In each of the 13 Chapters, Market Models presents real world illustrations to motivate theoretical developments. The accompanying CD contains spreadsheets with data and programs; this enables you to implement and adapt many of the examples. The pricing of options using normal mixture density functions to model returns; the use of Monte Carlo simulation to calculate the VaR of an options portfolio; modifying the covariance VaR to allow for fat-tailed P&L distributions; the calculation of implied, EWMA and 'historic' volatilities; GARCH volatility term structure forecasting; principal components analysis; and many more are all included.Carol Alexander brings many new insights to the pricing and hedging of options with her understanding of volatility and correlation, and the uncertainty which surrounds these key determinants of option portfolio risk. Modelling the market risk of portfolios is covered where the main focus is on a linear algebraic approach; the covariance matrix and principal component analysis are developed as key tools for the analysis of financial systems. The traditional time series econometric approach is also explained with coverage ranging from the application cointegration to long-short equity hedge funds, to high-frequency data prediction using neural networks and nearest neighbour algorithms.Throughout this text the emphasis is on understanding concepts and implementing solutions. It has been designed to be accessible to a very wide audience: the coverage is comprehensive and complete and the technical appendix makes the book largely self-contained.Market Models: A Guide to Financial Data Analysis is the ideal reference for all those involved in market risk measurement, quantitative trading and investment analysis.

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Super Crunchers: Why Thinking-By-Numbers is the New Way To Be Smart Review

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(More customer reviews)Is it a new brand of cereal? Or maybe it's a granola bar, or a chunky peanut butter spread? Then again, could it be the latest infomercial exercise device designed to give you the six pack abs you've always dreamed of but know in your heart of hearts you'll never achieve? Actually, it's a book - the title a product of the very methods the book describes. Here's what SUPER CRUNCHERS says.
(1) Mathematical regression models generated from large datasets often generate better predictions than human experts, and they provide supporting information on the predictive weight and reliability of each explanatory variable.
(2) Well-crafted experiments using randomized trials and control groups provide good market research and behavioral analysis results.
(3) Technological advances - the Internet, massive data storage devices, rapid computation, broadband telecommunication - are making it possible to share more sources of information and create ever-larger databases for analysis.
(4) Today's companies engage in multiple forms of market research by creating and using large databases and large-scale randomized trials.
(5) Many phenomena conform to normal distributions in which 95% of the population will be found within two standard deviations of the mean, the5% balance generally divided evenly in the two tails.
That's it. I just saved you $25.00 U.S. and a half-dozen or more hours learning how a guy from Yale named Ian Ayres collected a bit of information about applied mathematical techniques that have been in practical use for decades, packaged them up, palmed them off as something new, and cooked up the ridiculous name Super Crunching to describe an ostensibly new technological development. Yet "Super Crunching" is nothing more than the author's marketing hype for a couple of standard mathematical methodologies, a creation of nothing from something. There's no new breakthrough here, no new paradigm.
Yes, the anecdotal information about the future prices of wine vintages, Capital One's teaser offerings, and evidence-based medical diagnosis are interesting (hence the two stars rating). The rest, however, is neither prescriptive nor sufficiently critically analytical. Should we go out shopping for a Super Cruncher tomorrow? Should we delight in the increased accuracy of data-driven modeling and prediction, or should we fear the implied manipulation of our desires and the incessant, single-minded drive toward maximum profit at the expense of creativity? Do we really want movies and books to be developed from mathematical models like Epagogix? Do we really want our every keystroke on the Internet to be fodder for market research that manipulates us in response? John Kenneth Galbraith, among others, warned of exogenous, manufactured demand decades ago.
SUPER CRUNCHERS is part business tome, part econometric paean, and part sociology book, but not fully any of the three. No matter how many time the author uses words like "cool" and "humongous" and "amazing," it's still regrettably a "No Sale" even for someone like me who enjoys reading about applied mathematics.


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Baseball Hacks: Tips & Tools for Analyzing and Winning with Statistics Review

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(More customer reviews)If you've ever been involved in a fantasy baseball league and gotten killed by people who seem to have time to do nothing but research obscure baseball players, Baseball Hacks is the book for you. In this book, Joseph Adler takes his love of baseball and combines it with an understanding of databases and data-mining technology to help fantasy-sports fanatics and baseball statistic junkies get their regular fix of the numbers that drive America's Game.
The great thing about this book is that the software used is all open source. Adler includes Access and Excel hacks for those who have Office at home or at work, but the main hacks in the book involve MySQL for database queries and R for graphic statistical analysis. I've used MySQL before, but R was new for me, and I really enjoyed using the program.
Adler also uses Perl. A lot of Perl. But he doesn't expect the reader to be Perl programmers; he shows how the program was written, and what everything does. More importantly, he includes the whole script so that it's a simple matter of copying, and making modifications if needed. He even shows how to modify the scripts.
Downloading a beginning stat database is as easy as 1-2-3. Hack 25 tells you how to spider websites for statistical data - including getting data from MLB.com. Detailed instructions on working with R are included in section 4 (hacks 31-39). Adler even includes formulas for calculating the more arcane statistics (at least to non-sports people like me) such as OPS (on-base plus slugging average) and ISO (isolated power - a measure of how well a player hits the ball).
It's obvious that Baseball Hacks is a book designed for fantasy sports fanatics. I've also pointed the book out to some computer applications teachers and statistics teachers - combining the study of stats and database construction with a subject that so many teenage boys enjoy studying is a great idea. Teaching database structure and analysis is tough, but give them something that they like to do, and they're all over it. This book does exactly that.

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Baseball Hacks isn't your typical baseball book--it's a book about how to watch, research, and understand baseball. It's an instruction manual for the free baseball databases. It's a cookbook for baseball research. Every part of this book is designed to teach baseball fans how to do something. In short, it's a how-to book--one that will increase your enjoyment and knowledge of the game.

So much of the way baseball is played today hinges upon interpreting statistical data. Players are acquired based on their performance in statistical categories that ownership deems most important. Managers make in-game decisions based not on instincts, but on probability - how a particular batter might fare against left-handed pitching, for instance.

The goal of this unique book is to show fans all the baseball-related stuff that they can do for free (or close to free). Just as open source projects have made great software freely available, collaborative projects such as Retrosheet and Baseball DataBank have made great data freely available. You can use these data sources to research your favorite players, win your fantasy league, or appreciate the game of baseball even more than you do now.

Baseball Hacks shows how easy it is to get data, process it, and use it to truly understand baseball.The book lists a number of sources for current and historical baseball data, and explains how to load it into a database for analysis.It then introduces several powerful statistical tools for understanding data and forecasting results.

For the uninitiated baseball fan, author Joseph Adler walks readers through the core statistical categories for hitters (batting average, on-base percentage, etc.), pitchers (earned run average, strikeout-to-walk ratio, etc.), and fielders (putouts, errors, etc.). He then extrapolates upon these numbers to examine more advanced data groups like career averages, team stats, season-by-season comparisons, and more. Whether you're a mathematician, scientist, or season-ticket holder to your favorite team, Baseball Hacks is sure to have something for you.

Advance praise for Baseball Hacks:
"Baseball Hacks is the best book ever written for understanding and practicing baseball analytics. A must-read for baseball professionals and enthusiasts alike."
-- Ari Kaplan, database consultant to the Montreal Expos, San Diego Padres, and Baltimore Orioles

"The game was born in the 19th century, but the passion for its analysis continues to grow into the 21st.In Baseball Hacks, Joe Adler not only demonstrates that the latest data-mining technologies have useful application to the study of baseball statistics, he also teaches the reader how to do the analysis himself, arming the dedicated baseball fan with tools to take his understanding of the game to a higher level."

-- Mark E. Johnson, Ph.D., Founder, SportMetrika, Inc. and Baseball Analyst for the 2004 St. Louis Cardinals

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Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems) Review

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(More customer reviews)I'm surprisingly please with this book. I've been reading up on the topic and associated algorithms in other books for some time; I'm a software developer but don't have a statistics background, and so felt a lot of the texts were too focused on the math and the theory while being thin on content when it came to "rubber hitting the road", or even using clear, simple examples and straight-forward notation.
This book is so well-written that it communicates the concepts clearly, lucidly and in an organized fashion. The section that introduces Bayesian probability was drop-dead simple to follow. Quite frankly, having read a few other treatments on it, I can now say that everything else I read before this was overly complicated. Brevity is the soul of wit, no?
To the reviewer who criticized the authors use of words to describe equations: This is what the authors intended to do. Would you fault them for writing in English if you wanted Greek? Not everyone who can benefit from applied data mining has the requisite background to understand the nitty gritty mathematics, nor should they have to, if they just want to understand the behavior and practical applications of the technology.

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The Perfect Swarm: The Science of Complexity in Everyday Life Review

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(More customer reviews)As a glance at the "Look Inside" feature here on Amazon proves, Len Fisher writes a clear, interesting prose, raising important questions and suggesting rules that will help you make better decisions. He describes and applies 33 such rules in this latest contribution to popular science.
His basic thesis is that complex behaviors can be described by a simple rule. For example, gigantic numbers of fish seem to have a single mind -- but all a single fish has to know is to follow the fish immediately in front of it. Watching through your faceplate at gigantic schools of fish as they weave through the water -- you can see this rule in action in beautiful living color.
You can apply the same approach in trying to find a bargain, an approach that works best where there are many sellers and the products are fairly similar to each other.
The basic idea is "to estimate how many samples of the item might be available in total, and then look at a limited selection of these before choosing the next one that is at least as good (in terms of price and quality) as the best of those that we have so far seen. This procedure saves time and effort, and also reduces the possibility that we will spot a bargain, keep looking for a better one, decide on the original one, and go back only to find that it has been sold!"
Fisher explains the use of statistics in three scenarios:
"If we are going for the very best, we should look at one-third of all those available before going on to select the next one that is as good or better than the best that we have already seen (in terms of the lowest price for the same quality). This gives us a 33% chance of finding the very best bargain, and a very high chance of finding an extremely good bargain.
"If we are happy to accept a sample in the lowest 10% of prices, we need only look at 14% of the samples on offer before choosing the next one that we see which is at least as cheap as the cheapest of these. This gives us an 84% chance of settling on one among the cheapest 10%.
"If we are happy with a price in the lowest 25%, things get even better. We need only to look at 7% of the samples before choosing one that is at least as cheap as the cheapest we have seen. This gives you a whopping 92% chance of finding a bargain in your chosen range!"
Of course, if it's easy to find additional offers, or if it's fairly easy to get back to a better offer to see if it's still available, you may be able to get more/better/cheaper by spending a bit more time. Once you get the basic approach in mind, however, you'll be able to decide when to stop looking, make your choice, and get back to reading about other examples of how simple rules lead to great complexity.
Fisher's website is filled with additional examples, and his clear joy in reading and writing about science at work in our everyday life.
Robert C. Ross2009

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One of the greatest discoveries of recent times is that the complex patterns we find in life are often produced when all of the individuals in a group follow the same simple rule. This process of "self-organization" reveals itself in the inanimate worlds of crystals and seashells, but as Len Fisher shows, it is also evident in living organisms, from fish to ants to human beings. The coordinated movements of fish in shoals, for example, arise from the simple rule: "Follow the fish in front." Traffic flow arises from simple rules: "Keep your distance" and "Keep to the right."Now, in his new book, Fisher shows how we can manage our complex social lives in an ever more chaotic world. His investigation encompasses topics ranging from "swarm intelligence" to the science of parties and the best ways to start a fad. Finally, Fisher sheds light on the beauty and utility of complexity theory. An entertaining journey into the science of everyday life, The Perfect Swarm will delight anyone who wants to understand the complex situations in which we so often find ourselves.

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Data Mining and Market Intelligence for Optimal Marketing Returns Review

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(More customer reviews)This is the best market analytics book I have ever read. It provides a very complete, detailed, thorough and practical way to apply quantitative modelling, techniques, and methods to solve everyday problems in marketing, whether that is market planning, market investment, marketing design or implementation. High recommended!!!

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The authors present a practical and highly informative perspective on the elements that are crucial to the success of a marketing campaign. Unlike books that are either too theoretical to be of practical use to practitioners, or too soft to serve as solid and measurable implementation guidelines, this book focuses on the integration of established quantitative techniques into real life case studies that are immediately relevant to marketing practitioners.* Provides a dual treatment of market research and data mining * Uses a how-to approach for professionals with illustrative case studies in addition to theory * Includes practical tips on how to create executive reports, dashboards, and a market intelligence infrastructure

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Statistical Evidence in Medical Trials: Mountain or Molehill, What Do the Data Really Tell Us? Review

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(More customer reviews)This book is an extremely well written and well organized discussion covering what makes a good paper ... good. It is not a mathematical statistics text. Instead it covers the methodological issues critical for good clinical research. The chapters cover: how control subjects are selected, who was not included, the size of the effects (as opposed to the p-values), collaborative data from other studies and meta analysis. The one "statistics" chapter has the best short coverage I have read on p-values, type I and II errors, confidence intervals, odds ratios/relative risks, survival analysis, prevalence and incidence. Finally there is a very brief but exceptionally useful chapter on searching for medical articles using tools beyond to the common ones like PubMed.
One standout feature of this book is the authors use of illustrative clinical examples. Every main topic is supported by references, with brief summaries of interesting research articles. The organization allows these examples to flow nicely and to reinforce the author's points.
Another great feature is the use of summary sections that can be turned into checklists for reviewing articles.
If you are looking for a book on how to evaluate the methodological issues in research get this.

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Statistical Evidence in Medical Trials is a lucid, well-written and entertaining text that addresses common pitfalls in evaluating medical research. Including extensive use of publications from the medical literature and a non-technical account of how to appraise the quality of evidence presented in these publications, this book is ideal for health care professionals, students in medical or nursing schools, researchers and students in statistics, and anyone needing to assess the evidence published in medical journals.

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Mass Media Research: An Introduction Review

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(More customer reviews)The major task in learning research methods involves developing the necessary skills to analyze and assess research data. This superb book takes you into the mindset of seasoned mass media research professionals sharing the essential truth about mass media research. The authors' years of expertise are apparent. Their goal, to introduce the reader to mass media research using a minimum of technical terms and a maximum of practical guidelines, is achieved with an entertaining mix of humorous insights and sage advice. The text is a valuable resource for both beginners and advanced researchers alike. The scope is truly comprehensive, the writing style clear and accessible. Mass Media Research is an absolute must for every mass media research student and professional.

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Quality media is the result of meticulous research. MASS MEDIA RESEARCH: AN INTRODUCTION, 9e, shows you how it happens--from content analysis to surveys to experimental research--then gives you expert tips on analyzing the media you encounter in your daily life. The Ninth Edition is packed with study tools and review aids to help you succeed in your course.

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