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Models For Investors In Real World Markets
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Book Synopsis Models for Investors in Real World Markets by : James R. Thompson
Download or read book Models for Investors in Real World Markets written by James R. Thompson and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: * Considers neoclassical models in light of results that can go wrong with them to bring about better models. * Questions the assumption that markets clear quickly. * Offers a timely examination of the LTCM collapse. * Written by a group of well-respected and highly qualified authors.
Book Synopsis Equity Markets, Valuation, and Analysis by : H. Kent Baker
Download or read book Equity Markets, Valuation, and Analysis written by H. Kent Baker and published by John Wiley & Sons. This book was released on 2020-09-01 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sharpen your understanding of the financial markets with this incisive volume Equity Markets, Valuation, and Analysis brings together many of the leading practitioner and academic voices in finance to produce a comprehensive and empirical examination of equity markets. Masterfully written and edited by experts in the field, Equity Markets, Valuation, and Analysis introduces the basic concepts and applications that govern the area before moving on to increasingly intricate treatments of sub-fields and market trends. The book includes in-depth coverage of subjects including: · The latest trends and research from across the globe · The controversial issues facing the field of valuation and the future outlook for the field · Empirical evidence and research on equity markets · How investment professionals analyze and manage equity portfolios This book balances its comprehensive discussion of the empirical foundations of equity markets with the perspectives of financial experts. It is ideal for professional investors, financial analysts, and undergraduate and graduate students in finance.
Book Synopsis Forecasting Expected Returns in the Financial Markets by : Stephen Satchell
Download or read book Forecasting Expected Returns in the Financial Markets written by Stephen Satchell and published by Elsevier. This book was released on 2011-04-08 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting returns is as important as forecasting volatility in multiple areas of finance. This topic, essential to practitioners, is also studied by academics. In this new book, Dr Stephen Satchell brings together a collection of leading thinkers and practitioners from around the world who address this complex problem using the latest quantitative techniques. *Forecasting expected returns is an essential aspect of finance and highly technical *The first collection of papers to present new and developing techniques *International authors present both academic and practitioner perspectives
Book Synopsis A Random Walk Down Wall Street by : Burton Gordon Malkiel
Download or read book A Random Walk Down Wall Street written by Burton Gordon Malkiel and published by W. W. Norton & Company. This book was released on 2007 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: C.1 MEMORIAL GIFT. 03-28-2008. $29.95.
Book Synopsis A NASDAQ Market Simulation by : Vincent Darley
Download or read book A NASDAQ Market Simulation written by Vincent Darley and published by World Scientific. This book was released on 2007 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: This pioneering book describes the applications of agent-based modeling to financial markets. It presents a new paradigm for finance, where markets are treated as complex systems whose behavior emerges as a result of interactions of market participants, market institutions, and market rules. This includes both a presentation of the conceptual model and its software implementation. It also summarises the result of the profound research on the successful practical application of this new approach to answer questions regarding the Nasdaq Stock MarketOCOs decimalization that was implemented in 2001. The book presents conceptual foundations for modeling markets as complex systems. It describes the agent-based model of the Nasdaq stock market, including strategies used by market-makers and investors, market participants interactions, and impacts of rules and regulations. It includes analyses of simulation behavior, comparison with the behaviors observed in the real-world markets (existence of fat tails, spread clustering, etc.), and predictions about possible outcomes of decimalization. A framework for calibrating the market behavior and individual market-makers strategies to historical data is also presented."
Book Synopsis Information Computing and Automation by :
Download or read book Information Computing and Automation written by and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Endowment Model of Investing by : Martin L. Leibowitz
Download or read book The Endowment Model of Investing written by Martin L. Leibowitz and published by John Wiley & Sons. This book was released on 2010-03-02 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: A cutting-edge look at the endowment model of investing Many larger endowments and foundations have adopted a broadly diversified asset allocation strategy with only a small amount of traditional U.S. equities and bonds. This technique, known as the "endowment model of investing," has demonstrated consistent long-term performance and attracted the attention of numerous institutional and individual investors. With The Endowment Model of Investing Leibowitz, Bova, and Hammond take a closer look at the endowment model with customary research sophistication and attention to detail. Throughout the book, they examine how the model provides truly outstanding real returns, while keeping a close eye on the risks associated with this method of investing. Along the way, the authors offer practical advice on incorporating the endowment model into your own investment endeavors and reveal what it takes to make this method work in the real world. Details the growing debate about the endowment model of investing and discusses how to use it successfully Written by an authority on endowment investing and non-traditional asset allocation strategies Offers expert insights on understanding risk and return in non traditional asset allocation If you want to gain a better grasp of one of the most successful forms of investing, then The Endowment Model of Investing is a book you need to read.
Book Synopsis Nasdaq Market Simulation, A: Insights On A Major Market From The Science Of Complex Adaptive Systems by : Vincent Darley
Download or read book Nasdaq Market Simulation, A: Insights On A Major Market From The Science Of Complex Adaptive Systems written by Vincent Darley and published by World Scientific. This book was released on 2007-03-21 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: This pioneering book describes the applications of agent-based modeling to financial markets. It presents a new paradigm for finance, where markets are treated as complex systems whose behavior emerges as a result of interactions of market participants, market institutions, and market rules. This includes both a presentation of the conceptual model and its software implementation. It also summarises the result of the profound research on the successful practical application of this new approach to answer questions regarding the NASDAQ Stock Market's decimalization that was implemented in 2001.The book presents conceptual foundations for modeling markets as complex systems. It describes the agent-based model of the NASDAQ stock market, including strategies used by market-makers and investors, market participants interactions, and impacts of rules and regulations. It includes analyses of simulation behavior, comparison with the behaviors observed in the real-world markets (existence of fat tails, spread clustering, etc.), and predictions about possible outcomes of decimalization. A framework for calibrating the market behavior and individual market-makers strategies to historical data is also presented.
Book Synopsis New Frontiers in Applied Artificial Intelligence by : Ngoc Thanh Nguyen
Download or read book New Frontiers in Applied Artificial Intelligence written by Ngoc Thanh Nguyen and published by Springer Science & Business Media. This book was released on 2008-06-03 with total page 896 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 21st International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2008, held in Wroclaw, Poland, in June 2008. The 75 revised full papers presented were carefully reviewed and selected from 302 submissions. The papers are organized in topical sections on computer vision, fuzzy system applications, robot and manufacturing, data mining and KDS, neural networks, machine learning, natural language processing, internet application and education, heuristic search, application systems, agent-based system, evolutionary and genetic algorithms, knowledge management, and other applications. The book concludes with 15 contributions from the following special sessions: knowledge driven manufacturing systems, joint session on adaptive networked systems and fuzzy knowledge bases, and software agents and multi-agent systems.
Book Synopsis Market Sense and Nonsense by : Jack D. Schwager
Download or read book Market Sense and Nonsense written by Jack D. Schwager and published by John Wiley & Sons. This book was released on 2012-10-19 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bestselling author, Jack Schwager, challenges the assumptions at the core of investment theory and practice and exposes common investor mistakes, missteps, myths, and misreads When it comes to investment models and theories of how markets work, convenience usually trumps reality. The simple fact is that many revered investment theories and market models are flatly wrong—that is, if we insist that they work in the real world. Unfounded assumptions, erroneous theories, unrealistic models, cognitive biases, emotional foibles, and unsubstantiated beliefs all combine to lead investors astray—professionals as well as novices. In this engaging new book, Jack Schwager, bestselling author of Market Wizards and The New Market Wizards, takes aim at the most perniciously pervasive academic precepts, money management canards, market myths and investor errors. Like so many ducks in a shooting gallery, Schwager picks them off, one at a time, revealing the truth about many of the fallacious assumptions, theories, and beliefs at the core of investment theory and practice. A compilation of the most insidious, fundamental investment errors the author has observed over his long and distinguished career in the markets Brings to light the fallacies underlying many widely held academic precepts, professional money management methodologies, and investment behaviors A sobering dose of real-world insight for investment professionals and a highly readable source of information and guidance for general readers interested in investment, trading, and finance Spans both traditional and alternative investment classes, covering both basic and advanced topics As in his best-selling Market Wizard series, Schwager manages the trick of covering material that is pertinent to professionals, yet writing in a style that is clear and accessible to the layman
Book Synopsis Empirical Model Building by : James R. Thompson
Download or read book Empirical Model Building written by James R. Thompson and published by John Wiley & Sons. This book was released on 2011-11-30 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition "This...novel and highly stimulating book, which emphasizes solving real problems...should be widely read. It will have a positive and lasting effect on the teaching of modeling and statistics in general." - Short Book Reviews This new edition features developments and real-world examples that showcase essential empirical modeling techniques Successful empirical model building is founded on the relationship between data and approximate representations of the real systems that generated that data. As a result, it is essential for researchers who construct these models to possess the special skills and techniques for producing results that are insightful, reliable, and useful. Empirical Model Building: Data, Models, and Reality, Second Edition presents a hands-on approach to the basic principles of empirical model building through a shrewd mixture of differential equations, computer-intensive methods, and data. The book outlines both classical and new approaches and incorporates numerous real-world statistical problems that illustrate modeling approaches that are applicable to a broad range of audiences, including applied statisticians and practicing engineers and scientists. The book continues to review models of growth and decay, systems where competition and interaction add to the complextiy of the model while discussing both classical and non-classical data analysis methods. This Second Edition now features further coverage of momentum based investing practices and resampling techniques, showcasing their importance and expediency in the real world. The author provides applications of empirical modeling, such as computer modeling of the AIDS epidemic to explain why North America has most of the AIDS cases in the First World and data-based strategies that allow individual investors to build their own investment portfolios. Throughout the book, computer-based analysis is emphasized and newly added and updated exercises allow readers to test their comprehension of the presented material. Empirical Model Building, Second Edition is a suitable book for modeling courses at the upper-undergraduate and graduate levels. It is also an excellent reference for applied statisticians and researchers who carry out quantitative modeling in their everyday work.
Book Synopsis Structural Equation Modeling by : Jichuan Wang
Download or read book Structural Equation Modeling written by Jichuan Wang and published by John Wiley & Sons. This book was released on 2012-07-31 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: A reference guide for applications of SEM using Mplus Structural Equation Modeling: Applications Using Mplus is intended as both a teaching resource and a reference guide. Written in non-mathematical terms, this book focuses on the conceptual and practical aspects of Structural Equation Modeling (SEM). Basic concepts and examples of various SEM models are demonstrated along with recently developed advanced methods, such as mixture modeling and model-based power analysis and sample size estimate for SEM. The statistical modeling program, Mplus, is also featured and provides researchers with a flexible tool to analyze their data with an easy-to-use interface and graphical displays of data and analysis results. Key features: Presents a useful reference guide for applications of SEM whilst systematically demonstrating various advanced SEM models, such as multi-group and mixture models using Mplus. Discusses and demonstrates various SEM models using both cross-sectional and longitudinal data with both continuous and categorical outcomes. Provides step-by-step instructions of model specification and estimation, as well as detail interpretation of Mplus results. Explores different methods for sample size estimate and statistical power analysis for SEM. By following the examples provided in this book, readers will be able to build their own SEM models using Mplus. Teachers, graduate students, and researchers in social sciences and health studies will also benefit from this book.
Book Synopsis Latent Curve Models by : Kenneth A. Bollen
Download or read book Latent Curve Models written by Kenneth A. Bollen and published by John Wiley & Sons. This book was released on 2005-12-23 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: An effective technique for data analysis in the social sciences The recent explosion in longitudinal data in the social sciences highlights the need for this timely publication. Latent Curve Models: A Structural Equation Perspective provides an effective technique to analyze latent curve models (LCMs). This type of data features random intercepts and slopes that permit each case in a sample to have a different trajectory over time. Furthermore, researchers can include variables to predict the parameters governing these trajectories. The authors synthesize a vast amount of research and findings and, at the same time, provide original results. The book analyzes LCMs from the perspective of structural equation models (SEMs) with latent variables. While the authors discuss simple regression-based procedures that are useful in the early stages of LCMs, most of the presentation uses SEMs as a driving tool. This cutting-edge work includes some of the authors' recent work on the autoregressive latent trajectory model, suggests new models for method factors in multiple indicators, discusses repeated latent variable models, and establishes the identification of a variety of LCMs. This text has been thoroughly class-tested and makes extensive use of pedagogical tools to aid readers in mastering and applying LCMs quickly and easily to their own data sets. Key features include: Chapter introductions and summaries that provide a quick overview of highlights Empirical examples provided throughout that allow readers to test their newly found knowledge and discover practical applications Conclusions at the end of each chapter that stress the essential points that readers need to understand for advancement to more sophisticated topics Extensive footnoting that points the way to the primary literature for more information on particular topics With its emphasis on modeling and the use of numerous examples, this is an excellent book for graduate courses in latent trajectory models as well as a supplemental text for courses in structural modeling. This book is an excellent aid and reference for researchers in quantitative social and behavioral sciences who need to analyze longitudinal data.
Book Synopsis Foundations of Linear and Generalized Linear Models by : Alan Agresti
Download or read book Foundations of Linear and Generalized Linear Models written by Alan Agresti and published by John Wiley & Sons. This book was released on 2015-01-15 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: A valuable overview of the most important ideas and results in statistical modeling Written by a highly-experienced author, Foundations of Linear and Generalized Linear Models is a clear and comprehensive guide to the key concepts and results of linearstatistical models. The book presents a broad, in-depth overview of the most commonly usedstatistical models by discussing the theory underlying the models, R software applications,and examples with crafted models to elucidate key ideas and promote practical modelbuilding. The book begins by illustrating the fundamentals of linear models, such as how the model-fitting projects the data onto a model vector subspace and how orthogonal decompositions of the data yield information about the effects of explanatory variables. Subsequently, the book covers the most popular generalized linear models, which include binomial and multinomial logistic regression for categorical data, and Poisson and negative binomial loglinear models for count data. Focusing on the theoretical underpinnings of these models, Foundations ofLinear and Generalized Linear Models also features: An introduction to quasi-likelihood methods that require weaker distributional assumptions, such as generalized estimating equation methods An overview of linear mixed models and generalized linear mixed models with random effects for clustered correlated data, Bayesian modeling, and extensions to handle problematic cases such as high dimensional problems Numerous examples that use R software for all text data analyses More than 400 exercises for readers to practice and extend the theory, methods, and data analysis A supplementary website with datasets for the examples and exercises An invaluable textbook for upper-undergraduate and graduate-level students in statistics and biostatistics courses, Foundations of Linear and Generalized Linear Models is also an excellent reference for practicing statisticians and biostatisticians, as well as anyone who is interested in learning about the most important statistical models for analyzing data.
Book Synopsis Models for Probability and Statistical Inference by : James H. Stapleton
Download or read book Models for Probability and Statistical Inference written by James H. Stapleton and published by John Wiley & Sons. This book was released on 2007-12-14 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readers Models for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping. Ideal as a textbook for a two-semester sequence on probability and statistical inference, early chapters provide coverage on probability and include discussions of: discrete models and random variables; discrete distributions including binomial, hypergeometric, geometric, and Poisson; continuous, normal, gamma, and conditional distributions; and limit theory. Since limit theory is usually the most difficult topic for readers to master, the author thoroughly discusses modes of convergence of sequences of random variables, with special attention to convergence in distribution. The second half of the book addresses statistical inference, beginning with a discussion on point estimation and followed by coverage of consistency and confidence intervals. Further areas of exploration include: distributions defined in terms of the multivariate normal, chi-square, t, and F (central and non-central); the one- and two-sample Wilcoxon test, together with methods of estimation based on both; linear models with a linear space-projection approach; and logistic regression. Each section contains a set of problems ranging in difficulty from simple to more complex, and selected answers as well as proofs to almost all statements are provided. An abundant amount of figures in addition to helpful simulations and graphs produced by the statistical package S-Plus(r) are included to help build the intuition of readers.
Book Synopsis Methods and Applications of Linear Models by : Ronald R. Hocking
Download or read book Methods and Applications of Linear Models written by Ronald R. Hocking and published by John Wiley & Sons. This book was released on 2013-07-01 with total page 724 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the Second Edition "An essential desktop reference book . . . it should definitely be on your bookshelf." —Technometrics A thoroughly updated book, Methods and Applications of Linear Models: Regression and the Analysis of Variance, Third Edition features innovative approaches to understanding and working with models and theory of linear regression. The Third Edition provides readers with the necessary theoretical concepts, which are presented using intuitive ideas rather than complicated proofs, to describe the inference that is appropriate for the methods being discussed. The book presents a unique discussion that combines coverage of mathematical theory of linear models with analysis of variance models, providing readers with a comprehensive understanding of both the theoretical and technical aspects of linear models. With a new focus on fixed effects models, Methods and Applications of Linear Models: Regression and the Analysis of Variance, Third Edition also features: Newly added topics including least squares, the cell means model, and graphical inspection of data in the AVE method Frequent conceptual and numerical examples for clarifying the statistical analyses and demonstrating potential pitfalls Graphics and computations developed using JMP® software to accompany the concepts and techniques presented Numerous exercises presented to test readers and deepen their understanding of the material An ideal book for courses on linear models and linear regression at the undergraduate and graduate levels, the Third Edition of Methods and Applications of Linear Models: Regression and the Analysis of Variance is also a valuable reference for applied statisticians and researchers who utilize linear model methodology.
Book Synopsis Structural Equation Modeling by : Sik-Yum Lee
Download or read book Structural Equation Modeling written by Sik-Yum Lee and published by John Wiley & Sons. This book was released on 2007-04-04 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: ***Winner of the 2008 Ziegel Prize for outstanding new book of the year*** Structural equation modeling (SEM) is a powerful multivariate method allowing the evaluation of a series of simultaneous hypotheses about the impacts of latent and manifest variables on other variables, taking measurement errors into account. As SEMs have grown in popularity in recent years, new models and statistical methods have been developed for more accurate analysis of more complex data. A Bayesian approach to SEMs allows the use of prior information resulting in improved parameter estimates, latent variable estimates, and statistics for model comparison, as well as offering more reliable results for smaller samples. Structural Equation Modeling introduces the Bayesian approach to SEMs, including the selection of prior distributions and data augmentation, and offers an overview of the subject’s recent advances. Demonstrates how to utilize powerful statistical computing tools, including the Gibbs sampler, the Metropolis-Hasting algorithm, bridge sampling and path sampling to obtain the Bayesian results. Discusses the Bayes factor and Deviance Information Criterion (DIC) for model comparison. Includes coverage of complex models, including SEMs with ordered categorical variables, and dichotomous variables, nonlinear SEMs, two-level SEMs, multisample SEMs, mixtures of SEMs, SEMs with missing data, SEMs with variables from an exponential family of distributions, and some of their combinations. Illustrates the methodology through simulation studies and examples with real data from business management, education, psychology, public health and sociology. Demonstrates the application of the freely available software WinBUGS via a supplementary website featuring computer code and data sets. Structural Equation Modeling: A Bayesian Approach is a multi-disciplinary text ideal for researchers and students in many areas, including: statistics, biostatistics, business, education, medicine, psychology, public health and social science.
