The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data. To make use of this data, the powerful methods in this book for working with quantitative information, particularly about volatility and risks, are essential. Strengths of this fully-revised edition include major additions to the R code and the advanced topics covered. Individual chapters cover, among other topics, multivariate distributions, copulas, Bayesian computations, risk management, and cointegration. Suggested prerequisites are basic knowledge of statistics and probability, matrices and linear algebra, and calculus. There is an appendix on probability, statistics and linear algebra. Practicing financial engineers will also find this book of interest.
This book emphasizes the applications of statistics and probability to finance. The basics of these subjects are reviewed and more advanced topics in statistics, such as regression, ARMA and GARCH models, the bootstrap, and nonparametric regression using splines, are introduced as needed. The book covers the classical methods of finance and it introduces the newer area of behavioral finance. Applications and use of MATLAB and SAS software are stressed. The book will serve as a text in courses aimed at advanced undergraduates and masters students. Those in the finance industry can use it for self-study.
Financial engineers have access to enormous quantities of data but need powerful methods for extracting quantitative information, particularly about volatility and risks. Key features of this textbook are: illustration of concepts with financial markets and economic data, R Labs with real-data exercises, and integration of graphical and analytic methods for modeling and diagnosing modeling errors. Despite some overlap with the author's undergraduate textbook Statistics and Finance: An Introduction, this book differs from that earlier volume in several important aspects: it is graduate-level; computations and graphics are done in R; and many advanced topics are covered, for example, multivariate distributions, copulas, Bayesian computations, VaR and expected shortfall, and cointegration. The prerequisites are basic statistics and probability, matrices and linear algebra, and calculus. Some exposure to finance is helpful.
This monograph provides an up-to-date discussion of analysis strategies for regression problems in which predictor variables are measured with errors. The analysis of nonlinear regression models includes generalized linear models, transform-both-sides models and quasilikelihood and variance function problems. The text concentrates on the general ideas and strategies of estimation and inference rather than being concerned with a specific problem. Measurement error occurs in many fields, such as biometry, epidemiology and economics. In particular, the book contains a large number of epidemiological examples. An outline of strategies for handling progressively more difficult problems is also provided.
This easy-to-follow applied book on semiparametric regression methods using R is intended to close the gap between the available methodology and its use in practice. Semiparametric regression has a large literature but much of it is geared towards data analysts who have advanced knowledge of statistical methods. While R now has a great deal of semiparametric regression functionality, many of these developments have not trickled down to rank-and-file statistical analysts. The authors assemble a broad range of semiparametric regression R analyses and put them in a form that is useful for applied researchers. There are chapters devoted to penalized spines, generalized additive models, grouped data, bivariate extensions of penalized spines, and spatial semi-parametric regression models. Where feasible, the R code is provided in the text, however the book is also accompanied by an external website complete with datasets and R code. Because of its flexibility, semiparametric regression has proven to be of great value with many applications in fields as diverse as astronomy, biology, medicine, economics, and finance. This book is intended for applied statistical analysts who have some familiarity with R.
This monograph provides a careful review of the major statistical techniques used to analyze regression data with nonconstant variability and skewness. The authors have developed statistical techniques--such as formal fitting methods and less formal graphical techniques-- that can be applied to many problems across a range of disciplines, including pharmacokinetics, econometrics, biochemical assays, and fisheries research. While the main focus of the book in on data transformation and weighting, it also draws upon ideas from diverse fields such as influence diagnostics, robustness, bootstrapping, nonparametric data smoothing, quasi-likelihood methods, errors-in-variables, and random coefficients. The authors discuss the computation of estimates and give numerous examples using real data. The book also includes an extensive treatment of estimating variance functions in regression.
It's been over a decade since the first edition of Measurement Error in Nonlinear Models splashed onto the scene, and research in the field has certainly not cooled in the interim. In fact, quite the opposite has occurred. As a result, Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition has been revamped and ex
The names on the cast-bronze plaques hanging in the National Baseball Hall of Fame embody the history and drama of the sport--they are the royalty of baseball. Yet many inductees believed their entry into the Hall was anything but guaranteed, and even some who waited by the phone for the fateful "call to the Hall" were stunned to hear the news. Reactions to the call varied from stoicism to overwhelming emotion, but for most of the 31 inductees interviewed in this book, it was a moment of reflection and gratitude. In other cases, the call came years too late and family members received the posthumous honor.
Working with babies and children is most successful when therapists have a complete understanding and overview of all appropriate treatment options, and the effects of early influences on child health and development. This book shows therapists how to consider these factors in order to work more effectively within their individual areas of expertise. Contributors from a wide range of disciplines, including Ann Diamond Weinstein, Michael Shea, Carolyn Goh, Graham Kennedy, Matthew Appleton, David Haas, Thomas Harms, Franz Ruppert, Anita Hegerty and Kate Rosati, explore the influence of pregnancy, birth and family dynamics on the physical and mental health of babies and children. They show how these factors relate to common complaints, such as excessive and different types of crying, chronic illnesses and poor immune systems, and behavioural and attachment issues, and how complementary approaches can be best applied to treat these issues. This book also offers helpful advice for working within multidisciplinary teams. Illustrated with case studies and including examples from current research, this book is a valuable resource for therapists from diverse disciplines.
It is a time when southern Africa teeters on a precipice. In Zimbabwe, government-orchestrated thugs engage in ethnic cleansing while neighbouring countries and Western powers turn a blind eye. But when a Zimbabwean minister is murdered 5000 miles from home, the British and American governments must scramble for political cover. Now the question is: who is responsible? And in Washington, DC, a retired army general and young lawyer discover themselves embroiled in an international conspiracy behind the answer: at the highest levels of governments, across the globe, and within an elite secret society known only as The Seven Watchmen.
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