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Introduction to Statistical Methods for Financial Models
This book provides an introduction to the use of statistical concepts and methods to model and analyze financial data. The ten chapters of the book fall naturally into three sections. Chapters 1 to 3 cover some basic concepts of finance, focusing on the properties of returns on an asset. Chapters 4 through 6 cover aspects of portfolio theory and the methods of estimation needed to implement that theory. The remainder of the book, Chapters 7 through 10, discusses several models for financial data, along with the implications of those models for portfolio theory and for understanding the properties of return data. The audience for the book is students majoring in Statistics and Economics as well as in quantitative fields such as Mathematics and Engineering. Readers are assumed to have some background in statistical methods along with courses in multivariate calculus and linear algebra.
Analytic Methods in Sports
One of the greatest changes in the sports world in the past 20 years has been the use of mathematical methods to analyze performances, recognize trends and patterns, and predict results. Analytic Methods in Sports: Using Mathematics and Statistics to Understand Data from Baseball, Football, Basketball, and Other Sports, Second Edition provides a concise yet thorough introduction to the analytic and statistical methods that are useful in studying sports. The book gives you all the tools necessary to answer key questions in sports analysis. It explains how to apply the methods to sports data and interpret the results, demonstrating that the analysis of sports data is often different from stand...
Elements of Distribution Theory
This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics as well as for researchers who use statistical methods. Good backgrounds in calculus and linear algebra are important and a course in elementary mathematical analysis is useful, but not required. An appendix gives a detailed summary of the mathematical definitions and results that are used in the book. Topics covered range from the basic distribution and density functions, expectation, conditioning, characteristic functions, cumulants, convergence in distribution and the central limit theorem to more advanced concepts such as exchangeability, models with a group structure, asymptotic approximations to integrals, orthogonal polynomials and saddlepoint approximations. The emphasis is on topics useful in understanding statistical methodology; thus, parametric statistical models and the distribution theory associated with the normal distribution are covered comprehensively.
Teatro Grottesco
Thomas Ligotti is often cited as the most curious and remarkable figure in horror literature since H. P. Lovecraft. His work is noted by critics for its display of an exceptionally grotesque imagination and accomplished prose style. In his stories, Ligotti has followed a literary tradition that began with Edgar Allan Poe, portraying characters that are outside of anything that might be called normal life, depicting strange locales far off the beaten track, and rendering a grim vision of human existence as a perpetual nightmare. The horror stories collected in Teatro Grottesco feature tormented individuals who play out their doom in various odd little towns, as well as in dark sectors frequented by sinister and often blackly comical eccentrics. The cycle of narratives introduce readers to a freakish community of artists who encounter demonic perils that ultimately engulf their lives.
Analytic Methods in Sports
One of the greatest changes in the sports world in the past 20 years has been the use of mathematical methods to analyze performances, recognize trends and patterns, and predict results. Analytic Methods in Sports: Using Mathematics and Statistics to Understand Data from Baseball, Football, Basketball, and Other Sports, Second Edition provides a concise yet thorough introduction to the analytic and statistical methods that are useful in studying sports. The book gives you all the tools necessary to answer key questions in sports analysis. It explains how to apply the methods to sports data and interpret the results, demonstrating that the analysis of sports data is often different from stand...
Surrogates
Computer simulation experiments are essential to modern scientific discovery, whether that be in physics, chemistry, biology, epidemiology, ecology, engineering, etc. Surrogates are meta-models of computer simulations, used to solve mathematical models that are too intricate to be worked by hand. Gaussian process (GP) regression is a supremely flexible tool for the analysis of computer simulation experiments. This book presents an applied introduction to GP regression for modelling and optimization of computer simulation experiments. Features: • Emphasis on methods, applications, and reproducibility. • R code is integrated throughout for application of the methods. • Includes more than...
Exercises in Probability
Over 100 exercises with detailed solutions, insightful notes and references for further reading. Ideal for beginning researchers.
Vertical Density Representation And Its Applications
This book presents a new research topic in statistics — vertical density representation (VDR). The theory of VDR has been found to be useful for developing new ideas and methodologies in statistics and management science. The first paper related to VDR appeared in 1991. Several others have since been published and work is continuing on the topic. The purpose of this book is to survey the results presented in those papers and provide some new, unpublished results.VDR may be regarded as a special kind of transformation. By assuming that a variate is uniformly distributed on the contours of a given function in real n-dimensional space, and considering the density of the ordinate of the given ...
Asymptotic Theory Of Quantum Statistical Inference: Selected Papers
Quantum statistical inference, a research field with deep roots in the foundations of both quantum physics and mathematical statistics, has made remarkable progress since 1990. In particular, its asymptotic theory has been developed during this period. However, there has hitherto been no book covering this remarkable progress after 1990; the famous textbooks by Holevo and Helstrom deal only with research results in the earlier stage (1960s-1970s).This book presents the important and recent results of quantum statistical inference. It focuses on the asymptotic theory, which is one of the central issues of mathematical statistics and had not been investigated in quantum statistical inference u...
Semiparametric Efficiency Bounds for Microeconometric Models
In this survey, we evaluate estimators by comparing their asymptotic variances. The role of the efficiency bound, in this context, is to give a lower bound to the asymptotic variance of an estimator. An estimator with asymptotic variance equal to the efficiency bound can therefore be said to be asymptotically efficient. These bounds are also useful for understanding how the features of a given model affect the accuracy of parameter estimation.
