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Handbook of Alternative Data in Finance Volume I

Handbook of Alternative Data in Finance Volume I

Handbook of Alternative Data in Finance Volume I motivates and challenges the reader to explore and apply Alternative Data in finance. The book provides a robust and in-depth overview of Alternative Data including its definition characteristics difference from conventional data categories of Alternative Data Alternative Data providers and more. The book also offers a rigorous and detailed exploration of process application and delivery that should be practically useful to researchers and practitioners alike. Features Includes cutting edge applications in machine learning fintech and more Suitable for professional quantitative analysts and as a resource for postgraduates and researchers in financial mathematics Features chapters from many leading researchers and practitioners

GBP 140.00
1

Performance Reliability and Availability Evaluation of Computational Systems Volume I Performance and Background

Performance Reliability and Availability Evaluation of Computational Systems Volume I Performance and Background

This textbook intends to be a comprehensive and substantially self-contained two-volume book covering performance reliability and availability evaluation subjects. The volumes focus on computing systems although the methods may also be applied to other systems. The first volume covers Chapter 1 to Chapter 14 whose subtitle is ``Performance Modeling and Background. The second volume encompasses Chapter 15 to Chapter 25 and has the subtitle ``Reliability and Availability Modeling Measuring and Workload and Lifetime Data Analysis. This text is helpful for computer performance professionals for supporting planning design configuring and tuning the performance reliability and availability of computing systems. Such professionals may use these volumes to get acquainted with specific subjects by looking at the particular chapters. Many examples in the textbook on computing systems will help them understand the concepts covered in each chapter. The text may also be helpful for the instructor who teaches performance reliability and availability evaluation subjects. Many possible threads could be configured according to the interest of the audience and the duration of the course. Chapter 1 presents a good number of possible courses programs that could be organized using this text. Volume I is composed of the first two parts besides Chapter 1. Part I gives the knowledge required for the subsequent parts of the text. This part includes six chapters. It covers an introduction to probability descriptive statistics and exploratory data analysis random variables moments covariance some helpful discrete and continuous random variables Taylor series inference methods distribution fitting regression interpolation data scaling distance measures and some clustering methods. Part II presents methods for performance evaluation modeling such as operational analysis Discrete-Time Markov Chains (DTMC) and Continuous Time Markov Chains (CTMC) Markovian queues Stochastic Petri nets (SPN) and discrete event simulation. | Performance Reliability and Availability Evaluation of Computational Systems Volume I Performance and Background

GBP 120.00
1

Promoting Statistical Practice and Collaboration in Developing Countries

Promoting Statistical Practice and Collaboration in Developing Countries

Rarely but just often enough to rebuild hope something happens to confound my pessimism about the recent unprecedented happenings in the world. This book is the most recent instance and I think that all its readers will join me in rejoicing at the good it seeks to do. It is an example of the kind of international comity and collaboration that we could and should undertake to solve various societal problems. This book is a beautiful example of the power of the possible. [It] provides a blueprint for how the LISA 2020 model can be replicated in other fields. Civil engineers or accountants or nurses or any other profession could follow this outline to share expertise and build capacity and promote progress in other countries. It also contains some tutorials for statistical literacy across several fields. The details would change of course but ideas are durable and the generalizations seem pretty straightforward. This book shows every other profession where and how to stand in order to move the world. I urge every researcher to get a copy! —David Banks from the Foreword Promoting Statistical Practice and Collaboration in Developing Countries provides new insights into the current issues and opportunities in international statistics education statistical consulting and collaboration particularly in developing countries around the world. The book addresses the topics discussed in individual chapters from the perspectives of the historical context the present state and future directions of statistical training and practice so that readers may fully understand the challenges and opportunities in the field of statistics and data science especially in developing countries. Features • Reference point on statistical practice in developing countries for researchers scholars students and practitioners • Comprehensive source of state-of-the-art knowledge on creating statistical collaboration laboratories within the field of data science and statistics • Collection of innovative statistical teaching and learning techniques in developing countries Each chapter consists of independent case study contributions on a particular theme that are developed with a common structure and format. The common goal across the chapters is to enhance the exchange of diverse educational and action-oriented information among our intended audiences which include practitioners researchers students and statistics educators in developing countries.

GBP 105.00
1

The Navier-Stokes Problem in the 21st Century

The Navier-Stokes Problem in the 21st Century

Praise for the first edition “The author is an outstanding expert in harmonic analysis who has made important contributions. The book contains rigorous proofs of a number of the latest results in the field. I strongly recommend the book to postgraduate students and researchers working on challenging problems of harmonic analysis and mathematical theory of Navier-Stokes equations. —Gregory Seregin St Hildas College Oxford University “This is a great book on the mathematical aspects of the fundamental equations of hydrodynamics the incompressible Navier-Stokes equations. It covers many important topics and recent results and gives the reader a very good idea about where the theory stands at present. ”—Vladimir Sverak University of Minnesota The complete resolution of the Navier–Stokes equation—one of the Clay Millennium Prize Problems—remains an important open challenge in partial differential equations (PDEs) research despite substantial studies on turbulence and three-dimensional fluids. The Navier–Stokes Problem in the 21st Century Second Edition continues to provide a self-contained guide to the role of harmonic analysis in the PDEs of fluid mechanics now revised to include fresh examples theorems results and references that have become relevant since the first edition published in 2016. | The Navier-Stokes Problem in the 21st Century

GBP 99.99
1

Multiplicative Differential Equations Two Volume Set

Multiplicative Differential Equations Two Volume Set

Multiplicative Differential Equations: Volume I is the first part of a comprehensive approach to the subject. It continues a series of books written by the authors on multiplicative geometric approaches to key mathematical topics. This volume begins with a basic introduction to multiplicative differential equations and then moves on to first and second order equations as well as the question of existence and unique of solutions. Each chapter ends with a section of practical problems. The book is accessible to graduate students and researchers in mathematics physics engineering and biology. Multiplicative Differential Equations: Volume 2 is the second part of a comprehensive approach to the subject. It continues a series of books written by the authors on multiplicative geometric approaches to key mathematical topics. This volume is devoted to the theory of multiplicative differential systems. The asymptotic behavior of the solutions of such systems is studied. Stability theory for multiplicative linear and nonlinear systems is introduced and boundary value problems for second order multiplicative linear and nonlinear equations are explored. The authors also present first order multiplicative partial differential equations. Each chapter ends with a section of practical problems. The book is accessible to graduate students and researchers in mathematics physics engineering and biology. | Multiplicative Differential Equations Two Volume Set

GBP 170.00
1

Ratio of Momentum Diffusivity to Thermal Diffusivity Introduction Meta-analysis and Scrutinization

Ratio of Momentum Diffusivity to Thermal Diffusivity Introduction Meta-analysis and Scrutinization

This book presents a systematic introduction practical meaning and measurement of thermo-physical properties (i. e. viscosity density thermal conductivity specific heat capacity and thermal diffusivity) associated with the Prandtl number. The method of slope linear regression through the data points is presented in this textbook as a methodology for a deeper and insightful scrutinization. The book serves as a reference book for scientific investigators Teachers of Fluid Mechanics Experts on Heat and Mass Transfer Researchers on Boundary layer flows Mechanical and Chemical Engineers Physicists and Postgraduate Students working on transport phenomena who need theoretical and empirical reviews on the impact of increasing the ratio of momentum diffusivity to thermal diffusivity. Features: A systematic overview of the state-of-the-art in statistical methodology for understanding changes between dependent and independent variables. Pointers to some theoretical and empirical reviews on Prandtl number. Presents in-depth analysis of various self-similar flows emphasizing stretching induced flows nanofluid dynamics suction injection free convection mixed convection and forced convection. Insightful study on thermal radiation heat sour heat sink energy flux due to concentration gradient mass flux due to temperature gradient thermo-capillary convection flow Joule heating viscous dissipation thermal stratification thermophoresis and Brownian motion of particles. | Ratio of Momentum Diffusivity to Thermal Diffusivity Introduction Meta-analysis and Scrutinization

GBP 150.00
1

Principles of Uncertainty

Principles of Uncertainty

Praise for the first edition: Principles of Uncertainty is a profound and mesmerising book on the foundations and principles of subjectivist or behaviouristic Bayesian analysis. … the book is a pleasure to read. And highly recommended for teaching as it can be used at many different levels. … A must-read for sure!—Christian Robert CHANCE It's a lovely book one that I hope will be widely adopted as a course textbook. —Michael Jordan University of California Berkeley USA Like the prize-winning first edition Principles of Uncertainty Second Edition is an accessible comprehensive text on the theory of Bayesian Statistics written in an appealing inviting style and packed with interesting examples. It presents an introduction to the subjective Bayesian approach which has played a pivotal role in game theory economics and the recent boom in Markov Chain Monte Carlo methods. This new edition has been updated throughout and features new material on Nonparametric Bayesian Methods the Dirichlet distribution a simple proof of the central limit theorem and new problems. Key Features: First edition won the 2011 DeGroot Prize Well-written introduction to theory of Bayesian statistics Each of the introductory chapters begins by introducing one new concept or assumption Uses just-in-time mathematics—the introduction to mathematical ideas just before they are applied

GBP 99.99
1

The Theory of Statistical Implicative Analysis Or the Implausibility of Falsehood ... When the Exception Confirms the Rule

The Theory of Statistical Implicative Analysis Or the Implausibility of Falsehood ... When the Exception Confirms the Rule

This book summarizes the methods and concepts of Statistical Implicative Analysis (SIA) created by Régis Gras in the 1980s to study in a new way the behavioural responses of French pupils to mathematics tests. Using a multidimensional non-symmetrical data analysis method SIA crosses a set of subjects or objects with a set of variables. It effectively complements traditional correlational and psychometric methods. SIA through its various extensions is today presented as a broad Artificial Intelligence method aimed at extracting trends and possible causalities in the form of rules from a set of variables. It is based on the unlikeliness of the existence of these relationships i. e. on the relative weakness of their counter-examples compared to what chance alone would produce. It establishes a dual topological relationship between the set of subjects and the set of variables. Many applications of this approach driving forces or crucibles for the development of SIA have concerned and still concern various fields such as didactics evaluation and assessment psychology sociology medicine biology economics art history and others. Key Features: Presents the foundations and representations of SIA Provides extensions of variable sets and subjects Includes a bonus exercise | The Theory of Statistical Implicative Analysis Or the Implausibility of Falsehood . When the Exception Confirms the Rule

GBP 120.00
1

Bayesian Nonparametrics for Causal Inference and Missing Data

Bayesian Nonparametrics for Causal Inference and Missing Data

Bayesian Nonparametrics for Causal Inference and Missing Data provides an overview of flexible Bayesian nonparametric (BNP) methods for modeling joint or conditional distributions and functional relationships and their interplay with causal inference and missing data. This book emphasizes the importance of making untestable assumptions to identify estimands of interest such as missing at random assumption for missing data and unconfoundedness for causal inference in observational studies. Unlike parametric methods the BNP approach can account for possible violations of assumptions and minimize concerns about model misspecification. The overall strategy is to first specify BNP models for observed data and then to specify additional uncheckable assumptions to identify estimands of interest. The book is divided into three parts. Part I develops the key concepts in causal inference and missing data and reviews relevant concepts in Bayesian inference. Part II introduces the fundamental BNP tools required to address causal inference and missing data problems. Part III shows how the BNP approach can be applied in a variety of case studies. The datasets in the case studies come from electronic health records data survey data cohort studies and randomized clinical trials. Features • Thorough discussion of both BNP and its interplay with causal inference and missing data • How to use BNP and g-computation for causal inference and non-ignorable missingness • How to derive and calibrate sensitivity parameters to assess sensitivity to deviations from uncheckable causal and/or missingness assumptions • Detailed case studies illustrating the application of BNP methods to causal inference and missing data • R code and/or packages to implement BNP in causal inference and missing data problems The book is primarily aimed at researchers and graduate students from statistics and biostatistics. It will also serve as a useful practical reference for mathematically sophisticated epidemiologists and medical researchers.

GBP 90.00
1

Introduction to Stochastic Level Crossing Techniques

Introduction to Stochastic Level Crossing Techniques

Introduction to Stochastic Level Crossing Techniques describes stochastic models and their analysis using the System Point Level Crossing method (abbreviated SPLC or LC). This involves deriving probability density functions (pdfs) or cumulative probability distribution functions (cdfs) of key random variables applying simple level-crossing limit theorems developed by the author. The pdfs and/or cdfs are used to specify operational characteristics about the stochastic model of interest. The chapters describe distinct stochastic models and associated key random variables in the models. For each model a figure of a typical sample path (realization i. e. tracing over time) of the key random variable is displayed. For each model an analytic (Volterra) integral equation for the stationary pdf of the key random variable is created−by inspection of the sample path using the simple LC limit theorems. This LC method bypasses a great deal of algebra usually required by other methods of analysis. The integral equations will be solved directly or computationally. This book is meant for students of mathematics management science engineering natural sciences and researchers who use applied probability. It will also be useful to technical workers in a range of professions. Key Features: A description of one representative stochastic model (e. g. a single-server M/G/1 queue; a multiple server M/M/c queue; an inventory system; etc. ) Construction of a typical sample path of the key random variable of interest (e. g. the virtual waiting time or workload in queues; the net on-hand inventory in inventory systems; etc. ) Statements of the simple LC theorems which connect the sample-path upcrossing and downcrossing rates across state-space levels to simple mathematical functions of the stationary pdf of the key random variable at those state-space levels Creation of (usually Volterra) integral equations for the stationary pdf of the key random variable by inspection of the sample path Direct analytic solution of the integral equations where feasible; or computational solutions of the integral equations Use of the derived stationary pdfs for obtaining operational characteristics of the model

GBP 120.00
1

Financial Mathematics Two Volume Set

Financial Mathematics Two Volume Set

This textbook provides complete coverage of discrete-time financial models that form the cornerstones of financial derivative pricing theory. Unlike similar texts in the field this one presents multiple problem-solving approaches linking related comprehensive techniques for pricing different types of financial derivatives. Key features: In-depth coverage of discrete-time theory and methodology. Numerous fully worked out examples and exercises in every chapter. Mathematically rigorous and consistent yet bridging various basic and more advanced concepts. Judicious balance of financial theory mathematical and computational methods. Guide to Material. This revision contains: Almost 200 pages worth of new material in all chapters. A new chapter on elementary probability theory. An expanded the set of solved problems and additional exercises. Answers to all exercises. This book is a comprehensive self-contained and unified treatment of the main theory and application of mathematical methods behind modern-day financial mathematics. Table of Contents List of Figures and Tables Preface I Introduction to Pricing and Management of Financial Securities 1 Mathematics of Compounding 2 Primer on Pricing Risky Securities 3 Portfolio Management 4 Primer on Derivative Securities II Discrete-Time Modelling 5 Single-Period Arrow–Debreu Models 6 Introduction to Discrete-Time Stochastic Calculus 7 Replication and Pricing in the Binomial Tree Model 8 General Multi-Asset Multi-Period Model Appendices A Elementary Probability Theory B Glossary of Symbols and Abbreviations C Answers and Hints to Exercises References Index Biographies Giuseppe Campolieti is Professor of Mathematics at Wilfrid Laurier University in Waterloo Canada. He has been Natural Sciences and Engineering Research Council postdoctoral research fellow and university research fellow at the University of Toronto. In 1998 he joined the Masters in Mathematical Finance as an instructor and later as an adjunct professor in financial mathematics until 2002. Dr. Campolieti also founded a financial software and consulting company in 1998. He joined Laurier in 2002 as Associate Professor of Mathematics and as SHARCNET Chair in Financial Mathematics. Roman N. Makarov is Associate Professor and Chair of Mathematics at Wilfrid Laurier University. Prior to joining Laurier in 2003 he was an Assistant Professor of Mathematics at Siberian State University of Telecommunications and Informatics and a senior research fellow at the Laboratory of Monte Carlo Methods at the Institute of Computational Mathematics and Mathematical Geophysics in Novosibirsk Russia. | Financial Mathematics Two Volume Set

GBP 130.00
1

Theory of Statistical Inference

Theory of Statistical Inference

Theory of Statistical Inference is designed as a reference on statistical inference for researchers and students at the graduate or advanced undergraduate level. It presents a unified treatment of the foundational ideas of modern statistical inference and would be suitable for a core course in a graduate program in statistics or biostatistics. The emphasis is on the application of mathematical theory to the problem of inference leading to an optimization theory allowing the choice of those statistical methods yielding the most efficient use of data. The book shows how a small number of key concepts such as sufficiency invariance stochastic ordering decision theory and vector space algebra play a recurring and unifying role. The volume can be divided into four sections. Part I provides a review of the required distribution theory. Part II introduces the problem of statistical inference. This includes the definitions of the exponential family invariant and Bayesian models. Basic concepts of estimation confidence intervals and hypothesis testing are introduced here. Part III constitutes the core of the volume presenting a formal theory of statistical inference. Beginning with decision theory this section then covers uniformly minimum variance unbiased (UMVU) estimation minimum risk equivariant (MRE) estimation and the Neyman-Pearson test. Finally Part IV introduces large sample theory. This section begins with stochastic limit theorems the δ-method the Bahadur representation theorem for sample quantiles large sample U-estimation the Cramér-Rao lower bound and asymptotic efficiency. A separate chapter is then devoted to estimating equation methods. The volume ends with a detailed development of large sample hypothesis testing based on the likelihood ratio test (LRT) Rao score test and the Wald test. Features This volume includes treatment of linear and nonlinear regression models ANOVA models generalized linear models (GLM) and generalized estimating equations (GEE). An introduction to decision theory (including risk admissibility classification Bayes and minimax decision rules) is presented. The importance of this sometimes overlooked topic to statistical methodology is emphasized. The volume emphasizes throughout the important role that can be played by group theory and invariance in statistical inference. Nonparametric (rank-based) methods are derived by the same principles used for parametric models and are therefore presented as solutions to well-defined mathematical problems rather than as robust heuristic alternatives to parametric methods. Each chapter ends with a set of theoretical and applied exercises integrated with the main text. Problems involving R programming are included. Appendices summarize the necessary background in analysis matrix algebra and group theory.

GBP 99.99
1