Palgrave Handbook of Econometrics

Palgrave Handbook of Econometrics
Author: Terence C. Mills
Publisher: Palgrave Handbook of Econometr
Total Pages: 1432
Release: 2009-06-25
Genre: Business & Economics
ISBN:

Palgrave Handbooks of Econometrics comprises 'landmark' essays by the world's leading scholars and provides authoritative guidance in key areas of econometrics. With definitive contributions on the subject, the Handbook is an essential source for reference for professional econometricians, economists, researchers and students. Following the successful Palgrave Handbook of Econometrics: Volume 1, this second volume brings together leading academics working in econometrics today and explores applied econometrics. Volume 2 contains contributions on subjects including growth/development econometrics, computing, microeconomics, macroeconomics, finance, spatial and urban economics and international economics.

Martingale Limit Theory and Its Application

Martingale Limit Theory and Its Application
Author: P. Hall
Publisher: Academic Press
Total Pages: 321
Release: 2014-07-10
Genre: Mathematics
ISBN: 1483263223

Martingale Limit Theory and Its Application discusses the asymptotic properties of martingales, particularly as regards key prototype of probabilistic behavior that has wide applications. The book explains the thesis that martingale theory is central to probability theory, and also examines the relationships between martingales and processes embeddable in or approximated by Brownian motion. The text reviews the martingale convergence theorem, the classical limit theory and analogs, and the martingale limit theorems viewed as the rate of convergence results in the martingale convergence theorem. The book explains the square function inequalities, weak law of large numbers, as well as the strong law of large numbers. The text discusses the reverse martingales, martingale tail sums, the invariance principles in the central limit theorem, and also the law of the iterated logarithm. The book investigates the limit theory for stationary processes via corresponding results for approximating martingales and the estimation of parameters from stochastic processes. The text can be profitably used as a reference for mathematicians, advanced students, and professors of higher mathematics or statistics.

Stochastic Processes and Applications to Mathematical Finance

Stochastic Processes and Applications to Mathematical Finance
Author:
Publisher: World Scientific
Total Pages: 410
Release: 2004
Genre: Business & Economics
ISBN: 9812702857

This book contains 17 articles on stochastic processes (stochastic calculus and Malliavin calculus, functionals of Brownian motions and L(r)vy processes, stochastic control and optimization problems, stochastic numerics, and so on) and their applications to problems in mathematical finance.The proceedings have been selected for coverage in: OCo Index to Scientific & Technical Proceedings- (ISTP- / ISI Proceedings)OCo Index to Scientific & Technical Proceedings (ISTP CDROM version / ISI Proceedings)OCo Index to Social Sciences & Humanities Proceedings- (ISSHP- / ISI Proceedings)OCo Index to Social Sciences & Humanities Proceedings (ISSHP CDROM version / ISI Proceedings)OCo CC Proceedings OCo Engineering & Physical Sciences"

Statistical Models Based on Counting Processes

Statistical Models Based on Counting Processes
Author: Per K. Andersen
Publisher: Springer Science & Business Media
Total Pages: 779
Release: 2012-12-06
Genre: Mathematics
ISBN: 1461243483

Modern survival analysis and more general event history analysis may be effectively handled within the mathematical framework of counting processes. This book presents this theory, which has been the subject of intense research activity over the past 15 years. The exposition of the theory is integrated with careful presentation of many practical examples, drawn almost exclusively from the authors'own experience, with detailed numerical and graphical illustrations. Although Statistical Models Based on Counting Processes may be viewed as a research monograph for mathematical statisticians and biostatisticians, almost all the methods are given in concrete detail for use in practice by other mathematically oriented researchers studying event histories (demographers, econometricians, epidemiologists, actuarial mathematicians, reliability engineers and biologists). Much of the material has so far only been available in the journal literature (if at all), and so a wide variety of researchers will find this an invaluable survey of the subject.

Stochastic Processes And Applications To Mathematical Finance - Proceedings Of The Ritsumeikan International Symposium

Stochastic Processes And Applications To Mathematical Finance - Proceedings Of The Ritsumeikan International Symposium
Author: Jiro Akahori
Publisher: World Scientific
Total Pages: 410
Release: 2004-07-06
Genre: Mathematics
ISBN: 9814483095

This book contains 17 articles on stochastic processes (stochastic calculus and Malliavin calculus, functionals of Brownian motions and Lévy processes, stochastic control and optimization problems, stochastic numerics, and so on) and their applications to problems in mathematical finance.The proceedings have been selected for coverage in:• Index to Scientific & Technical Proceedings® (ISTP® / ISI Proceedings)• Index to Scientific & Technical Proceedings (ISTP CDROM version / ISI Proceedings)• Index to Social Sciences & Humanities Proceedings® (ISSHP® / ISI Proceedings)• Index to Social Sciences & Humanities Proceedings (ISSHP CDROM version / ISI Proceedings)• CC Proceedings — Engineering & Physical Sciences

Stochastic Processes and Applications to Mathematical Finance

Stochastic Processes and Applications to Mathematical Finance
Author: Jiro Akahori
Publisher: World Scientific
Total Pages: 410
Release: 2004
Genre: Mathematics
ISBN: 9812387781

This book contains articles on stochastic processes (stochastic calculus and Malliavin calculus, functionals of Brownian motions and Levy processes, stochastic control and optimization problems, stochastic numerics, and so on) and their applications to problems in mathematical finance. Examples of topics are applications of Malliavin calculus and numerical analysis to a new simulation scheme for calculating the price of financial derivatives, applications of the asymptotic expansion method in Malliavin calculus to financial problems, semimartingale decompositions under an enlargement of filtrations in connection with insider problems, and the problem of transaction costs in connection with stochastic control and optimization problems.

Modelling Nonlinear Economic Time Series

Modelling Nonlinear Economic Time Series
Author: Timo Teräsvirta
Publisher: OUP Oxford
Total Pages: 592
Release: 2010-12-16
Genre: Business & Economics
ISBN: 9780199587148

This book contains an extensive up-to-date overview of nonlinear time series models and their application to modelling economic relationships. It considers nonlinear models in stationary and nonstationary frameworks, and both parametric and nonparametric models are discussed. The book contains examples of nonlinear models in economic theory and presents the most common nonlinear time series models. Importantly, it shows the reader how to apply these models in practice. For thispurpose, the building of various nonlinear models with its three stages of model building: specification, estimation and evaluation, is discussed in detail and is illustrated by several examples involving both economic and non-economic data. Since estimation of nonlinear time series models is carried outusing numerical algorithms, the book contains a chapter on estimating parametric nonlinear models and another on estimating nonparametric ones.Forecasting is a major reason for building time series models, linear or nonlinear. The book contains a discussion on forecasting with nonlinear models, both parametric and nonparametric, and considers numerical techniques necessary for computing multi-period forecasts from them. The main focus of the book is on models of the conditional mean, but models of the conditional variance, mainly those of autoregressive conditional heteroskedasticity, receive attention as well. A separate chapter isdevoted to state space models. As a whole, the book is an indispensable tool for researchers interested in nonlinear time series and is also suitable for teaching courses in econometrics and time series analysis.

Stochastic Processes

Stochastic Processes
Author: Robert G. Gallager
Publisher: Cambridge University Press
Total Pages: 559
Release: 2013-12-12
Genre: Business & Economics
ISBN: 1107039754

The definitive textbook on stochastic processes, written by one of the world's leading information theorists, covering both theory and applications.

Classical Potential Theory and Its Probabilistic Counterpart

Classical Potential Theory and Its Probabilistic Counterpart
Author: Joseph L. Doob
Publisher: Springer Science & Business Media
Total Pages: 892
Release: 2001-01-12
Genre: Mathematics
ISBN: 9783540412069

From the reviews: "Here is a momumental work by Doob, one of the masters, in which Part 1 develops the potential theory associated with Laplace's equation and the heat equation, and Part 2 develops those parts (martingales and Brownian motion) of stochastic process theory which are closely related to Part 1". --G.E.H. Reuter in Short Book Reviews (1985)

Predictive Econometrics and Big Data

Predictive Econometrics and Big Data
Author: Vladik Kreinovich
Publisher: Springer
Total Pages: 788
Release: 2017-11-30
Genre: Technology & Engineering
ISBN: 3319709429

This book presents recent research on predictive econometrics and big data. Gathering edited papers presented at the 11th International Conference of the Thailand Econometric Society (TES2018), held in Chiang Mai, Thailand, on January 10-12, 2018, its main focus is on predictive techniques – which directly aim at predicting economic phenomena; and big data techniques – which enable us to handle the enormous amounts of data generated by modern computers in a reasonable time. The book also discusses the applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that employs mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. It is therefore important to develop data processing techniques that explicitly focus on prediction. The more data we have, the better our predictions will be. As such, these techniques are essential to our ability to process huge amounts of available data.