Copula-Based Markov Models for Time Series

Copula-Based Markov Models for Time Series
Title Copula-Based Markov Models for Time Series PDF eBook
Author Li-Hsien Sun
Publisher Springer Nature
Pages 141
Release 2020-07-01
Genre Business & Economics
ISBN 9811549982

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This book provides statistical methodologies for time series data, focusing on copula-based Markov chain models for serially correlated time series. It also includes data examples from economics, engineering, finance, sport and other disciplines to illustrate the methods presented. An accessible textbook for students in the fields of economics, management, mathematics, statistics, and related fields wanting to gain insights into the statistical analysis of time series data using copulas, the book also features stand-alone chapters to appeal to researchers. As the subtitle suggests, the book highlights parametric models based on normal distribution, t-distribution, normal mixture distribution, Poisson distribution, and others. Presenting likelihood-based methods as the main statistical tools for fitting the models, the book details the development of computing techniques to find the maximum likelihood estimator. It also addresses statistical process control, as well as Bayesian and regression methods. Lastly, to help readers analyze their data, it provides computer codes (R codes) for most of the statistical methods.

Handbook of Financial Time Series

Handbook of Financial Time Series
Title Handbook of Financial Time Series PDF eBook
Author Torben Gustav Andersen
Publisher Springer Science & Business Media
Pages 1045
Release 2009-04-21
Genre Business & Economics
ISBN 3540712976

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The Handbook of Financial Time Series gives an up-to-date overview of the field and covers all relevant topics both from a statistical and an econometrical point of view. There are many fine contributions, and a preamble by Nobel Prize winner Robert F. Engle.

Hidden Markov Models for Time Series

Hidden Markov Models for Time Series
Title Hidden Markov Models for Time Series PDF eBook
Author Walter Zucchini
Publisher CRC Press
Pages 370
Release 2017-12-19
Genre Mathematics
ISBN 1482253844

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Hidden Markov Models for Time Series: An Introduction Using R, Second Edition illustrates the great flexibility of hidden Markov models (HMMs) as general-purpose models for time series data. The book provides a broad understanding of the models and their uses. After presenting the basic model formulation, the book covers estimation, forecasting, decoding, prediction, model selection, and Bayesian inference for HMMs. Through examples and applications, the authors describe how to extend and generalize the basic model so that it can be applied in a rich variety of situations. The book demonstrates how HMMs can be applied to a wide range of types of time series: continuous-valued, circular, multivariate, binary, bounded and unbounded counts, and categorical observations. It also discusses how to employ the freely available computing environment R to carry out the computations. Features Presents an accessible overview of HMMs Explores a variety of applications in ecology, finance, epidemiology, climatology, and sociology Includes numerous theoretical and programming exercises Provides most of the analysed data sets online New to the second edition A total of five chapters on extensions, including HMMs for longitudinal data, hidden semi-Markov models and models with continuous-valued state process New case studies on animal movement, rainfall occurrence and capture-recapture data

An Introduction to High-Frequency Finance

An Introduction to High-Frequency Finance
Title An Introduction to High-Frequency Finance PDF eBook
Author Ramazan Gençay
Publisher Elsevier
Pages 411
Release 2001-05-29
Genre Business & Economics
ISBN 008049904X

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Liquid markets generate hundreds or thousands of ticks (the minimum change in price a security can have, either up or down) every business day. Data vendors such as Reuters transmit more than 275,000 prices per day for foreign exchange spot rates alone. Thus, high-frequency data can be a fundamental object of study, as traders make decisions by observing high-frequency or tick-by-tick data. Yet most studies published in financial literature deal with low frequency, regularly spaced data. For a variety of reasons, high-frequency data are becoming a way for understanding market microstructure. This book discusses the best mathematical models and tools for dealing with such vast amounts of data.This book provides a framework for the analysis, modeling, and inference of high frequency financial time series. With particular emphasis on foreign exchange markets, as well as currency, interest rate, and bond futures markets, this unified view of high frequency time series methods investigates the price formation process and concludes by reviewing techniques for constructing systematic trading models for financial assets.

Economic Time Series

Economic Time Series
Title Economic Time Series PDF eBook
Author William R. Bell
Publisher CRC Press
Pages 544
Release 2018-11-14
Genre Mathematics
ISBN 1439846588

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Economic Time Series: Modeling and Seasonality is a focused resource on analysis of economic time series as pertains to modeling and seasonality, presenting cutting-edge research that would otherwise be scattered throughout diverse peer-reviewed journals. This compilation of 21 chapters showcases the cross-fertilization between the fields of time s

Convolution Copula Econometrics

Convolution Copula Econometrics
Title Convolution Copula Econometrics PDF eBook
Author Umberto Cherubini
Publisher Springer
Pages 99
Release 2016-12-01
Genre Business & Economics
ISBN 3319480154

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This book presents a novel approach to time series econometrics, which studies the behavior of nonlinear stochastic processes. This approach allows for an arbitrary dependence structure in the increments and provides a generalization with respect to the standard linear independent increments assumption of classical time series models. The book offers a solution to the problem of a general semiparametric approach, which is given by a concept called C-convolution (convolution of dependent variables), and the corresponding theory of convolution-based copulas. Intended for econometrics and statistics scholars with a special interest in time series analysis and copula functions (or other nonparametric approaches), the book is also useful for doctoral students with a basic knowledge of copula functions wanting to learn about the latest research developments in the field.

Feeling Smart

Feeling Smart
Title Feeling Smart PDF eBook
Author Eyal Winter
Publisher PublicAffairs
Pages 289
Release 2014-12-30
Genre Business & Economics
ISBN 1610394917

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Which is smarter -- your head or your gut? It's a familiar refrain: you're getting too emotional. Try and think rationally. But is it always good advice? In this surprising book, Eyal Winter asks a simple question: why do we have emotions? If they lead to such bad decisions, why hasn't evolution long since made emotions irrelevant? The answer is that, even though they may not behave in a purely logical manner, our emotions frequently lead us to better, safer, more optimal outcomes. In fact, as Winter discovers, there is often logic in emotion, and emotion in logic. For instance, many mutually beneficial commitments -- such as marriage, or being a member of a team -- are only possible when underscored by emotion rather than deliberate thought. The difference between pleasurable music and bad noise is mathematically precise; yet it is also something we feel at an instinctive level. And even though people are usually overconfident -- how can we all be above average? -- we often benefit from our arrogance. Feeling Smart brings together game theory, evolution, and behavioral science to produce a surprising and very persuasive defense of how we think, even when we don't.