Bayesian Statistics and New Generations

Bayesian Statistics and New Generations

Author: Raffaele Argiento

Publisher: Springer Nature

Published: 2019-11-21

Total Pages: 184

ISBN-13: 3030306119

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This book presents a selection of peer-reviewed contributions to the fourth Bayesian Young Statisticians Meeting, BAYSM 2018, held at the University of Warwick on 2-3 July 2018. The meeting provided a valuable opportunity for young researchers, MSc students, PhD students, and postdocs interested in Bayesian statistics to connect with the broader Bayesian community. The proceedings offer cutting-edge papers on a wide range of topics in Bayesian statistics, identify important challenges and investigate promising methodological approaches, while also assessing current methods and stimulating applications. The book is intended for a broad audience of statisticians, and demonstrates how theoretical, methodological, and computational aspects are often combined in the Bayesian framework to successfully tackle complex problems.


Introduction to Bayesian Econometrics

Introduction to Bayesian Econometrics

Author: Edward Greenberg

Publisher: Cambridge University Press

Published: 2013

Total Pages: 271

ISBN-13: 1107015316

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This textbook explains the basic ideas of subjective probability and shows how subjective probabilities must obey the usual rules of probability to ensure coherency. It defines the likelihood function, prior distributions and posterior distributions. It explains how posterior distributions are the basis for inference and explores their basic properties. Various methods of specifying prior distributions are considered, with special emphasis on subject-matter considerations and exchange ability. The regression model is examined to show how analytical methods may fail in the derivation of marginal posterior distributions. The remainder of the book is concerned with applications of the theory to important models that are used in economics, political science, biostatistics and other applied fields. New to the second edition is a chapter on semiparametric regression and new sections on the ordinal probit, item response, factor analysis, ARCH-GARCH and stochastic volatility models. The new edition also emphasizes the R programming language.


Bayesian Methods in Finance

Bayesian Methods in Finance

Author: Svetlozar T. Rachev

Publisher: John Wiley & Sons

Published: 2008-02-13

Total Pages: 351

ISBN-13: 0470249242

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Bayesian Methods in Finance provides a detailed overview of the theory of Bayesian methods and explains their real-world applications to financial modeling. While the principles and concepts explained throughout the book can be used in financial modeling and decision making in general, the authors focus on portfolio management and market risk management—since these are the areas in finance where Bayesian methods have had the greatest penetration to date.


Bayesian Multivariate Time Series Methods for Empirical Macroeconomics

Bayesian Multivariate Time Series Methods for Empirical Macroeconomics

Author: Gary Koop

Publisher: Now Publishers Inc

Published: 2010

Total Pages: 104

ISBN-13: 160198362X

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Bayesian Multivariate Time Series Methods for Empirical Macroeconomics provides a survey of the Bayesian methods used in modern empirical macroeconomics. These models have been developed to address the fact that most questions of interest to empirical macroeconomists involve several variables and must be addressed using multivariate time series methods. Many different multivariate time series models have been used in macroeconomics, but Vector Autoregressive (VAR) models have been among the most popular. Bayesian Multivariate Time Series Methods for Empirical Macroeconomics reviews and extends the Bayesian literature on VARs, TVP-VARs and TVP-FAVARs with a focus on the practitioner. The authors go beyond simply defining each model, but specify how to use them in practice, discuss the advantages and disadvantages of each and offer tips on when and why each model can be used.


Handbook of Financial Time Series

Handbook of Financial Time Series

Author: Torben Gustav Andersen

Publisher: Springer Science & Business Media

Published: 2009-04-21

Total Pages: 1045

ISBN-13: 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.


Bayesian Econometric Methods

Bayesian Econometric Methods

Author: Joshua Chan

Publisher: Cambridge University Press

Published: 2019-08-15

Total Pages: 491

ISBN-13: 1108423388

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Illustrates Bayesian theory and application through a series of exercises in question and answer format.


Big Data Technologies and Applications

Big Data Technologies and Applications

Author: Zeng Deze

Publisher: Springer Nature

Published: 2021-04-08

Total Pages: 209

ISBN-13: 3030728021

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This book constitutes the refereed post-conference proceedings of the 10th International Conference on Big Data Technologies and Applications, BDTA 2020, and the 13th International Conference on Wireless Internet, WiCON 2020, held in December 2020. Due to COVID-19 pandemic the conference was held virtually. The 9 full papers of BDTA 2020 were selected from 22 submissions and present all big data technologies, such as storage, search and management. WiCON 2020 received 18 paper submissions and after the reviewing process 5 papers were accepted. The main topics include wireless and communicating networks, wireless communication security, green wireless network architectures and IoT based applications.


Markov Chain Monte Carlo

Markov Chain Monte Carlo

Author: Dani Gamerman

Publisher: CRC Press

Published: 2006-05-10

Total Pages: 342

ISBN-13: 148229642X

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While there have been few theoretical contributions on the Markov Chain Monte Carlo (MCMC) methods in the past decade, current understanding and application of MCMC to the solution of inference problems has increased by leaps and bounds. Incorporating changes in theory and highlighting new applications, Markov Chain Monte Carlo: Stochastic Simul


Modeling and Forecasting Electricity Loads and Prices

Modeling and Forecasting Electricity Loads and Prices

Author: Rafal Weron

Publisher: John Wiley & Sons

Published: 2007-01-30

Total Pages: 192

ISBN-13: 0470059990

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This book offers an in-depth and up-to-date review of different statistical tools that can be used to analyze and forecast the dynamics of two crucial for every energy company processes—electricity prices and loads. It provides coverage of seasonal decomposition, mean reversion, heavy-tailed distributions, exponential smoothing, spike preprocessing, autoregressive time series including models with exogenous variables and heteroskedastic (GARCH) components, regime-switching models, interval forecasts, jump-diffusion models, derivatives pricing and the market price of risk. Modeling and Forecasting Electricity Loads and Prices is packaged with a CD containing both the data and detailed examples of implementation of different techniques in Matlab, with additional examples in SAS. A reader can retrace all the intermediate steps of a practical implementation of a model and test his understanding of the method and correctness of the computer code using the same input data. The book will be of particular interest to the quants employed by the utilities, independent power generators and marketers, energy trading desks of the hedge funds and financial institutions, and the executives attending courses designed to help them to brush up on their technical skills. The text will be also of use to graduate students in electrical engineering, econometrics and finance wanting to get a grip on advanced statistical tools applied in this hot area. In fact, there are sixteen Case Studies in the book making it a self-contained tutorial to electricity load and price modeling and forecasting.


Modelling Financial Time Series

Modelling Financial Time Series

Author: Stephen J. Taylor

Publisher: World Scientific

Published: 2008

Total Pages: 297

ISBN-13: 9812770852

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This book contains several innovative models for the prices of financial assets. First published in 1986, it is a classic text in the area of financial econometrics. It presents ARCH and stochastic volatility models that are often used and cited in academic research and are applied by quantitative analysts in many banks. Another often-cited contribution of the first edition is the documentation of statistical characteristics of financial returns, which are referred to as stylized facts. This second edition takes into account the remarkable progress made by empirical researchers during the past two decades from 1986 to 2006. In the new Preface, the author summarizes this progress in two key areas: firstly, measuring, modelling and forecasting volatility; and secondly, detecting and exploiting price trends. Sample Chapter(s). Chapter 1: Introduction (1,134 KB). Contents: Features of Financial Returns; Modelling Price Volatility; Forecasting Standard Deviations; The Accuracy of Autocorrelation Estimates; Testing the Random Walk Hypothesis; Forecasting Trends in Prices; Evidence Against the Efficiency of Futures Markets; Valuing Options; Appendix: A Computer Program for Modelling Financial Time Series. Readership: Academic researchers in finance & economics; quantitative analysts.