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Author: C. Wells
Publisher: Springer Science & Business Media
ISBN: 940158611X
Category : Business & Economics
Languages : en
Pages : 181
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Book Description
A non-technical introduction to the question of modeling with time-varying parameters, using the beta coefficient from Financial Economics as the main example. After a brief introduction to this coefficient for those not versed in finance, the book presents a number of rather well known tests for constant coefficients and then performs these tests on data from the Stockholm Exchange. The Kalman filter is then introduced and a simple example is used to demonstrate the power of the filter. The filter is then used to estimate the market model with time-varying betas. The book concludes with further examples of how the Kalman filter may be used in estimation models used in analyzing other aspects of finance. Since both the programs and the data used in the book are available for downloading, the book is especially valuable for students and other researchers interested in learning the art of modeling with time varying coefficients.
Author: C. Wells
Publisher: Springer Science & Business Media
ISBN: 940158611X
Category : Business & Economics
Languages : en
Pages : 181
Get Book Here
Book Description
A non-technical introduction to the question of modeling with time-varying parameters, using the beta coefficient from Financial Economics as the main example. After a brief introduction to this coefficient for those not versed in finance, the book presents a number of rather well known tests for constant coefficients and then performs these tests on data from the Stockholm Exchange. The Kalman filter is then introduced and a simple example is used to demonstrate the power of the filter. The filter is then used to estimate the market model with time-varying betas. The book concludes with further examples of how the Kalman filter may be used in estimation models used in analyzing other aspects of finance. Since both the programs and the data used in the book are available for downloading, the book is especially valuable for students and other researchers interested in learning the art of modeling with time varying coefficients.
Author: C. Wells
Publisher: Springer Science & Business Media
ISBN: 9780792337713
Category : Business & Economics
Languages : en
Pages : 198
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Book Description
A non-technical introduction to the question of modeling with time-varying parameters, using the beta coefficient from Financial Economics as the main example. After a brief introduction to this coefficient for those not versed in finance, the book presents a number of rather well known tests for constant coefficients and then performs these tests on data from the Stockholm Exchange. The Kalman filter is then introduced and a simple example is used to demonstrate the power of the filter. The filter is then used to estimate the market model with time-varying betas. The book concludes with further examples of how the Kalman filter may be used in estimation models used in analyzing other aspects of finance. Since both the programs and the data used in the book are available for downloading, the book is especially valuable for students and other researchers interested in learning the art of modeling with time varying coefficients.
Author: B.Philipp Kellerhals
Publisher: Springer Science & Business Media
ISBN: 3662219018
Category : Business & Economics
Languages : en
Pages : 243
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Book Description
Straight after its invention in the early sixties, the Kalman filter approach became part of the astronautical guidance system of the Apollo project and therefore received immediate acceptance in the field of electrical engineer ing. This sounds similar to the well known success story of the Black-Scholes model in finance, which has been implemented by the Chicago Board of Op tions Exchange (CBOE) within a few month after its publication in 1973. Recently, the Kalman filter approach has been discovered as a comfortable estimation tool in continuous time finance, bringing together seemingly un related methods from different fields. Dr. B. Philipp Kellerhals contributes to this topic in several respects. Specialized versions of the Kalman filter are developed and implemented for three different continuous time pricing models: A pricing model for closed-end funds, taking advantage from the fact, that the net asset value is observable, a term structure model, where the market price of risk itself is a stochastic variable, and a model for electricity forwards, where the volatility of the price process is stochastic. Beside the fact that these three models can be treated independently, the book as a whole gives the interested reader a comprehensive account of the requirements and capabilities of the Kalman filter applied to finance models. While the first model uses a linear version of the filter, the second model using LIBOR and swap market data requires an extended Kalman filter. Finally, the third model leads to a non-linear transition equation of the filter algorithm.
Author: Ramaprasad Bhar
Publisher: World Scientific
ISBN: 9814304859
Category : Business & Economics
Languages : en
Pages : 354
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Book Description
This book provides a comprehensive account of stochastic filtering as a modeling tool in finance and economics. It aims to present this very important tool with a view to making it more popular among researchers in the disciplines of finance and economics. It is not intended to give a complete mathematical treatment of different stochastic filtering approaches, but rather to describe them in simple terms and illustrate their application with real historical data for problems normally encountered in these disciplines. Beyond laying out the steps to be implemented, the steps are demonstrated in the context of different market segments. Although no prior knowledge in this area is required, the reader is expected to have knowledge of probability theory as well as a general mathematical aptitude. Its simple presentation of complex algorithms required to solve modeling problems in increasingly sophisticated financial markets makes this book particularly valuable as a reference for graduate students and researchers interested in the field. Furthermore, it analyses the model estimation results in the context of the market and contrasts these with contemporary research publications. It is also suitable for use as a text for graduate level courses on stochastic modeling.
Author: Jimson Mathew
Publisher: Springer
ISBN: 3642321127
Category : Computers
Languages : en
Pages : 457
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Book Description
This book constitutes the refereed proceedings of the International Conference Eco-friendly Computing and Communication Systems, ICECCS 2012, held in Kochi, Kerala, India, in August 2012. The 50 revised full papers presented were carefully reviewed and selected from 133 submissions. The papers are organized in topical sections on energy efficient software system and applications; wireless communication systems; green energy technologies; image and signal processing; bioinformatics and emerging technologies; secure and reliable systems; mathematical modeling and scientific computing; pervasive computing and applications.
Author: Andrew C. Harvey
Publisher: Cambridge University Press
ISBN: 9780521405737
Category : Business & Economics
Languages : en
Pages : 574
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Book Description
A synthesis of concepts and materials, that ordinarily appear separately in time series and econometrics literature, presents a comprehensive review of theoretical and applied concepts in modeling economic and social time series.
Author: Brian D. O. Anderson
Publisher: Courier Corporation
ISBN: 0486136892
Category : Science
Languages : en
Pages : 370
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Book Description
Graduate-level text extends studies of signal processing, particularly regarding communication systems and digital filtering theory. Topics include filtering, linear systems, and estimation; discrete-time Kalman filter; time-invariant filters; more. 1979 edition.
Author: Robert Grover Brown
Publisher: Wiley-Liss
ISBN:
Category : Computers
Languages : en
Pages : 504
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Book Description
In this updated edition the main thrust is on applied Kalman filtering. Chapters 1-3 provide a minimal background in random process theory and the response of linear systems to random inputs. The following chapter is devoted to Wiener filtering and the remainder of the text deals with various facets of Kalman filtering with emphasis on applications. Starred problems at the end of each chapter are computer exercises. The authors believe that programming the equations and analyzing the results of specific examples is the best way to obtain the insight that is essential in engineering work.
Author: Cheng Few Lee
Publisher: World Scientific
ISBN: 9811202400
Category : Business & Economics
Languages : en
Pages : 5053
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Book Description
This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In both theory and methodology, we need to rely upon mathematics, which includes linear algebra, geometry, differential equations, Stochastic differential equation (Ito calculus), optimization, constrained optimization, and others. These forms of mathematics have been used to derive capital market line, security market line (capital asset pricing model), option pricing model, portfolio analysis, and others.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience.
Author: Kostas Triantafyllopoulos
Publisher: Springer Nature
ISBN: 303076124X
Category : Mathematics
Languages : en
Pages : 503
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Book Description
Bayesian Inference of State Space Models: Kalman Filtering and Beyond offers a comprehensive introduction to Bayesian estimation and forecasting for state space models. The celebrated Kalman filter, with its numerous extensions, takes centre stage in the book. Univariate and multivariate models, linear Gaussian, non-linear and non-Gaussian models are discussed with applications to signal processing, environmetrics, economics and systems engineering. Over the past years there has been a growing literature on Bayesian inference of state space models, focusing on multivariate models as well as on non-linear and non-Gaussian models. The availability of time series data in many fields of science and industry on the one hand, and the development of low-cost computational capabilities on the other, have resulted in a wealth of statistical methods aimed at parameter estimation and forecasting. This book brings together many of these methods, presenting an accessible and comprehensive introduction to state space models. A number of data sets from different disciplines are used to illustrate the methods and show how they are applied in practice. The R package BTSA, created for the book, includes many of the algorithms and examples presented. The book is essentially self-contained and includes a chapter summarising the prerequisites in undergraduate linear algebra, probability and statistics. An up-to-date and complete account of state space methods, illustrated by real-life data sets and R code, this textbook will appeal to a wide range of students and scientists, notably in the disciplines of statistics, systems engineering, signal processing, data science, finance and econometrics. With numerous exercises in each chapter, and prerequisite knowledge conveniently recalled, it is suitable for upper undergraduate and graduate courses.
