The Kalman Filter in Finance by C. Wells.

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 co...

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Bibliographic Details
Main Author: Wells, C. (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Dordrecht : Springer Netherlands : Imprint: Springer, 1996.
Edition:1st ed. 1996.
Series:Advanced Studies in Theoretical and Applied Econometrics, 32
Springer eBook Collection.
Subjects:
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.

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505 0 |a 1 Introduction -- 2 Tests for parameter stability -- 3 Flexible Least Squares -- 4 The Kalman filter -- 5 Parameter estimation -- 6 The estimates, reconsidered -- 7 Modeling with the Kalman filter -- A Tables of References -- A.1 Stability tests by partitioning data -- A.2 Tests for heteroscedasticity -- A.3 Models in the literature -- B The programs and the data -- B.1 Subroutines -- B.2 The main programs -- B.3 The data. 
520 |a 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. 
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