Hidden Markov Models Applications to Financial Economics /

Markov chains have increasingly become useful way of capturing stochastic nature of many economic and financial variables. Although the hidden Markov processes have been widely employed for some time in many engineering applications e.g. speech recognition, its effectiveness has now been recognized...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Bhar, Ramaprasad (Συγγραφέας), Hamori, Shigeyuki (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Boston, MA : Springer US, 2004.
Σειρά:Advanced Studies in Theoretical and Applied Econometrics, 40
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Bhar, Ramaprasad.  |e author. 
245 1 0 |a Hidden Markov Models  |h [electronic resource] :  |b Applications to Financial Economics /  |c by Ramaprasad Bhar, Shigeyuki Hamori. 
264 1 |a Boston, MA :  |b Springer US,  |c 2004. 
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490 1 |a Advanced Studies in Theoretical and Applied Econometrics,  |x 1570-5811 ;  |v 40 
505 0 |a Volatility in Growth Rate of Real GDP -- Linkages Among G7 Stock Markets -- Interplay between Industrial Production and Stock Market -- Linking Inflation and Inflation Uncertainty -- Exploring Permanent and Transitory Components of Stock Return -- Exploring the Relationship between Coincident Financial Market Indicators. 
520 |a Markov chains have increasingly become useful way of capturing stochastic nature of many economic and financial variables. Although the hidden Markov processes have been widely employed for some time in many engineering applications e.g. speech recognition, its effectiveness has now been recognized in areas of social science research as well. The main aim of Hidden Markov Models: Applications to Financial Economics is to make such techniques available to more researchers in financial economics. As such we only cover the necessary theoretical aspects in each chapter while focusing on real life applications using contemporary data mainly from OECD group of countries. The underlying assumption here is that the researchers in financial economics would be familiar with such application although empirical techniques would be more traditional econometrics. Keeping the application level in a more familiar level, we focus on the methodology based on hidden Markov processes. This will, we believe, help the reader to develop more in-depth understanding of the modeling issues thereby benefiting their future research. 
650 0 |a Finance. 
650 0 |a Econometrics. 
650 0 |a Microeconomics. 
650 0 |a Macroeconomics. 
650 0 |a International economics. 
650 0 |a Public finance. 
650 1 4 |a Economics. 
650 2 4 |a Public Economics. 
650 2 4 |a Econometrics. 
650 2 4 |a International Economics. 
650 2 4 |a Finance, general. 
650 2 4 |a Macroeconomics/Monetary Economics//Financial Economics. 
650 2 4 |a Microeconomics. 
700 1 |a Hamori, Shigeyuki.  |e author. 
710 2 |a SpringerLink (Online service) 
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776 0 8 |i Printed edition:  |z 9781402078996 
830 0 |a Advanced Studies in Theoretical and Applied Econometrics,  |x 1570-5811 ;  |v 40 
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