Intertemporal Asset Allocation when the Underlying Factors are Unobservable

Chiarella, C; Hsiao, C; Semmler, W

Intertemporal Asset Allocation when the Underlying Factors are Unobservable

Chiarella, C Hsiao, C Semmler, W

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Publisher:: Springer
Publication Type:: Journal Article
Citation:: Computational Economics, 2007, 29 (3-4), pp. 383 - 418
Issue Date:: 2007-01

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Field	Value	Language
dc.contributor.author	Chiarella, C	en_US
dc.contributor.author	Hsiao, C	en_US
dc.contributor.author	Semmler, W	en_US
dc.date.issued	2007-01	en_US
dc.identifier.citation	Computational Economics, 2007, 29 (3-4), pp. 383 - 418	en_US
dc.identifier.issn	0927-7099	en_US
dc.identifier.uri	http://hdl.handle.net/10453/5127
dc.description.abstract	The aim of this paper is to develop an optimal long-term bond investment strategy which can be applied to real market situations. This paper employs Merton s intertemporal framework to accommodate the features of a stochastic interest rate and the time-varying dynamics of bond returns.The long-term investors encounter a partial information problem where they can only observe the market bond prices but not the driving factors of the variability of the interest rate and the bond return dynamics.With the assumption of Gaussian factor dynamics, we are able to develop an analytical solution for the optimal long-term investment strategies under the case of full information. To apply the best theoretical investment strategy to the real market we need to be aware of the existence of measurement errors representing the gap between theoretical and empirical models. We estimate the model based on data for the German securities market and then the estimation results are employed to develop long-term bond investment strategies. Because of the presence of measurement errors, we provide a simulation study to examine the performance of the best theoretical investment strategy. We find that the measurement errors have a great impact on the optimality of the investment strategies and that under certain circumstance the best theoretical investmentstrategies may not perform so well in a real market situation. In the simulation study, we also investigate the role of information about the variability of the stochastic interest rate and the bond return dynamics. Our results show that this information can indeed be used to advantage in making sensible long-term investment decisions.	en_US
dc.publisher	Springer	en_US
dc.relation.ispartof	Computational Economics	en_US
dc.relation.isbasedon	10.1007/s10614-006-9072-0	en_US
dc.subject.classification	Economics	en_US
dc.title	Intertemporal Asset Allocation when the Underlying Factors are Unobservable	en_US
dc.type	Journal Article
utslib.citation.volume	3-4	en_US
utslib.citation.volume	29	en_US
utslib.for	1403 Econometrics	en_US
utslib.for	1499 Other Economics	en_US
utslib.for	1502 Banking, Finance and Investment	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
utslib.copyright.status	closed_access
pubs.consider-herdc	true	en_US
pubs.issue	3-4	en_US
pubs.volume	29	en_US

Abstract:

The aim of this paper is to develop an optimal long-term bond investment strategy which can be applied to real market situations. This paper employs Merton s intertemporal framework to accommodate the features of a stochastic interest rate and the time-varying dynamics of bond returns.The long-term investors encounter a partial information problem where they can only observe the market bond prices but not the driving factors of the variability of the interest rate and the bond return dynamics.With the assumption of Gaussian factor dynamics, we are able to develop an analytical solution for the optimal long-term investment strategies under the case of full information. To apply the best theoretical investment strategy to the real market we need to be aware of the existence of measurement errors representing the gap between theoretical and empirical models. We estimate the model based on data for the German securities market and then the estimation results are employed to develop long-term bond investment strategies. Because of the presence of measurement errors, we provide a simulation study to examine the performance of the best theoretical investment strategy. We find that the measurement errors have a great impact on the optimality of the investment strategies and that under certain circumstance the best theoretical investmentstrategies may not perform so well in a real market situation. In the simulation study, we also investigate the role of information about the variability of the stochastic interest rate and the bond return dynamics. Our results show that this information can indeed be used to advantage in making sensible long-term investment decisions.

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http://hdl.handle.net/10453/5127