NDLI: Modelling stock return sensitivities to economic factors with the Kalman filter and neural networks

Content Provider	IEEE Xplore Digital Library
Author	Bentz, Y. Boone, L. Connor, J.
Copyright Year	1996
Description	Author affiliation: Soc. Gen., Paris, France (Bentz, Y.)
Abstract	Sensitivity analysis of asset returns to various economic variables provides investors with a useful tool to build portfolios and manage their risk. However, there are strong reasons to believe that stock exposures evolve through time and that factor models involving them are only pertinent if they use reliable estimates of future sensitivities. Both Kalman filtering and neural networks may be used to provide such estimates. While the Kalman filter is good at modelling the time structure of sensitivities, neural networks are capable of relating them to exogeneous variables in a non linear way. Furthermore, because the two approaches perform complementary tasks of sensitivity forecasting, they may be combined to achieve better performances. These procedures are evaluated in a controlled simulation experiment and in a real stock exposure analysis. Stock sensitivities to interest and exchange rates are forecasted for 90 French shares and portfolios are built accordingly.
Starting Page	79
Ending Page	82
File Size	310308
Page Count	4
File Format	PDF
ISBN	0780332369
DOI	10.1109/CIFER.1996.501827
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1996-03-24
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Economic forecasting Portfolios Neural networks Sensitivity analysis Asset management Risk management Kalman filters Filtering Analytical models Exchange rates
Content Type	Text
Resource Type	Article

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Mr. Siddhartha Mukherjee siddhartha@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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