Tunaru, Radu, Fabozzi, Frank J., Masood, Omar (2007) Discrete Variable Chain Graphical Modelling for Assessing the Effects of Fund Managers' Characteristics on Incentives Satisfaction and Size of Returns. European Journal of Finance, 13 (3). pp. 269-282. ISSN 1351-847X. (doi:10.1080/13518470600813581) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:25101)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
Official URL: http://dx.doi.org/10.1080/13518470600813581 |
Abstract
The relevance of a fund manager's educational and experience profile to the size of investment portfolio return has been the subject of recurrent research in the last decade. While previous research considered an external reference point of view analysing industry-wide aggregated data, little research, if any, has been directed at revealing the inside story of what influences the subjective perception of the risk framework the managers at a financial institution have to work under or whether managers consider incentives they receive to be satisfactory. This survey-based study analyses the answers of 120 fund managers from one of the world's largest banks to a set of questions designed to unveil the links between the objective and more subjective factors that contribute to the investment activity in the banking industry. This context is different from previous studies because information has been collected not only on objective characteristics such as age, size of portfolio, and size of incentives but also on whether investment decisions are based on subjective judgment or analytic tools and on the level of satisfaction with incentives and the bank's risk management system. This paper provides a methodology capable of exploring the links among the variables obtained from the interviews, graphical chain modelling, which offers an elegant solution to the problem caused by the sparsity of the data, testing with categorical ordinal variables, and model selection. The results may help senior management of financial institutions identify possible linkages that determine a stable and encouraging working environment for fund managers.
Item Type: | Article |
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DOI/Identification number: | 10.1080/13518470600813581 |
Subjects: | H Social Sciences > H Social Sciences (General) |
Divisions: | Divisions > Kent Business School - Division > Department of Accounting and Finance |
Depositing User: | Jennifer Knapp |
Date Deposited: | 19 Jul 2010 10:21 UTC |
Last Modified: | 05 Nov 2024 10:05 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/25101 (The current URI for this page, for reference purposes) |
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