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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/14394
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| Title: | RISK MANAGEMENT AND DATA QUALITY SELECTION: AN INFORMATION ECONOMICS APPROACH |
| Authors: | Bansal, Arun
Kauffman, Robert J. |
| Issue Date: | Nov-1991 |
| Publisher: | Stern School of Business, New York University |
| Series/Report no.: | IS-91-37 |
| Abstract: | Data quality has been shown to be a major determinant of the value of
systems that utilize input data feeds and transform them into valuable
information under a variety of business contexts. For this study, we
have chosen a financial risk management context to investigate the
relationship between data quality and value of risk management
forecasting systems. Three attributes of data quality, frequency,
response time, and accuracy, along with the cost of data are considered.
Joint impacts of attributes are also considered. It is shown that an
increase in report frequency results in an increase in the utility of a
risk management forecasting system, but this increase is limited by the
responsiveness of the hedging scheme. Frequency is shown to improve the
utility of the forecasting systems in two ways: First, an increase in
frequency pushes the predicted states closer to the actual states and
second, an increase in frequency causes the reliability of the
forecasting model to increase. A delay in response time of reports is
predicted to have a greater impact on utility for high frequency reports
than for low frequency reports. Finally, data inaccuracies are
recommended to be the first concern of a portfolio manager before an
attempt is made to increase the reporting frequency. |
| URI: | http://hdl.handle.net/2451/14394 |
| Appears in Collections: | IOMS: Information Systems Working Papers
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