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Abstract Details
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Activity Number:
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247
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Type:
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Contributed
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Date/Time:
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Monday, July 30, 2012 : 2:00 PM to 3:50 PM
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Sponsor:
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Business and Economic Statistics Section
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| Abstract - #305247 |
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Title:
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Aggregating and Evaluating Analyst Forecasts Using Percentage and Relative Error
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Author(s):
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Victor Jose*+
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Companies:
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Georgetown University
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Address:
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544 Hariri Building, Washington, DC, 20057, United States
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Keywords:
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Analyst Forecasts ;
Overconfidence ;
Relative Error ;
Percentage Error
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Abstract:
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Percentage and relative error are two of the most commonly used forecast accuracy measures in practice due to its ease of interpretation and unit-free property. In this paper, we analyze the use of these measures in the context of estimating weights for aggregating forecasts and we see that these weighted forecasts tend to provide some improvements in certain situations especially when an overconfidence bias exists. We illustrate this approach by using analyst data from the IBES database for SP500 companies as an example.
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Authors who are presenting talks have a * after their name.
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