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Activity Number:
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94
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Type:
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Topic Contributed
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Date/Time:
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Monday, August 12, 2002 : 10:30 AM to 12:20 PM
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Sponsor:
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Business & Economics Statistics Section*
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| Abstract - #301369 |
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Title:
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Density Forecast Evaluation with Applications in Economics and Finance
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Author(s):
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Aurobindo Ghosh*+ and Anil Bera
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Affiliation(s):
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University of Illinois, Urbana-Champaign and University of Illinois, Urbana-Champaign
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Address:
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484 Wohlers Hall, 1206 South Sixth Street,, Champaign, Illinois, 61820, USA
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Keywords:
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smooth test ; probability integral transform ; density forecast evaluation
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Abstract:
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Recently, econometricians have shifted their attention from point and interval forecasts to density forecasts, because at the heart of market risk measurement is the forecast of the probability density functions (PDF) of various market variables. One of the main problems in this area has been evaluation of the density forecasts. Unlike the graphical approaches that are used most often, we propose an analytical procedure based on the Neyman smooth test, using the probability integral transform of the original data. Our evaluation procedure is very simple, and preliminary results shows that it has very good size and power properties. We used this test to evaluate the forecast density functions of daily returns on the S. & P. 500 index. However, one of major issues in time series forecasting is dependence in the returns data. To address this issue, we proposed a simple augmentation of the smooth test using functions of the probability integral transforms and their lags.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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