Event Forecasts Evaluation

碩士 === 國立暨南國際大學 === 經濟學系 === 95 === The conventional market timing tests are often used to evaluate the accuracy of the event forecasts. Under the IID assumption of event forecasts, these tests perform well. However, all of these tests have servere size distortions when the event forecasts are seria...

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Main Authors: Pao-Yu Lu, 呂寶玉
Other Authors: Ching-Chuan Tsong
Format: Others
Language:zh-TW
Published: 2007
Online Access:http://ndltd.ncl.edu.tw/handle/4bft37
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spelling ndltd-TW-095NCNU03890052018-04-10T17:12:34Z http://ndltd.ncl.edu.tw/handle/4bft37 Event Forecasts Evaluation 事件預測評估 Pao-Yu Lu 呂寶玉 碩士 國立暨南國際大學 經濟學系 95 The conventional market timing tests are often used to evaluate the accuracy of the event forecasts. Under the IID assumption of event forecasts, these tests perform well. However, all of these tests have servere size distortions when the event forecasts are serially correlated. In this thesis, the method of heteroskedasticity-autocorrelation consistent (HAC) is employed to cope with this problem. After accounting for the serial correlation, the HAC robust tests including fixed-b approximation and naive block bootstrap can effectively reduce the over size problem. In the empirical study, we find that conventional tests over reject the null when the event forecasts and event realization of all countries have high serial correlation, which means the event forecasts have the timing ability. According to the evidence of sample correlation coefficient, however, it seems that the event forecasts have no timing ability by using these the HAC robust tests. Therefore, the HAC robust tests are strongly suggested to evaluate the event forecasts even when the event forecasts have serial correlation. Ching-Chuan Tsong 欉清全 2007 學位論文 ; thesis 60 zh-TW
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language zh-TW
format Others
sources NDLTD
description 碩士 === 國立暨南國際大學 === 經濟學系 === 95 === The conventional market timing tests are often used to evaluate the accuracy of the event forecasts. Under the IID assumption of event forecasts, these tests perform well. However, all of these tests have servere size distortions when the event forecasts are serially correlated. In this thesis, the method of heteroskedasticity-autocorrelation consistent (HAC) is employed to cope with this problem. After accounting for the serial correlation, the HAC robust tests including fixed-b approximation and naive block bootstrap can effectively reduce the over size problem. In the empirical study, we find that conventional tests over reject the null when the event forecasts and event realization of all countries have high serial correlation, which means the event forecasts have the timing ability. According to the evidence of sample correlation coefficient, however, it seems that the event forecasts have no timing ability by using these the HAC robust tests. Therefore, the HAC robust tests are strongly suggested to evaluate the event forecasts even when the event forecasts have serial correlation.
author2 Ching-Chuan Tsong
author_facet Ching-Chuan Tsong
Pao-Yu Lu
呂寶玉
author Pao-Yu Lu
呂寶玉
spellingShingle Pao-Yu Lu
呂寶玉
Event Forecasts Evaluation
author_sort Pao-Yu Lu
title Event Forecasts Evaluation
title_short Event Forecasts Evaluation
title_full Event Forecasts Evaluation
title_fullStr Event Forecasts Evaluation
title_full_unstemmed Event Forecasts Evaluation
title_sort event forecasts evaluation
publishDate 2007
url http://ndltd.ncl.edu.tw/handle/4bft37
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