Predicting Stock Market Crises by VAR Model
博士 === 國立中山大學 === 財務管理學系研究所 === 100 === There are several methods to predict financial crises. There are also several types of indicators used by financial institutions. These indicators, which are estimated in different ways, often show various developments, although it is not possible to directly...
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ndltd-TW-100NSYS53050232015-10-13T21:17:53Z http://ndltd.ncl.edu.tw/handle/00447954477831417733 Predicting Stock Market Crises by VAR Model VAR模型-股票市場危機的預測 Han-Chih Yang 楊韓緻 博士 國立中山大學 財務管理學系研究所 100 There are several methods to predict financial crises. There are also several types of indicators used by financial institutions. These indicators, which are estimated in different ways, often show various developments, although it is not possible to directly assess which is the most suitable. Here, we still try to find what characteristics that industry group has and forecast financial crises In this paper, our data started from monthly of 1977 January to 2008 December in S&P100. We consider Fama-French and Cluster Analysis to process data to make data with same characteristic within a group. Then, we use GARCH type models and apply it to VaR predicting stock turmoil. In conclusion, we found that the group which has high kurtosis value is the key factor for predicting stock crises instead of volatility. Moreover, the characteristics of this industry which can predict stock crises is a great scale. On the other hand, we can through this model to double check the reaction for anticipating. Therefore, people can do some actions to control risk to reduce the loss. Huang,Jen-Jsung Wang, Chou-Wen 黃振聰 王昭文 2012 學位論文 ; thesis 30 en_US |
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博士 === 國立中山大學 === 財務管理學系研究所 === 100 === There are several methods to predict financial crises. There are also several types of indicators used by financial institutions. These indicators, which are estimated in different ways, often show various developments, although it is not possible to directly assess which is the most suitable. Here, we still try to find what characteristics that industry group has and forecast financial crises
In this paper, our data started from monthly of 1977 January to 2008 December in S&P100. We consider Fama-French and Cluster Analysis to process data to make data with same characteristic within a group. Then, we use GARCH type models and apply it to VaR predicting stock turmoil.
In conclusion, we found that the group which has high kurtosis value is the key factor for predicting stock crises instead of volatility. Moreover, the characteristics of this industry which can predict stock crises is a great scale. On the other hand, we can through this model to double check the reaction for anticipating. Therefore, people can do some actions to control risk to reduce the loss.
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author2 |
Huang,Jen-Jsung |
author_facet |
Huang,Jen-Jsung Han-Chih Yang 楊韓緻 |
author |
Han-Chih Yang 楊韓緻 |
spellingShingle |
Han-Chih Yang 楊韓緻 Predicting Stock Market Crises by VAR Model |
author_sort |
Han-Chih Yang |
title |
Predicting Stock Market Crises by VAR Model |
title_short |
Predicting Stock Market Crises by VAR Model |
title_full |
Predicting Stock Market Crises by VAR Model |
title_fullStr |
Predicting Stock Market Crises by VAR Model |
title_full_unstemmed |
Predicting Stock Market Crises by VAR Model |
title_sort |
predicting stock market crises by var model |
publishDate |
2012 |
url |
http://ndltd.ncl.edu.tw/handle/00447954477831417733 |
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