Measuring Risk on Financial Interdependence
碩士 === 國立臺灣大學 === 財務金融學研究所 === 99 === Financial crisis seems to come more regularly in recent years. A prominent phenomenon is the spillover effect shown in the time of crisis. Many researchers begin to find a simple measure to characterize the risk of dependence in financial market. In this study,...
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ndltd-TW-099NTU053040842015-10-16T04:03:27Z http://ndltd.ncl.edu.tw/handle/50504246241679028494 Measuring Risk on Financial Interdependence 金融相依性之風險測量 Shih-Kang Chao 趙士綱 碩士 國立臺灣大學 財務金融學研究所 99 Financial crisis seems to come more regularly in recent years. A prominent phenomenon is the spillover effect shown in the time of crisis. Many researchers begin to find a simple measure to characterize the risk of dependence in financial market. In this study, we propose a special case of CoVaR, which is a measure of dependence risk proposed by Adrian and Brunnermeier (2010). The asymptotic conditional distribution is derived from multivariate renewal theory under normal distribution and DEJP process in discrete time setting. The CoVaR’s are computed numerically and are compared with the benchmarks from Monte Carlo simulation. We also compare the normal asymptotic CoVaR with the t distribution Monte Carlo simulated CoVaR since it is hard to get the asymptotic CoVaR under t distribution. We find that model assumption is likely to affect the CoVaR values and that the Monte Carlo simulation is computationally demanding. The asymptotic CoVaR’s are suitably accurate in some most needed situations with higher time-efficiency. Possibilities for further researches are also suggested in the conclusion. Yaw-Juei Wang 王耀輝 2011 學位論文 ; thesis 55 en_US |
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碩士 === 國立臺灣大學 === 財務金融學研究所 === 99 === Financial crisis seems to come more regularly in recent years. A prominent phenomenon is the spillover effect shown in the time of crisis. Many researchers begin to find a simple measure to characterize the risk of dependence in financial market. In this study, we propose a special case of CoVaR, which is a measure of dependence risk proposed by Adrian and Brunnermeier (2010). The asymptotic conditional distribution is derived from multivariate renewal theory under normal distribution and DEJP process in discrete time setting. The CoVaR’s are computed numerically and are compared with the benchmarks from Monte Carlo simulation.
We also compare the normal asymptotic CoVaR with the t distribution Monte Carlo simulated CoVaR since it is hard to get the asymptotic CoVaR under t distribution.
We find that model assumption is likely to affect the CoVaR values and that the Monte Carlo simulation is computationally demanding. The asymptotic CoVaR’s are suitably accurate in some most needed situations with higher time-efficiency.
Possibilities for further researches are also suggested in the conclusion.
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Yaw-Juei Wang |
author_facet |
Yaw-Juei Wang Shih-Kang Chao 趙士綱 |
author |
Shih-Kang Chao 趙士綱 |
spellingShingle |
Shih-Kang Chao 趙士綱 Measuring Risk on Financial Interdependence |
author_sort |
Shih-Kang Chao |
title |
Measuring Risk on Financial Interdependence |
title_short |
Measuring Risk on Financial Interdependence |
title_full |
Measuring Risk on Financial Interdependence |
title_fullStr |
Measuring Risk on Financial Interdependence |
title_full_unstemmed |
Measuring Risk on Financial Interdependence |
title_sort |
measuring risk on financial interdependence |
publishDate |
2011 |
url |
http://ndltd.ncl.edu.tw/handle/50504246241679028494 |
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