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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Main Authors: Shih-Kang Chao, 趙士綱
Other Authors: Yaw-Juei Wang
Format: Others
Language:en_US
Published: 2011
Online Access:http://ndltd.ncl.edu.tw/handle/50504246241679028494
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spelling 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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description 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.
author2 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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