Analyzing financial risk and co-movement of gold market, and Indonesian, Philippine, and Thailand stock markets: Dynamic copula with markov-switching

© Springer International Publishing Switzerland 2016. In this paper, we analyze the dependency between the Thailand, Indonesia, and the Philippine (TIP) stock markets and gold markets using dynamic copula with the Markov-switching model with 2 regimes, namely high dependence and low dependence regim...

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Main Authors: Pathairat Pastpipatkul, Woraphon Yamaka, Songsak Sriboonchitta
Format: Book Series
Published: 2018
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Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84952700779&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/55562
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-555622018-09-05T02:57:55Z Analyzing financial risk and co-movement of gold market, and Indonesian, Philippine, and Thailand stock markets: Dynamic copula with markov-switching Pathairat Pastpipatkul Woraphon Yamaka Songsak Sriboonchitta Computer Science © Springer International Publishing Switzerland 2016. In this paper, we analyze the dependency between the Thailand, Indonesia, and the Philippine (TIP) stock markets and gold markets using dynamic copula with the Markov-switching model with 2 regimes, namely high dependence and low dependence regimes, and extend the obtained correlation to measure the market risk. We are particularly interested in examining whether or not gold serves as a hedge in the TIP stock markets. Using daily data from January 2008 to November 2014, we find that the Gaussian copula identifies a long period of high dependence of TIPGOLD returns (market downturn) which coincides with the European debt crisis. However, if we do not take gold into account, the dependence between the TIP returns is lower in both regimes, thereby leading to a higher value at risk (VaR) and expected shortfall (ES). Therefore, gold can serve as a hedging, or a safe haven, for TIP stock markets during market downturns and upturns. Additionally, the Kupiec unconditional coverage and the Christoffersen conditional coverage test are conducted for VaR and ES backtesting. The results reveal that the Gaussian Markov-switching dynamic copula is the appropriate model to estimate a dynamic VaR and ES. 2018-09-05T02:57:55Z 2018-09-05T02:57:55Z 2016-01-01 Book Series 1860949X 2-s2.0-84952700779 10.1007/978-3-319-27284-9_37 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84952700779&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/55562
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Computer Science
spellingShingle Computer Science
Pathairat Pastpipatkul
Woraphon Yamaka
Songsak Sriboonchitta
Analyzing financial risk and co-movement of gold market, and Indonesian, Philippine, and Thailand stock markets: Dynamic copula with markov-switching
description © Springer International Publishing Switzerland 2016. In this paper, we analyze the dependency between the Thailand, Indonesia, and the Philippine (TIP) stock markets and gold markets using dynamic copula with the Markov-switching model with 2 regimes, namely high dependence and low dependence regimes, and extend the obtained correlation to measure the market risk. We are particularly interested in examining whether or not gold serves as a hedge in the TIP stock markets. Using daily data from January 2008 to November 2014, we find that the Gaussian copula identifies a long period of high dependence of TIPGOLD returns (market downturn) which coincides with the European debt crisis. However, if we do not take gold into account, the dependence between the TIP returns is lower in both regimes, thereby leading to a higher value at risk (VaR) and expected shortfall (ES). Therefore, gold can serve as a hedging, or a safe haven, for TIP stock markets during market downturns and upturns. Additionally, the Kupiec unconditional coverage and the Christoffersen conditional coverage test are conducted for VaR and ES backtesting. The results reveal that the Gaussian Markov-switching dynamic copula is the appropriate model to estimate a dynamic VaR and ES.
format Book Series
author Pathairat Pastpipatkul
Woraphon Yamaka
Songsak Sriboonchitta
author_facet Pathairat Pastpipatkul
Woraphon Yamaka
Songsak Sriboonchitta
author_sort Pathairat Pastpipatkul
title Analyzing financial risk and co-movement of gold market, and Indonesian, Philippine, and Thailand stock markets: Dynamic copula with markov-switching
title_short Analyzing financial risk and co-movement of gold market, and Indonesian, Philippine, and Thailand stock markets: Dynamic copula with markov-switching
title_full Analyzing financial risk and co-movement of gold market, and Indonesian, Philippine, and Thailand stock markets: Dynamic copula with markov-switching
title_fullStr Analyzing financial risk and co-movement of gold market, and Indonesian, Philippine, and Thailand stock markets: Dynamic copula with markov-switching
title_full_unstemmed Analyzing financial risk and co-movement of gold market, and Indonesian, Philippine, and Thailand stock markets: Dynamic copula with markov-switching
title_sort analyzing financial risk and co-movement of gold market, and indonesian, philippine, and thailand stock markets: dynamic copula with markov-switching
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84952700779&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/55562
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