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DC Field | Value | Language |
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dc.contributor.author | Petchaluck Boonyakunakorn | en_US |
dc.contributor.author | Pathairat Pastpipatkul | en_US |
dc.contributor.author | Songsak Sriboonchitta | en_US |
dc.date.accessioned | 2019-08-05T04:35:05Z | - |
dc.date.available | 2019-08-05T04:35:05Z | - |
dc.date.issued | 2019-01-01 | en_US |
dc.identifier.issn | 1860949X | en_US |
dc.identifier.other | 2-s2.0-85065608077 | en_US |
dc.identifier.other | 10.1007/978-3-030-04200-4_33 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85065608077&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/65532 | - |
dc.description.abstract | © Springer Nature Switzerland AG 2019. This paper analyzes the Value at Risk (VaR) of ASEAN-5 stock market indexes by employing Bayesian MSGARCH models. The estimated MSGARCH models with two-regime results show that the two regimes have different unconditional volatility levels and volatility persistence for all ASEAN-5 stock return. This different parameter estimate shows that the volatility process evolution is heterogeneous across the two regimes. Therefore, MSGARCH with two-regime should provide a better result than the standard GRACH model since Markov-switching model can capture characterize the time series behaviors in different regimes. For the estimated VaR results, we found that Philippines stock return presents the highest risk, whereas it provides the highest average yield among ASEAN-5 which is attractive for risk-lover investors. Malaysia is the preferred one for the risk-averse investors since it presents the lowest VaR, but provides a high return. Thailand stock return offers the median risk and median returns among ASEAN-5. Singapore stock return presents a high VaR estimate, but provides the lowest yield, being the most not attractive for investors. | en_US |
dc.subject | Computer Science | en_US |
dc.title | Value at risk of the stock market in asean-5 | en_US |
dc.type | Book Series | en_US |
article.title.sourcetitle | Studies in Computational Intelligence | en_US |
article.volume | 809 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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