Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/107314
DC Field | Value | Language |
---|---|---|
dc.contributor | School of Hotel and Tourism Management | - |
dc.creator | Yang, P | - |
dc.creator | Song, H | - |
dc.creator | Wen, L | - |
dc.creator | Liu, H | - |
dc.date.accessioned | 2024-06-14T06:36:49Z | - |
dc.date.available | 2024-06-14T06:36:49Z | - |
dc.identifier.issn | 1354-8166 | - |
dc.identifier.uri | http://hdl.handle.net/10397/107314 | - |
dc.language.iso | en | en_US |
dc.publisher | Sage Publications Ltd. | en_US |
dc.rights | This is the accepted version of the publication Yang, P., Song, H., Wen, L., & Liu, H. (2023). Modeling and forecasting listed tourism firms’ risk in China using a trend asymmetric GARCH-MIDAS model. Tourism Economics, 0(0). Copyright © 2023 The Author(s). DOI: 10.1177/13548166231207671. | en_US |
dc.subject | COVID-19 | en_US |
dc.subject | Trend asymmetric GARCH-MIDAS model | en_US |
dc.subject | Uncertainty shock | en_US |
dc.subject | Volatility forecasting | en_US |
dc.title | Modeling and forecasting listed tourism firms’ risk in China using a trend asymmetric GARCH-MIDAS model | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.doi | 10.1177/13548166231207671 | - |
dcterms.abstract | This study employs the multivariate trend asymmetric GARCH-MIDAS (TAGM) model, an extension of the GARCH-MIDAS model, to explore the potential asymmetric impact of uncertainty shocks, including oil and infectious disease shocks, on the long-term volatility of China’s listed tourism firms. Furthermore, we test the out-of-sample forecasting accuracy of uncertainty shocks to China’s listed tourism firms’ risk, which is measured by the volatility of tourism stocks after the outbreak of coronavirus disease 2019 (COVID-19). The results show that uncertainty shocks have a significant asymmetric effect on the long-run volatility of tourism stocks. The included uncertainty shocks improved accuracy in forecasting China’s listed tourism firms’ risk after the pandemic outbreak. The empirical results have important implications for tourism investment strategies in unstable environments. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Tourism economics, First published online October 18, 2023, OnlineFirst, https://doi.org/10.1177/13548166231207671 | - |
dcterms.isPartOf | Tourism economics | - |
dcterms.issued | 2023 | - |
dc.identifier.scopus | 2-s2.0-85174221652 | - |
dc.identifier.eissn | 2044-0375 | - |
dc.description.validate | 202406 bcch | - |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | a2813 | en_US |
dc.identifier.SubFormID | 48451 | en_US |
dc.description.fundingSource | RGC | en_US |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | National Natural Science Foundation of China (72374083, 72004077, 72004106); Key Research Base of Humanities and Social Sciences of the Ministry of Education (22JJD790066); Humanities and Social Science Fund of the Ministry of Education (20YJC79007) | en_US |
dc.description.pubStatus | Published | en_US |
dc.description.oaCategory | Green (AAM) | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Yang_Modeling_Forecasting_Listed.pdf | Pre-Published version | 1.33 MB | Adobe PDF | View/Open |
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