Identification of the contagion effect in China's financial market uncertainties : a multiscale and dynamic perspective
Gespeichert in:
| Autor*in: |
Wang, Xinya [verfasserIn] Xu, Xin [verfasserIn] Rong, Xueyun [verfasserIn] Xuan, Siyuan [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2024 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: International review of economics & finance - Amsterdam [u.a.] : Elsevier Science, 1992, 93(2024), 1 vom: Juni, Seite 1340-1362 |
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| Übergeordnetes Werk: |
volume:93 ; year:2024 ; number:1 ; month:06 ; pages:1340-1362 |
| Links: |
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| DOI / URN: |
10.1016/j.iref.2024.03.074 |
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| Katalog-ID: |
1890325538 |
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| 982 | |2 26 |1 00 |x DE-206 |b Uncertainty is a crucial source of financial market volatility. Unlike previous research considering uncertainty from holistic and static viewpoints, we investigate the contagion effect of financial market uncertainties from a combined time-frequency and dynamic perspective. In a data-rich environment, we construct various uncertainty indices for China's financial market based on forecast errors and examine their contagion effect using a combined wavelet transform and network analysis. We also simulate dynamic contagion patterns under three different extreme scenarios, including a short-term liquidity crisis, a medium-term stock market crash and long-term central bank monetary policy shocks. The results indicate that the short-term fluctuations in China's financial market uncertainty exhibit a greater contagion intensity but with limited range. However, long-term uncertainty shocks exhibit a broader scope, but their impact intensity is significantly mitigated. Moreover, the liquidity crisis does not present a wide impact at the early stage, whereas the contagion pattern of the stock market crash shows explosive characteristics. | ||
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10.1016/j.iref.2024.03.074 doi (DE-627)1890325538 (DE-599)KXP1890325538 DE-627 ger DE-627 rda eng Wang, Xinya verfasserin (DE-588)1153425181 (DE-627)1014835186 (DE-576)500220018 aut Identification of the contagion effect in China's financial market uncertainties a multiscale and dynamic perspective Xinya Wang, Xin Xu, Xueyun Rong, Siyuan Xuan 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Contagion (dpeaa)DE-206 Financial uncertainty (dpeaa)DE-206 Multiscale (dpeaa)DE-206 Network (dpeaa)DE-206 Xu, Xin verfasserin (DE-588)1338833316 (DE-627)1898529841 aut Rong, Xueyun verfasserin (DE-588)1337183601 (DE-627)189676875X aut Xuan, Siyuan verfasserin (DE-588)1292804068 (DE-627)1849787530 aut Enthalten in International review of economics & finance Amsterdam [u.a.] : Elsevier Science, 1992 93(2024), 1 vom: Juni, Seite 1340-1362 Online-Ressource (DE-627)324452098 (DE-600)2026509-8 (DE-576)259271977 1059-0560 nnns volume:93 year:2024 number:1 month:06 pages:1340-1362 https://www.sciencedirect.com/science/article/pii/S1059056024002399/pdfft?md5=eadb0648657351b5314a506f5ed39fc6&pid=1-s2.0-S1059056024002399-main.pdf Verlag lizenzpflichtig https://doi.org/10.1016/j.iref.2024.03.074 Resolving-System lizenzpflichtig GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 93 2024 1 6 1340-1362 26 01 0206 453181679X x1z 30-05-24 26 00 DE-206 Uncertainty is a crucial source of financial market volatility. Unlike previous research considering uncertainty from holistic and static viewpoints, we investigate the contagion effect of financial market uncertainties from a combined time-frequency and dynamic perspective. In a data-rich environment, we construct various uncertainty indices for China's financial market based on forecast errors and examine their contagion effect using a combined wavelet transform and network analysis. We also simulate dynamic contagion patterns under three different extreme scenarios, including a short-term liquidity crisis, a medium-term stock market crash and long-term central bank monetary policy shocks. The results indicate that the short-term fluctuations in China's financial market uncertainty exhibit a greater contagion intensity but with limited range. However, long-term uncertainty shocks exhibit a broader scope, but their impact intensity is significantly mitigated. Moreover, the liquidity crisis does not present a wide impact at the early stage, whereas the contagion pattern of the stock market crash shows explosive characteristics. |
| spelling |
10.1016/j.iref.2024.03.074 doi (DE-627)1890325538 (DE-599)KXP1890325538 DE-627 ger DE-627 rda eng Wang, Xinya verfasserin (DE-588)1153425181 (DE-627)1014835186 (DE-576)500220018 aut Identification of the contagion effect in China's financial market uncertainties a multiscale and dynamic perspective Xinya Wang, Xin Xu, Xueyun Rong, Siyuan Xuan 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Contagion (dpeaa)DE-206 Financial uncertainty (dpeaa)DE-206 Multiscale (dpeaa)DE-206 Network (dpeaa)DE-206 Xu, Xin verfasserin (DE-588)1338833316 (DE-627)1898529841 aut Rong, Xueyun verfasserin (DE-588)1337183601 (DE-627)189676875X aut Xuan, Siyuan verfasserin (DE-588)1292804068 (DE-627)1849787530 aut Enthalten in International review of economics & finance Amsterdam [u.a.] : Elsevier Science, 1992 93(2024), 1 vom: Juni, Seite 1340-1362 Online-Ressource (DE-627)324452098 (DE-600)2026509-8 (DE-576)259271977 1059-0560 nnns volume:93 year:2024 number:1 month:06 pages:1340-1362 https://www.sciencedirect.com/science/article/pii/S1059056024002399/pdfft?md5=eadb0648657351b5314a506f5ed39fc6&pid=1-s2.0-S1059056024002399-main.pdf Verlag lizenzpflichtig https://doi.org/10.1016/j.iref.2024.03.074 Resolving-System lizenzpflichtig GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 93 2024 1 6 1340-1362 26 01 0206 453181679X x1z 30-05-24 26 00 DE-206 Uncertainty is a crucial source of financial market volatility. Unlike previous research considering uncertainty from holistic and static viewpoints, we investigate the contagion effect of financial market uncertainties from a combined time-frequency and dynamic perspective. In a data-rich environment, we construct various uncertainty indices for China's financial market based on forecast errors and examine their contagion effect using a combined wavelet transform and network analysis. We also simulate dynamic contagion patterns under three different extreme scenarios, including a short-term liquidity crisis, a medium-term stock market crash and long-term central bank monetary policy shocks. The results indicate that the short-term fluctuations in China's financial market uncertainty exhibit a greater contagion intensity but with limited range. However, long-term uncertainty shocks exhibit a broader scope, but their impact intensity is significantly mitigated. Moreover, the liquidity crisis does not present a wide impact at the early stage, whereas the contagion pattern of the stock market crash shows explosive characteristics. |
| allfields_unstemmed |
10.1016/j.iref.2024.03.074 doi (DE-627)1890325538 (DE-599)KXP1890325538 DE-627 ger DE-627 rda eng Wang, Xinya verfasserin (DE-588)1153425181 (DE-627)1014835186 (DE-576)500220018 aut Identification of the contagion effect in China's financial market uncertainties a multiscale and dynamic perspective Xinya Wang, Xin Xu, Xueyun Rong, Siyuan Xuan 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Contagion (dpeaa)DE-206 Financial uncertainty (dpeaa)DE-206 Multiscale (dpeaa)DE-206 Network (dpeaa)DE-206 Xu, Xin verfasserin (DE-588)1338833316 (DE-627)1898529841 aut Rong, Xueyun verfasserin (DE-588)1337183601 (DE-627)189676875X aut Xuan, Siyuan verfasserin (DE-588)1292804068 (DE-627)1849787530 aut Enthalten in International review of economics & finance Amsterdam [u.a.] : Elsevier Science, 1992 93(2024), 1 vom: Juni, Seite 1340-1362 Online-Ressource (DE-627)324452098 (DE-600)2026509-8 (DE-576)259271977 1059-0560 nnns volume:93 year:2024 number:1 month:06 pages:1340-1362 https://www.sciencedirect.com/science/article/pii/S1059056024002399/pdfft?md5=eadb0648657351b5314a506f5ed39fc6&pid=1-s2.0-S1059056024002399-main.pdf Verlag lizenzpflichtig https://doi.org/10.1016/j.iref.2024.03.074 Resolving-System lizenzpflichtig GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 93 2024 1 6 1340-1362 26 01 0206 453181679X x1z 30-05-24 26 00 DE-206 Uncertainty is a crucial source of financial market volatility. Unlike previous research considering uncertainty from holistic and static viewpoints, we investigate the contagion effect of financial market uncertainties from a combined time-frequency and dynamic perspective. In a data-rich environment, we construct various uncertainty indices for China's financial market based on forecast errors and examine their contagion effect using a combined wavelet transform and network analysis. We also simulate dynamic contagion patterns under three different extreme scenarios, including a short-term liquidity crisis, a medium-term stock market crash and long-term central bank monetary policy shocks. The results indicate that the short-term fluctuations in China's financial market uncertainty exhibit a greater contagion intensity but with limited range. However, long-term uncertainty shocks exhibit a broader scope, but their impact intensity is significantly mitigated. Moreover, the liquidity crisis does not present a wide impact at the early stage, whereas the contagion pattern of the stock market crash shows explosive characteristics. |
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10.1016/j.iref.2024.03.074 doi (DE-627)1890325538 (DE-599)KXP1890325538 DE-627 ger DE-627 rda eng Wang, Xinya verfasserin (DE-588)1153425181 (DE-627)1014835186 (DE-576)500220018 aut Identification of the contagion effect in China's financial market uncertainties a multiscale and dynamic perspective Xinya Wang, Xin Xu, Xueyun Rong, Siyuan Xuan 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Contagion (dpeaa)DE-206 Financial uncertainty (dpeaa)DE-206 Multiscale (dpeaa)DE-206 Network (dpeaa)DE-206 Xu, Xin verfasserin (DE-588)1338833316 (DE-627)1898529841 aut Rong, Xueyun verfasserin (DE-588)1337183601 (DE-627)189676875X aut Xuan, Siyuan verfasserin (DE-588)1292804068 (DE-627)1849787530 aut Enthalten in International review of economics & finance Amsterdam [u.a.] : Elsevier Science, 1992 93(2024), 1 vom: Juni, Seite 1340-1362 Online-Ressource (DE-627)324452098 (DE-600)2026509-8 (DE-576)259271977 1059-0560 nnns volume:93 year:2024 number:1 month:06 pages:1340-1362 https://www.sciencedirect.com/science/article/pii/S1059056024002399/pdfft?md5=eadb0648657351b5314a506f5ed39fc6&pid=1-s2.0-S1059056024002399-main.pdf Verlag lizenzpflichtig https://doi.org/10.1016/j.iref.2024.03.074 Resolving-System lizenzpflichtig GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 93 2024 1 6 1340-1362 26 01 0206 453181679X x1z 30-05-24 26 00 DE-206 Uncertainty is a crucial source of financial market volatility. Unlike previous research considering uncertainty from holistic and static viewpoints, we investigate the contagion effect of financial market uncertainties from a combined time-frequency and dynamic perspective. In a data-rich environment, we construct various uncertainty indices for China's financial market based on forecast errors and examine their contagion effect using a combined wavelet transform and network analysis. We also simulate dynamic contagion patterns under three different extreme scenarios, including a short-term liquidity crisis, a medium-term stock market crash and long-term central bank monetary policy shocks. The results indicate that the short-term fluctuations in China's financial market uncertainty exhibit a greater contagion intensity but with limited range. However, long-term uncertainty shocks exhibit a broader scope, but their impact intensity is significantly mitigated. Moreover, the liquidity crisis does not present a wide impact at the early stage, whereas the contagion pattern of the stock market crash shows explosive characteristics. |
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10.1016/j.iref.2024.03.074 doi (DE-627)1890325538 (DE-599)KXP1890325538 DE-627 ger DE-627 rda eng Wang, Xinya verfasserin (DE-588)1153425181 (DE-627)1014835186 (DE-576)500220018 aut Identification of the contagion effect in China's financial market uncertainties a multiscale and dynamic perspective Xinya Wang, Xin Xu, Xueyun Rong, Siyuan Xuan 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Contagion (dpeaa)DE-206 Financial uncertainty (dpeaa)DE-206 Multiscale (dpeaa)DE-206 Network (dpeaa)DE-206 Xu, Xin verfasserin (DE-588)1338833316 (DE-627)1898529841 aut Rong, Xueyun verfasserin (DE-588)1337183601 (DE-627)189676875X aut Xuan, Siyuan verfasserin (DE-588)1292804068 (DE-627)1849787530 aut Enthalten in International review of economics & finance Amsterdam [u.a.] : Elsevier Science, 1992 93(2024), 1 vom: Juni, Seite 1340-1362 Online-Ressource (DE-627)324452098 (DE-600)2026509-8 (DE-576)259271977 1059-0560 nnns volume:93 year:2024 number:1 month:06 pages:1340-1362 https://www.sciencedirect.com/science/article/pii/S1059056024002399/pdfft?md5=eadb0648657351b5314a506f5ed39fc6&pid=1-s2.0-S1059056024002399-main.pdf Verlag lizenzpflichtig https://doi.org/10.1016/j.iref.2024.03.074 Resolving-System lizenzpflichtig GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 93 2024 1 6 1340-1362 26 01 0206 453181679X x1z 30-05-24 26 00 DE-206 Uncertainty is a crucial source of financial market volatility. Unlike previous research considering uncertainty from holistic and static viewpoints, we investigate the contagion effect of financial market uncertainties from a combined time-frequency and dynamic perspective. In a data-rich environment, we construct various uncertainty indices for China's financial market based on forecast errors and examine their contagion effect using a combined wavelet transform and network analysis. We also simulate dynamic contagion patterns under three different extreme scenarios, including a short-term liquidity crisis, a medium-term stock market crash and long-term central bank monetary policy shocks. The results indicate that the short-term fluctuations in China's financial market uncertainty exhibit a greater contagion intensity but with limited range. However, long-term uncertainty shocks exhibit a broader scope, but their impact intensity is significantly mitigated. Moreover, the liquidity crisis does not present a wide impact at the early stage, whereas the contagion pattern of the stock market crash shows explosive characteristics. |
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Unlike previous research considering uncertainty from holistic and static viewpoints, we investigate the contagion effect of financial market uncertainties from a combined time-frequency and dynamic perspective. In a data-rich environment, we construct various uncertainty indices for China's financial market based on forecast errors and examine their contagion effect using a combined wavelet transform and network analysis. We also simulate dynamic contagion patterns under three different extreme scenarios, including a short-term liquidity crisis, a medium-term stock market crash and long-term central bank monetary policy shocks. The results indicate that the short-term fluctuations in China's financial market uncertainty exhibit a greater contagion intensity but with limited range. However, long-term uncertainty shocks exhibit a broader scope, but their impact intensity is significantly mitigated. 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26 00 DE-206 Uncertainty is a crucial source of financial market volatility. Unlike previous research considering uncertainty from holistic and static viewpoints, we investigate the contagion effect of financial market uncertainties from a combined time-frequency and dynamic perspective. In a data-rich environment, we construct various uncertainty indices for China's financial market based on forecast errors and examine their contagion effect using a combined wavelet transform and network analysis. We also simulate dynamic contagion patterns under three different extreme scenarios, including a short-term liquidity crisis, a medium-term stock market crash and long-term central bank monetary policy shocks. The results indicate that the short-term fluctuations in China's financial market uncertainty exhibit a greater contagion intensity but with limited range. However, long-term uncertainty shocks exhibit a broader scope, but their impact intensity is significantly mitigated. Moreover, the liquidity crisis does not present a wide impact at the early stage, whereas the contagion pattern of the stock market crash shows explosive characteristics Identification of the contagion effect in China's financial market uncertainties a multiscale and dynamic perspective Xinya Wang, Xin Xu, Xueyun Rong, Siyuan Xuan Contagion (dpeaa)DE-206 Financial uncertainty (dpeaa)DE-206 Multiscale (dpeaa)DE-206 Network (dpeaa)DE-206 |
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ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="b">Uncertainty is a crucial source of financial market volatility. Unlike previous research considering uncertainty from holistic and static viewpoints, we investigate the contagion effect of financial market uncertainties from a combined time-frequency and dynamic perspective. In a data-rich environment, we construct various uncertainty indices for China's financial market based on forecast errors and examine their contagion effect using a combined wavelet transform and network analysis. We also simulate dynamic contagion patterns under three different extreme scenarios, including a short-term liquidity crisis, a medium-term stock market crash and long-term central bank monetary policy shocks. The results indicate that the short-term fluctuations in China's financial market uncertainty exhibit a greater contagion intensity but with limited range. However, long-term uncertainty shocks exhibit a broader scope, but their impact intensity is significantly mitigated. Moreover, the liquidity crisis does not present a wide impact at the early stage, whereas the contagion pattern of the stock market crash shows explosive characteristics.</subfield></datafield></record></collection>
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