Asymmetric Impact of Oil Price Changes on Stock Prices: Evidence from Country and Sectoral Level Data
Abstract This paper examines the symmetric and asymmetric effects of oil price changes on stock prices using the linear and non-linear Autoregressive Distributed Lag (ARDL) approach to cointegration and error-correction modeling. For the country-level analysis, monthly data from Brazil, Canada, Chil...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Saha, Sujata [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Schlagwörter: |
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| Anmerkung: |
© Academy of Economics and Finance 2021 |
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| Übergeordnetes Werk: |
Enthalten in: Journal of economics and finance - New York, NY : Springer, 1989, 46(2022), 2 vom: 07. Jan., Seite 237-282 |
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| Übergeordnetes Werk: |
volume:46 ; year:2022 ; number:2 ; day:07 ; month:01 ; pages:237-282 |
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| DOI / URN: |
10.1007/s12197-021-09559-3 |
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SPR04678621X |
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| 520 | |a Abstract This paper examines the symmetric and asymmetric effects of oil price changes on stock prices using the linear and non-linear Autoregressive Distributed Lag (ARDL) approach to cointegration and error-correction modeling. For the country-level analysis, monthly data from Brazil, Canada, Chile, Japan, S. Korea, Malaysia, Mexico, the U.K., and the U.S. have been considered. The results show that oil price changes have asymmetric effects on stock prices mostly in the short run. To dig deeper into the asymmetric relationship between oil and stock prices, I disaggregate data at the sectoral level by focusing on eleven U.S. sectoral stock indices to investigate the performance of different sectors. This helps solve the problem of aggregation bias that is associated with country-level data. The findings show that changes in oil price have significant asymmetric effects in nine out of the eleven sectors in the short run. In most of these sectors, the short run asymmetric relationship translates into the long run. | ||
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10.1007/s12197-021-09559-3 doi (DE-627)SPR04678621X (SPR)s12197-021-09559-3-e DE-627 ger DE-627 rakwb eng Saha, Sujata verfasserin (orcid)0000-0002-2839-5601 aut Asymmetric Impact of Oil Price Changes on Stock Prices: Evidence from Country and Sectoral Level Data 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Academy of Economics and Finance 2021 Abstract This paper examines the symmetric and asymmetric effects of oil price changes on stock prices using the linear and non-linear Autoregressive Distributed Lag (ARDL) approach to cointegration and error-correction modeling. For the country-level analysis, monthly data from Brazil, Canada, Chile, Japan, S. Korea, Malaysia, Mexico, the U.K., and the U.S. have been considered. The results show that oil price changes have asymmetric effects on stock prices mostly in the short run. To dig deeper into the asymmetric relationship between oil and stock prices, I disaggregate data at the sectoral level by focusing on eleven U.S. sectoral stock indices to investigate the performance of different sectors. This helps solve the problem of aggregation bias that is associated with country-level data. The findings show that changes in oil price have significant asymmetric effects in nine out of the eleven sectors in the short run. In most of these sectors, the short run asymmetric relationship translates into the long run. Oil price (dpeaa)DE-He213 Stock prices (dpeaa)DE-He213 Nonlinear ARDL (dpeaa)DE-He213 Asymmetry (dpeaa)DE-He213 Sectoral stock prices (dpeaa)DE-He213 Enthalten in Journal of economics and finance New York, NY : Springer, 1989 46(2022), 2 vom: 07. Jan., Seite 237-282 (DE-627)341900664 (DE-600)2069807-0 1938-9744 nnns volume:46 year:2022 number:2 day:07 month:01 pages:237-282 https://dx.doi.org/10.1007/s12197-021-09559-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_26 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 46 2022 2 07 01 237-282 |
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10.1007/s12197-021-09559-3 doi (DE-627)SPR04678621X (SPR)s12197-021-09559-3-e DE-627 ger DE-627 rakwb eng Saha, Sujata verfasserin (orcid)0000-0002-2839-5601 aut Asymmetric Impact of Oil Price Changes on Stock Prices: Evidence from Country and Sectoral Level Data 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Academy of Economics and Finance 2021 Abstract This paper examines the symmetric and asymmetric effects of oil price changes on stock prices using the linear and non-linear Autoregressive Distributed Lag (ARDL) approach to cointegration and error-correction modeling. For the country-level analysis, monthly data from Brazil, Canada, Chile, Japan, S. Korea, Malaysia, Mexico, the U.K., and the U.S. have been considered. The results show that oil price changes have asymmetric effects on stock prices mostly in the short run. To dig deeper into the asymmetric relationship between oil and stock prices, I disaggregate data at the sectoral level by focusing on eleven U.S. sectoral stock indices to investigate the performance of different sectors. This helps solve the problem of aggregation bias that is associated with country-level data. The findings show that changes in oil price have significant asymmetric effects in nine out of the eleven sectors in the short run. In most of these sectors, the short run asymmetric relationship translates into the long run. Oil price (dpeaa)DE-He213 Stock prices (dpeaa)DE-He213 Nonlinear ARDL (dpeaa)DE-He213 Asymmetry (dpeaa)DE-He213 Sectoral stock prices (dpeaa)DE-He213 Enthalten in Journal of economics and finance New York, NY : Springer, 1989 46(2022), 2 vom: 07. Jan., Seite 237-282 (DE-627)341900664 (DE-600)2069807-0 1938-9744 nnns volume:46 year:2022 number:2 day:07 month:01 pages:237-282 https://dx.doi.org/10.1007/s12197-021-09559-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_26 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 46 2022 2 07 01 237-282 |
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10.1007/s12197-021-09559-3 doi (DE-627)SPR04678621X (SPR)s12197-021-09559-3-e DE-627 ger DE-627 rakwb eng Saha, Sujata verfasserin (orcid)0000-0002-2839-5601 aut Asymmetric Impact of Oil Price Changes on Stock Prices: Evidence from Country and Sectoral Level Data 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Academy of Economics and Finance 2021 Abstract This paper examines the symmetric and asymmetric effects of oil price changes on stock prices using the linear and non-linear Autoregressive Distributed Lag (ARDL) approach to cointegration and error-correction modeling. For the country-level analysis, monthly data from Brazil, Canada, Chile, Japan, S. Korea, Malaysia, Mexico, the U.K., and the U.S. have been considered. The results show that oil price changes have asymmetric effects on stock prices mostly in the short run. To dig deeper into the asymmetric relationship between oil and stock prices, I disaggregate data at the sectoral level by focusing on eleven U.S. sectoral stock indices to investigate the performance of different sectors. This helps solve the problem of aggregation bias that is associated with country-level data. The findings show that changes in oil price have significant asymmetric effects in nine out of the eleven sectors in the short run. In most of these sectors, the short run asymmetric relationship translates into the long run. Oil price (dpeaa)DE-He213 Stock prices (dpeaa)DE-He213 Nonlinear ARDL (dpeaa)DE-He213 Asymmetry (dpeaa)DE-He213 Sectoral stock prices (dpeaa)DE-He213 Enthalten in Journal of economics and finance New York, NY : Springer, 1989 46(2022), 2 vom: 07. Jan., Seite 237-282 (DE-627)341900664 (DE-600)2069807-0 1938-9744 nnns volume:46 year:2022 number:2 day:07 month:01 pages:237-282 https://dx.doi.org/10.1007/s12197-021-09559-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_26 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 46 2022 2 07 01 237-282 |
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10.1007/s12197-021-09559-3 doi (DE-627)SPR04678621X (SPR)s12197-021-09559-3-e DE-627 ger DE-627 rakwb eng Saha, Sujata verfasserin (orcid)0000-0002-2839-5601 aut Asymmetric Impact of Oil Price Changes on Stock Prices: Evidence from Country and Sectoral Level Data 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Academy of Economics and Finance 2021 Abstract This paper examines the symmetric and asymmetric effects of oil price changes on stock prices using the linear and non-linear Autoregressive Distributed Lag (ARDL) approach to cointegration and error-correction modeling. For the country-level analysis, monthly data from Brazil, Canada, Chile, Japan, S. Korea, Malaysia, Mexico, the U.K., and the U.S. have been considered. The results show that oil price changes have asymmetric effects on stock prices mostly in the short run. To dig deeper into the asymmetric relationship between oil and stock prices, I disaggregate data at the sectoral level by focusing on eleven U.S. sectoral stock indices to investigate the performance of different sectors. This helps solve the problem of aggregation bias that is associated with country-level data. The findings show that changes in oil price have significant asymmetric effects in nine out of the eleven sectors in the short run. In most of these sectors, the short run asymmetric relationship translates into the long run. Oil price (dpeaa)DE-He213 Stock prices (dpeaa)DE-He213 Nonlinear ARDL (dpeaa)DE-He213 Asymmetry (dpeaa)DE-He213 Sectoral stock prices (dpeaa)DE-He213 Enthalten in Journal of economics and finance New York, NY : Springer, 1989 46(2022), 2 vom: 07. Jan., Seite 237-282 (DE-627)341900664 (DE-600)2069807-0 1938-9744 nnns volume:46 year:2022 number:2 day:07 month:01 pages:237-282 https://dx.doi.org/10.1007/s12197-021-09559-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_26 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 46 2022 2 07 01 237-282 |
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Saha, Sujata |
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Saha, Sujata misc Oil price misc Stock prices misc Nonlinear ARDL misc Asymmetry misc Sectoral stock prices Asymmetric Impact of Oil Price Changes on Stock Prices: Evidence from Country and Sectoral Level Data |
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Asymmetric Impact of Oil Price Changes on Stock Prices: Evidence from Country and Sectoral Level Data Oil price (dpeaa)DE-He213 Stock prices (dpeaa)DE-He213 Nonlinear ARDL (dpeaa)DE-He213 Asymmetry (dpeaa)DE-He213 Sectoral stock prices (dpeaa)DE-He213 |
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asymmetric impact of oil price changes on stock prices: evidence from country and sectoral level data |
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Asymmetric Impact of Oil Price Changes on Stock Prices: Evidence from Country and Sectoral Level Data |
| abstract |
Abstract This paper examines the symmetric and asymmetric effects of oil price changes on stock prices using the linear and non-linear Autoregressive Distributed Lag (ARDL) approach to cointegration and error-correction modeling. For the country-level analysis, monthly data from Brazil, Canada, Chile, Japan, S. Korea, Malaysia, Mexico, the U.K., and the U.S. have been considered. The results show that oil price changes have asymmetric effects on stock prices mostly in the short run. To dig deeper into the asymmetric relationship between oil and stock prices, I disaggregate data at the sectoral level by focusing on eleven U.S. sectoral stock indices to investigate the performance of different sectors. This helps solve the problem of aggregation bias that is associated with country-level data. The findings show that changes in oil price have significant asymmetric effects in nine out of the eleven sectors in the short run. In most of these sectors, the short run asymmetric relationship translates into the long run. © Academy of Economics and Finance 2021 |
| abstractGer |
Abstract This paper examines the symmetric and asymmetric effects of oil price changes on stock prices using the linear and non-linear Autoregressive Distributed Lag (ARDL) approach to cointegration and error-correction modeling. For the country-level analysis, monthly data from Brazil, Canada, Chile, Japan, S. Korea, Malaysia, Mexico, the U.K., and the U.S. have been considered. The results show that oil price changes have asymmetric effects on stock prices mostly in the short run. To dig deeper into the asymmetric relationship between oil and stock prices, I disaggregate data at the sectoral level by focusing on eleven U.S. sectoral stock indices to investigate the performance of different sectors. This helps solve the problem of aggregation bias that is associated with country-level data. The findings show that changes in oil price have significant asymmetric effects in nine out of the eleven sectors in the short run. In most of these sectors, the short run asymmetric relationship translates into the long run. © Academy of Economics and Finance 2021 |
| abstract_unstemmed |
Abstract This paper examines the symmetric and asymmetric effects of oil price changes on stock prices using the linear and non-linear Autoregressive Distributed Lag (ARDL) approach to cointegration and error-correction modeling. For the country-level analysis, monthly data from Brazil, Canada, Chile, Japan, S. Korea, Malaysia, Mexico, the U.K., and the U.S. have been considered. The results show that oil price changes have asymmetric effects on stock prices mostly in the short run. To dig deeper into the asymmetric relationship between oil and stock prices, I disaggregate data at the sectoral level by focusing on eleven U.S. sectoral stock indices to investigate the performance of different sectors. This helps solve the problem of aggregation bias that is associated with country-level data. The findings show that changes in oil price have significant asymmetric effects in nine out of the eleven sectors in the short run. In most of these sectors, the short run asymmetric relationship translates into the long run. © Academy of Economics and Finance 2021 |
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Asymmetric Impact of Oil Price Changes on Stock Prices: Evidence from Country and Sectoral Level Data |
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https://dx.doi.org/10.1007/s12197-021-09559-3 |
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