Smooth and abrupt dynamics in financial volatility : the MS-MEM-MIDAS
Gespeichert in:
| Autor*in: |
Scaffidi Domianello, Luca [verfasserIn] Gallo, Giampiero M. [verfasserIn] Otranto, Edoardo [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: Oxford bulletin of economics and statistics - Oxford : Wiley-Blackwell, 1973, 86(2024), 1 vom: Feb., Seite 21-43 |
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| Übergeordnetes Werk: |
volume:86 ; year:2024 ; number:1 ; month:02 ; pages:21-43 |
| Links: |
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| DOI / URN: |
10.1111/obes.12576 |
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| Katalog-ID: |
1882421590 |
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| 982 | |2 26 |1 00 |x DE-206 |b In this paper, we maintain that the evolution of the realized volatility is characterized by a combination of high-frequency dynamics and smoother, yet persistent, dynamics evolving at a lower frequency. We suggest a new Multiplicative Error Model which combines the mixed frequency features of a MIDAS at the monthly level with Markovian dynamics at the daily level. When estimated in-sample on the realized kernel volatility of the S&P500 index, this model dominates other simpler specifications, especially when monthly aggregated realized volatility is used. The same pattern is confirmed in the out-of-sample forecasting performance which suggests that adding an abrupt change in the average level of volatility better helps in tracking quick bursts of volatility and a relatively rapid absorption of the shocks. | ||
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10.1111/obes.12576 doi (DE-627)1882421590 (DE-599)KXP1882421590 DE-627 ger DE-627 rda eng Scaffidi Domianello, Luca verfasserin aut Smooth and abrupt dynamics in financial volatility the MS-MEM-MIDAS Luca Scaffidi Domianello, Giampiero M. Gallo and Edoardo Otranto 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 1.1\x Volatilität (DE-627)091398819 (DE-2867)18679-3 stw 1.2\x ARCH-Modell (DE-627)091347998 (DE-2867)19574-5 stw 1.3\x Aktienmarkt (DE-627)091346312 (DE-2867)13713-5 stw 1.4\x Theorie (DE-627)091394902 (DE-2867)19073-6 stw Gallo, Giampiero M. verfasserin (DE-588)170242269 (DE-627)060301406 (DE-576)131143441 aut Otranto, Edoardo verfasserin aut Enthalten in Oxford bulletin of economics and statistics Oxford : Wiley-Blackwell, 1973 86(2024), 1 vom: Feb., Seite 21-43 Online-Ressource (DE-627)26901876X (DE-600)1473788-7 (DE-576)077662547 1468-0084 nnns volume:86 year:2024 number:1 month:02 pages:21-43 https://onlinelibrary.wiley.com/doi/pdf/10.1111/obes.12576 Verlag lizenzpflichtig https://doi.org/10.1111/obes.12576 Resolving-System lizenzpflichtig GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 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_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_184 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_266 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_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_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 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_2190 GBV_ILN_2232 GBV_ILN_2336 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 86 2024 1 2 21-43 26 01 0206 4495418432 x1z 04-03-24 26 00 DE-206 In this paper, we maintain that the evolution of the realized volatility is characterized by a combination of high-frequency dynamics and smoother, yet persistent, dynamics evolving at a lower frequency. We suggest a new Multiplicative Error Model which combines the mixed frequency features of a MIDAS at the monthly level with Markovian dynamics at the daily level. When estimated in-sample on the realized kernel volatility of the S&P500 index, this model dominates other simpler specifications, especially when monthly aggregated realized volatility is used. The same pattern is confirmed in the out-of-sample forecasting performance which suggests that adding an abrupt change in the average level of volatility better helps in tracking quick bursts of volatility and a relatively rapid absorption of the shocks. |
| spelling |
10.1111/obes.12576 doi (DE-627)1882421590 (DE-599)KXP1882421590 DE-627 ger DE-627 rda eng Scaffidi Domianello, Luca verfasserin aut Smooth and abrupt dynamics in financial volatility the MS-MEM-MIDAS Luca Scaffidi Domianello, Giampiero M. Gallo and Edoardo Otranto 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 1.1\x Volatilität (DE-627)091398819 (DE-2867)18679-3 stw 1.2\x ARCH-Modell (DE-627)091347998 (DE-2867)19574-5 stw 1.3\x Aktienmarkt (DE-627)091346312 (DE-2867)13713-5 stw 1.4\x Theorie (DE-627)091394902 (DE-2867)19073-6 stw Gallo, Giampiero M. verfasserin (DE-588)170242269 (DE-627)060301406 (DE-576)131143441 aut Otranto, Edoardo verfasserin aut Enthalten in Oxford bulletin of economics and statistics Oxford : Wiley-Blackwell, 1973 86(2024), 1 vom: Feb., Seite 21-43 Online-Ressource (DE-627)26901876X (DE-600)1473788-7 (DE-576)077662547 1468-0084 nnns volume:86 year:2024 number:1 month:02 pages:21-43 https://onlinelibrary.wiley.com/doi/pdf/10.1111/obes.12576 Verlag lizenzpflichtig https://doi.org/10.1111/obes.12576 Resolving-System lizenzpflichtig GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 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_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_184 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_266 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_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_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 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_2190 GBV_ILN_2232 GBV_ILN_2336 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 86 2024 1 2 21-43 26 01 0206 4495418432 x1z 04-03-24 26 00 DE-206 In this paper, we maintain that the evolution of the realized volatility is characterized by a combination of high-frequency dynamics and smoother, yet persistent, dynamics evolving at a lower frequency. We suggest a new Multiplicative Error Model which combines the mixed frequency features of a MIDAS at the monthly level with Markovian dynamics at the daily level. When estimated in-sample on the realized kernel volatility of the S&P500 index, this model dominates other simpler specifications, especially when monthly aggregated realized volatility is used. The same pattern is confirmed in the out-of-sample forecasting performance which suggests that adding an abrupt change in the average level of volatility better helps in tracking quick bursts of volatility and a relatively rapid absorption of the shocks. |
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10.1111/obes.12576 doi (DE-627)1882421590 (DE-599)KXP1882421590 DE-627 ger DE-627 rda eng Scaffidi Domianello, Luca verfasserin aut Smooth and abrupt dynamics in financial volatility the MS-MEM-MIDAS Luca Scaffidi Domianello, Giampiero M. Gallo and Edoardo Otranto 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 1.1\x Volatilität (DE-627)091398819 (DE-2867)18679-3 stw 1.2\x ARCH-Modell (DE-627)091347998 (DE-2867)19574-5 stw 1.3\x Aktienmarkt (DE-627)091346312 (DE-2867)13713-5 stw 1.4\x Theorie (DE-627)091394902 (DE-2867)19073-6 stw Gallo, Giampiero M. verfasserin (DE-588)170242269 (DE-627)060301406 (DE-576)131143441 aut Otranto, Edoardo verfasserin aut Enthalten in Oxford bulletin of economics and statistics Oxford : Wiley-Blackwell, 1973 86(2024), 1 vom: Feb., Seite 21-43 Online-Ressource (DE-627)26901876X (DE-600)1473788-7 (DE-576)077662547 1468-0084 nnns volume:86 year:2024 number:1 month:02 pages:21-43 https://onlinelibrary.wiley.com/doi/pdf/10.1111/obes.12576 Verlag lizenzpflichtig https://doi.org/10.1111/obes.12576 Resolving-System lizenzpflichtig GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 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_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_184 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_266 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_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_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 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_2190 GBV_ILN_2232 GBV_ILN_2336 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 86 2024 1 2 21-43 26 01 0206 4495418432 x1z 04-03-24 26 00 DE-206 In this paper, we maintain that the evolution of the realized volatility is characterized by a combination of high-frequency dynamics and smoother, yet persistent, dynamics evolving at a lower frequency. We suggest a new Multiplicative Error Model which combines the mixed frequency features of a MIDAS at the monthly level with Markovian dynamics at the daily level. When estimated in-sample on the realized kernel volatility of the S&P500 index, this model dominates other simpler specifications, especially when monthly aggregated realized volatility is used. The same pattern is confirmed in the out-of-sample forecasting performance which suggests that adding an abrupt change in the average level of volatility better helps in tracking quick bursts of volatility and a relatively rapid absorption of the shocks. |
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26 00 DE-206 In this paper, we maintain that the evolution of the realized volatility is characterized by a combination of high-frequency dynamics and smoother, yet persistent, dynamics evolving at a lower frequency. We suggest a new Multiplicative Error Model which combines the mixed frequency features of a MIDAS at the monthly level with Markovian dynamics at the daily level. When estimated in-sample on the realized kernel volatility of the S&P500 index, this model dominates other simpler specifications, especially when monthly aggregated realized volatility is used. The same pattern is confirmed in the out-of-sample forecasting performance which suggests that adding an abrupt change in the average level of volatility better helps in tracking quick bursts of volatility and a relatively rapid absorption of the shocks Smooth and abrupt dynamics in financial volatility the MS-MEM-MIDAS Luca Scaffidi Domianello, Giampiero M. Gallo and Edoardo Otranto 1.1\x Volatilität (DE-627)091398819 (DE-2867)18679-3 stw 1.2\x ARCH-Modell (DE-627)091347998 (DE-2867)19574-5 stw 1.3\x Aktienmarkt (DE-627)091346312 (DE-2867)13713-5 stw 1.4\x Theorie (DE-627)091394902 (DE-2867)19073-6 stw |
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Smooth and abrupt dynamics in financial volatility |
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https://onlinelibrary.wiley.com/doi/pdf/10.1111/obes.12576 https://doi.org/10.1111/obes.12576 |
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Gallo, Giampiero M. Otranto, Edoardo |
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Gallo, Giampiero Maria Gallo, G. M. Gallo, Giampiero M. |
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ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4326</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4333</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4334</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4336</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4393</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">86</subfield><subfield code="j">2024</subfield><subfield code="e">1</subfield><subfield code="c">2</subfield><subfield code="h">21-43</subfield></datafield><datafield tag="980" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">01</subfield><subfield code="x">0206</subfield><subfield code="b">4495418432</subfield><subfield code="y">x1z</subfield><subfield code="z">04-03-24</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="b">In this paper, we maintain that the evolution of the realized volatility is characterized by a combination of high-frequency dynamics and smoother, yet persistent, dynamics evolving at a lower frequency. We suggest a new Multiplicative Error Model which combines the mixed frequency features of a MIDAS at the monthly level with Markovian dynamics at the daily level. When estimated in-sample on the realized kernel volatility of the S&P500 index, this model dominates other simpler specifications, especially when monthly aggregated realized volatility is used. The same pattern is confirmed in the out-of-sample forecasting performance which suggests that adding an abrupt change in the average level of volatility better helps in tracking quick bursts of volatility and a relatively rapid absorption of the shocks.</subfield></datafield></record></collection>
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7.400772 |