Equilibrium-based volatility models of the market portfolio rate of return (peacock tails or stotting gazelles)
Abstract We introduce a theoretical and empirical method of studying equilibrium-consistent volatility models. We implement it with the market portfolio’s return, which is central to financial risk management. Within an equilibrium framework, we study two families of such models. One is deterministi...
Ausführliche Beschreibung
Autor*in: |
Feldman, David [verfasserIn] |
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Format: |
Artikel |
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Sprache: |
Englisch |
Erschienen: |
2015 |
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Schlagwörter: |
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Anmerkung: |
© Springer Science+Business Media New York 2015 |
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Übergeordnetes Werk: |
Enthalten in: Annals of operations research - Springer US, 1984, 262(2015), 2 vom: 02. Sept., Seite 493-518 |
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Übergeordnetes Werk: |
volume:262 ; year:2015 ; number:2 ; day:02 ; month:09 ; pages:493-518 |
Links: |
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DOI / URN: |
10.1007/s10479-015-1972-8 |
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Katalog-ID: |
OLC2111181447 |
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10.1007/s10479-015-1972-8 doi (DE-627)OLC2111181447 (DE-He213)s10479-015-1972-8-p DE-627 ger DE-627 rakwb eng 004 VZ 3,2 ssgn Feldman, David verfasserin (orcid)0000-0002-3300-0379 aut Equilibrium-based volatility models of the market portfolio rate of return (peacock tails or stotting gazelles) 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2015 Abstract We introduce a theoretical and empirical method of studying equilibrium-consistent volatility models. We implement it with the market portfolio’s return, which is central to financial risk management. Within an equilibrium framework, we study two families of such models. One is deterministic volatility, represented by current popular models. The other is in the “constant elasticity of variance” family, in which we propose new models. Theoretically, we show that, together with constant expected returns, the latter family tends to have better ability to forecast. Empirically, our proposed models, while as easy to implement as the popular ones, outperform them in three out-of-sample forecast evaluations of different time periods, by standard predictability criteria. This is true particularly during high-volatility periods, whether the market rises or falls. Market risk Volatility model Systematic risk Market portfolio Predictive power Equilibrium GARCH RiskMetrics Piecewise constant volatility Constant elasticity of variance Xu, Xin aut Enthalten in Annals of operations research Springer US, 1984 262(2015), 2 vom: 02. Sept., Seite 493-518 (DE-627)12964370X (DE-600)252629-3 (DE-576)018141862 0254-5330 volume:262 year:2015 number:2 day:02 month:09 pages:493-518 https://doi.org/10.1007/s10479-015-1972-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-WIW SSG-OLC-MAT AR 262 2015 2 02 09 493-518 |
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10.1007/s10479-015-1972-8 doi (DE-627)OLC2111181447 (DE-He213)s10479-015-1972-8-p DE-627 ger DE-627 rakwb eng 004 VZ 3,2 ssgn Feldman, David verfasserin (orcid)0000-0002-3300-0379 aut Equilibrium-based volatility models of the market portfolio rate of return (peacock tails or stotting gazelles) 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2015 Abstract We introduce a theoretical and empirical method of studying equilibrium-consistent volatility models. We implement it with the market portfolio’s return, which is central to financial risk management. Within an equilibrium framework, we study two families of such models. One is deterministic volatility, represented by current popular models. The other is in the “constant elasticity of variance” family, in which we propose new models. Theoretically, we show that, together with constant expected returns, the latter family tends to have better ability to forecast. Empirically, our proposed models, while as easy to implement as the popular ones, outperform them in three out-of-sample forecast evaluations of different time periods, by standard predictability criteria. This is true particularly during high-volatility periods, whether the market rises or falls. Market risk Volatility model Systematic risk Market portfolio Predictive power Equilibrium GARCH RiskMetrics Piecewise constant volatility Constant elasticity of variance Xu, Xin aut Enthalten in Annals of operations research Springer US, 1984 262(2015), 2 vom: 02. Sept., Seite 493-518 (DE-627)12964370X (DE-600)252629-3 (DE-576)018141862 0254-5330 volume:262 year:2015 number:2 day:02 month:09 pages:493-518 https://doi.org/10.1007/s10479-015-1972-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-WIW SSG-OLC-MAT AR 262 2015 2 02 09 493-518 |
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10.1007/s10479-015-1972-8 doi (DE-627)OLC2111181447 (DE-He213)s10479-015-1972-8-p DE-627 ger DE-627 rakwb eng 004 VZ 3,2 ssgn Feldman, David verfasserin (orcid)0000-0002-3300-0379 aut Equilibrium-based volatility models of the market portfolio rate of return (peacock tails or stotting gazelles) 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2015 Abstract We introduce a theoretical and empirical method of studying equilibrium-consistent volatility models. We implement it with the market portfolio’s return, which is central to financial risk management. Within an equilibrium framework, we study two families of such models. One is deterministic volatility, represented by current popular models. The other is in the “constant elasticity of variance” family, in which we propose new models. Theoretically, we show that, together with constant expected returns, the latter family tends to have better ability to forecast. Empirically, our proposed models, while as easy to implement as the popular ones, outperform them in three out-of-sample forecast evaluations of different time periods, by standard predictability criteria. This is true particularly during high-volatility periods, whether the market rises or falls. Market risk Volatility model Systematic risk Market portfolio Predictive power Equilibrium GARCH RiskMetrics Piecewise constant volatility Constant elasticity of variance Xu, Xin aut Enthalten in Annals of operations research Springer US, 1984 262(2015), 2 vom: 02. Sept., Seite 493-518 (DE-627)12964370X (DE-600)252629-3 (DE-576)018141862 0254-5330 volume:262 year:2015 number:2 day:02 month:09 pages:493-518 https://doi.org/10.1007/s10479-015-1972-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-WIW SSG-OLC-MAT AR 262 2015 2 02 09 493-518 |
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10.1007/s10479-015-1972-8 doi (DE-627)OLC2111181447 (DE-He213)s10479-015-1972-8-p DE-627 ger DE-627 rakwb eng 004 VZ 3,2 ssgn Feldman, David verfasserin (orcid)0000-0002-3300-0379 aut Equilibrium-based volatility models of the market portfolio rate of return (peacock tails or stotting gazelles) 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2015 Abstract We introduce a theoretical and empirical method of studying equilibrium-consistent volatility models. We implement it with the market portfolio’s return, which is central to financial risk management. Within an equilibrium framework, we study two families of such models. One is deterministic volatility, represented by current popular models. The other is in the “constant elasticity of variance” family, in which we propose new models. Theoretically, we show that, together with constant expected returns, the latter family tends to have better ability to forecast. Empirically, our proposed models, while as easy to implement as the popular ones, outperform them in three out-of-sample forecast evaluations of different time periods, by standard predictability criteria. This is true particularly during high-volatility periods, whether the market rises or falls. Market risk Volatility model Systematic risk Market portfolio Predictive power Equilibrium GARCH RiskMetrics Piecewise constant volatility Constant elasticity of variance Xu, Xin aut Enthalten in Annals of operations research Springer US, 1984 262(2015), 2 vom: 02. Sept., Seite 493-518 (DE-627)12964370X (DE-600)252629-3 (DE-576)018141862 0254-5330 volume:262 year:2015 number:2 day:02 month:09 pages:493-518 https://doi.org/10.1007/s10479-015-1972-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-WIW SSG-OLC-MAT AR 262 2015 2 02 09 493-518 |
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Abstract We introduce a theoretical and empirical method of studying equilibrium-consistent volatility models. We implement it with the market portfolio’s return, which is central to financial risk management. Within an equilibrium framework, we study two families of such models. One is deterministic volatility, represented by current popular models. The other is in the “constant elasticity of variance” family, in which we propose new models. Theoretically, we show that, together with constant expected returns, the latter family tends to have better ability to forecast. Empirically, our proposed models, while as easy to implement as the popular ones, outperform them in three out-of-sample forecast evaluations of different time periods, by standard predictability criteria. This is true particularly during high-volatility periods, whether the market rises or falls. © Springer Science+Business Media New York 2015 |
abstractGer |
Abstract We introduce a theoretical and empirical method of studying equilibrium-consistent volatility models. We implement it with the market portfolio’s return, which is central to financial risk management. Within an equilibrium framework, we study two families of such models. One is deterministic volatility, represented by current popular models. The other is in the “constant elasticity of variance” family, in which we propose new models. Theoretically, we show that, together with constant expected returns, the latter family tends to have better ability to forecast. Empirically, our proposed models, while as easy to implement as the popular ones, outperform them in three out-of-sample forecast evaluations of different time periods, by standard predictability criteria. This is true particularly during high-volatility periods, whether the market rises or falls. © Springer Science+Business Media New York 2015 |
abstract_unstemmed |
Abstract We introduce a theoretical and empirical method of studying equilibrium-consistent volatility models. We implement it with the market portfolio’s return, which is central to financial risk management. Within an equilibrium framework, we study two families of such models. One is deterministic volatility, represented by current popular models. The other is in the “constant elasticity of variance” family, in which we propose new models. Theoretically, we show that, together with constant expected returns, the latter family tends to have better ability to forecast. Empirically, our proposed models, while as easy to implement as the popular ones, outperform them in three out-of-sample forecast evaluations of different time periods, by standard predictability criteria. This is true particularly during high-volatility periods, whether the market rises or falls. © Springer Science+Business Media New York 2015 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">OLC2111181447</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230502202902.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">230502s2015 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10479-015-1972-8</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2111181447</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s10479-015-1972-8-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">3,2</subfield><subfield code="2">ssgn</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Feldman, David</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0002-3300-0379</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Equilibrium-based volatility models of the market portfolio rate of return (peacock tails or stotting gazelles)</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2015</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Science+Business Media New York 2015</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract We introduce a theoretical and empirical method of studying equilibrium-consistent volatility models. We implement it with the market portfolio’s return, which is central to financial risk management. Within an equilibrium framework, we study two families of such models. One is deterministic volatility, represented by current popular models. The other is in the “constant elasticity of variance” family, in which we propose new models. Theoretically, we show that, together with constant expected returns, the latter family tends to have better ability to forecast. Empirically, our proposed models, while as easy to implement as the popular ones, outperform them in three out-of-sample forecast evaluations of different time periods, by standard predictability criteria. 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