Pricing European Options by Numerical Replication: Quadratic Programming with Constraints
Abstract The paper considers a regression approach to pricing European options in an incomplete market. The algorithm replicates an option by a portfolio consisting of the underlying security and a risk-free bond. We apply linear regression framework and quadratic programming with linear constraints...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ryabchenko, Valeriy [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2004 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media, Inc. 2006 |
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| Übergeordnetes Werk: |
Enthalten in: Asia-Pacific financial markets - Springer US, 1998, 11(2004), 3 vom: Sept., Seite 301-333 |
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| Übergeordnetes Werk: |
volume:11 ; year:2004 ; number:3 ; month:09 ; pages:301-333 |
| Links: |
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| DOI / URN: |
10.1007/s10690-005-9004-3 |
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OLC2040205454 |
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| 520 | |a Abstract The paper considers a regression approach to pricing European options in an incomplete market. The algorithm replicates an option by a portfolio consisting of the underlying security and a risk-free bond. We apply linear regression framework and quadratic programming with linear constraints (input = sample paths of underlying security; output = table of option prices as a function of time and price of the underlying security). We populate the model with historical prices of the underlying security (possibly massaged to the present volatility) or with Monte Carlo simulated prices. Risk neutral processes or probabilities are not needed in this framework. | ||
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10.1007/s10690-005-9004-3 doi (DE-627)OLC2040205454 (DE-He213)s10690-005-9004-3-p DE-627 ger DE-627 rakwb eng 330 VZ Ryabchenko, Valeriy verfasserin aut Pricing European Options by Numerical Replication: Quadratic Programming with Constraints 2004 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, Inc. 2006 Abstract The paper considers a regression approach to pricing European options in an incomplete market. The algorithm replicates an option by a portfolio consisting of the underlying security and a risk-free bond. We apply linear regression framework and quadratic programming with linear constraints (input = sample paths of underlying security; output = table of option prices as a function of time and price of the underlying security). We populate the model with historical prices of the underlying security (possibly massaged to the present volatility) or with Monte Carlo simulated prices. Risk neutral processes or probabilities are not needed in this framework. Stock Price Option Price Call Option Implied Volatility Strike Price Sarykalin, Sergey aut Uryasev, Stan aut Enthalten in Asia-Pacific financial markets Springer US, 1998 11(2004), 3 vom: Sept., Seite 301-333 (DE-627)245393838 (DE-600)1431844-1 (DE-576)385402090 1387-2834 nnns volume:11 year:2004 number:3 month:09 pages:301-333 https://doi.org/10.1007/s10690-005-9004-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-OAS SSG-OLC-MFO SSG-OLC-WIW GBV_ILN_26 AR 11 2004 3 09 301-333 |
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10.1007/s10690-005-9004-3 doi (DE-627)OLC2040205454 (DE-He213)s10690-005-9004-3-p DE-627 ger DE-627 rakwb eng 330 VZ Ryabchenko, Valeriy verfasserin aut Pricing European Options by Numerical Replication: Quadratic Programming with Constraints 2004 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, Inc. 2006 Abstract The paper considers a regression approach to pricing European options in an incomplete market. The algorithm replicates an option by a portfolio consisting of the underlying security and a risk-free bond. We apply linear regression framework and quadratic programming with linear constraints (input = sample paths of underlying security; output = table of option prices as a function of time and price of the underlying security). We populate the model with historical prices of the underlying security (possibly massaged to the present volatility) or with Monte Carlo simulated prices. Risk neutral processes or probabilities are not needed in this framework. Stock Price Option Price Call Option Implied Volatility Strike Price Sarykalin, Sergey aut Uryasev, Stan aut Enthalten in Asia-Pacific financial markets Springer US, 1998 11(2004), 3 vom: Sept., Seite 301-333 (DE-627)245393838 (DE-600)1431844-1 (DE-576)385402090 1387-2834 nnns volume:11 year:2004 number:3 month:09 pages:301-333 https://doi.org/10.1007/s10690-005-9004-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-OAS SSG-OLC-MFO SSG-OLC-WIW GBV_ILN_26 AR 11 2004 3 09 301-333 |
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10.1007/s10690-005-9004-3 doi (DE-627)OLC2040205454 (DE-He213)s10690-005-9004-3-p DE-627 ger DE-627 rakwb eng 330 VZ Ryabchenko, Valeriy verfasserin aut Pricing European Options by Numerical Replication: Quadratic Programming with Constraints 2004 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, Inc. 2006 Abstract The paper considers a regression approach to pricing European options in an incomplete market. The algorithm replicates an option by a portfolio consisting of the underlying security and a risk-free bond. We apply linear regression framework and quadratic programming with linear constraints (input = sample paths of underlying security; output = table of option prices as a function of time and price of the underlying security). We populate the model with historical prices of the underlying security (possibly massaged to the present volatility) or with Monte Carlo simulated prices. Risk neutral processes or probabilities are not needed in this framework. Stock Price Option Price Call Option Implied Volatility Strike Price Sarykalin, Sergey aut Uryasev, Stan aut Enthalten in Asia-Pacific financial markets Springer US, 1998 11(2004), 3 vom: Sept., Seite 301-333 (DE-627)245393838 (DE-600)1431844-1 (DE-576)385402090 1387-2834 nnns volume:11 year:2004 number:3 month:09 pages:301-333 https://doi.org/10.1007/s10690-005-9004-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-OAS SSG-OLC-MFO SSG-OLC-WIW GBV_ILN_26 AR 11 2004 3 09 301-333 |
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Abstract The paper considers a regression approach to pricing European options in an incomplete market. The algorithm replicates an option by a portfolio consisting of the underlying security and a risk-free bond. We apply linear regression framework and quadratic programming with linear constraints (input = sample paths of underlying security; output = table of option prices as a function of time and price of the underlying security). We populate the model with historical prices of the underlying security (possibly massaged to the present volatility) or with Monte Carlo simulated prices. Risk neutral processes or probabilities are not needed in this framework. © Springer Science+Business Media, Inc. 2006 |
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Abstract The paper considers a regression approach to pricing European options in an incomplete market. The algorithm replicates an option by a portfolio consisting of the underlying security and a risk-free bond. We apply linear regression framework and quadratic programming with linear constraints (input = sample paths of underlying security; output = table of option prices as a function of time and price of the underlying security). We populate the model with historical prices of the underlying security (possibly massaged to the present volatility) or with Monte Carlo simulated prices. Risk neutral processes or probabilities are not needed in this framework. © Springer Science+Business Media, Inc. 2006 |
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Abstract The paper considers a regression approach to pricing European options in an incomplete market. The algorithm replicates an option by a portfolio consisting of the underlying security and a risk-free bond. We apply linear regression framework and quadratic programming with linear constraints (input = sample paths of underlying security; output = table of option prices as a function of time and price of the underlying security). We populate the model with historical prices of the underlying security (possibly massaged to the present volatility) or with Monte Carlo simulated prices. Risk neutral processes or probabilities are not needed in this framework. © Springer Science+Business Media, Inc. 2006 |
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