Option pricing and risk management: analytic approaches with GARCH-Lévy dynamics

This Ph.D. thesis considers making some contributions to the asset pricing and financial risk management literature. First of all it offers some dynamics in the area of asset pricing which are practically implement able for pricing European style options. More precisely it considers blending GARCH t...

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Main Author: Mozumder, Md. Sharif Ullah
Format: Thesis (University of Nottingham only)
Language:English
Published: 2011
Subjects:
Online Access:https://eprints.nottingham.ac.uk/13065/
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author Mozumder, Md. Sharif Ullah
author_facet Mozumder, Md. Sharif Ullah
author_sort Mozumder, Md. Sharif Ullah
building Nottingham Research Data Repository
collection Online Access
description This Ph.D. thesis considers making some contributions to the asset pricing and financial risk management literature. First of all it offers some dynamics in the area of asset pricing which are practically implement able for pricing European style options. More precisely it considers blending GARCH type non-Markovian dynamics with Levy type Markovian innovations to offer analytic valuation of European style derivatives (at this initial stage). Revealing the mathematical underpinnings- required to replace conditional Gaussian innovations in G ARCH option pricing models by innovations coming from some Levy processes( with one sided and both sided jumps)-is the main focus. The necessity for this arises from the fact that the non-normal (Levy) innovations are crucial as heteroskedasticity alone doesn't suffice to capture the option smirk and the analytic valuation is highly expected because it makes the model practically implementable. Thus besides incorporating non-normality particular attention is paid to analytic valuation as well; though the Monte Carlo techniques can be readily applied for the proposed dynamics. However an approximation is required to uphold the analytic pricing, especially for innovations coming from Levy processes which are not Subordinator. These dynamics are capable of overcoming many deficiencies of benchmark Black-Scholes model and can be used to price other derivatives such as Credit, Interest rate, Commodity, Weather etc. The approach is built on a discrete time continuous state space and upholds the no-arbitrage principle of derivative pricing through the use of conditional Esscher transform to configure Equivalent :tviartingale Measure(EMl'vI). Similar to the existing literature, established for GARCH with normal innovations, existence of EMM provides de-facto evidence in support of no-arbitrage argument. Besides the main focus this research has made some complementary contributions to the option pricing literature. Since J.P.Morgan introduced RiskMetrics in 1994, the normal quantile based VaR has been considered as industry standard for risk management. However VaR itself has inherent inconsistencies which are exacerbated under the assumption of normality. The second part of this thesis considers two frequently referred approaches to non-normality in risk management : extreme value(EV) approach and Levy approach. The idea is to reveal the relative performance of various risk measures under full density based Levy approach and solely tail observation based EV approach. We provide empirical evidence which confirms that though purely tail based risk measures value-at-risk (VaR) and its coherent version expected shortfall (ES) are well comparable under both approaches, entire spectrum based spectral risk measure (SRM) is misleading for EV approach. Backtesting risk measure VaR is considered under both approaches. We plan to improve the computational efficiency of estimation of Levy coherent risk measures through application of characteristic function based FRFT. Our ultimate goal is to see whether the conditional moment generating functions -developed for GARCH-Levy models in the first part of this thesis- can be adapted to the characteristic function based FRFT technique in order to estimate the risk measures in analytic fashion.
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spelling nottingham-130652025-02-28T11:22:56Z https://eprints.nottingham.ac.uk/13065/ Option pricing and risk management: analytic approaches with GARCH-Lévy dynamics Mozumder, Md. Sharif Ullah This Ph.D. thesis considers making some contributions to the asset pricing and financial risk management literature. First of all it offers some dynamics in the area of asset pricing which are practically implement able for pricing European style options. More precisely it considers blending GARCH type non-Markovian dynamics with Levy type Markovian innovations to offer analytic valuation of European style derivatives (at this initial stage). Revealing the mathematical underpinnings- required to replace conditional Gaussian innovations in G ARCH option pricing models by innovations coming from some Levy processes( with one sided and both sided jumps)-is the main focus. The necessity for this arises from the fact that the non-normal (Levy) innovations are crucial as heteroskedasticity alone doesn't suffice to capture the option smirk and the analytic valuation is highly expected because it makes the model practically implementable. Thus besides incorporating non-normality particular attention is paid to analytic valuation as well; though the Monte Carlo techniques can be readily applied for the proposed dynamics. However an approximation is required to uphold the analytic pricing, especially for innovations coming from Levy processes which are not Subordinator. These dynamics are capable of overcoming many deficiencies of benchmark Black-Scholes model and can be used to price other derivatives such as Credit, Interest rate, Commodity, Weather etc. The approach is built on a discrete time continuous state space and upholds the no-arbitrage principle of derivative pricing through the use of conditional Esscher transform to configure Equivalent :tviartingale Measure(EMl'vI). Similar to the existing literature, established for GARCH with normal innovations, existence of EMM provides de-facto evidence in support of no-arbitrage argument. Besides the main focus this research has made some complementary contributions to the option pricing literature. Since J.P.Morgan introduced RiskMetrics in 1994, the normal quantile based VaR has been considered as industry standard for risk management. However VaR itself has inherent inconsistencies which are exacerbated under the assumption of normality. The second part of this thesis considers two frequently referred approaches to non-normality in risk management : extreme value(EV) approach and Levy approach. The idea is to reveal the relative performance of various risk measures under full density based Levy approach and solely tail observation based EV approach. We provide empirical evidence which confirms that though purely tail based risk measures value-at-risk (VaR) and its coherent version expected shortfall (ES) are well comparable under both approaches, entire spectrum based spectral risk measure (SRM) is misleading for EV approach. Backtesting risk measure VaR is considered under both approaches. We plan to improve the computational efficiency of estimation of Levy coherent risk measures through application of characteristic function based FRFT. Our ultimate goal is to see whether the conditional moment generating functions -developed for GARCH-Levy models in the first part of this thesis- can be adapted to the characteristic function based FRFT technique in order to estimate the risk measures in analytic fashion. 2011 Thesis (University of Nottingham only) NonPeerReviewed application/pdf en arr https://eprints.nottingham.ac.uk/13065/1/555505.pdf Mozumder, Md. Sharif Ullah (2011) Option pricing and risk management: analytic approaches with GARCH-Lévy dynamics. PhD thesis, University of Nottingham. Options (Finance) prices mathematical models
spellingShingle Options (Finance)
prices
mathematical models
Mozumder, Md. Sharif Ullah
Option pricing and risk management: analytic approaches with GARCH-Lévy dynamics
title Option pricing and risk management: analytic approaches with GARCH-Lévy dynamics
title_full Option pricing and risk management: analytic approaches with GARCH-Lévy dynamics
title_fullStr Option pricing and risk management: analytic approaches with GARCH-Lévy dynamics
title_full_unstemmed Option pricing and risk management: analytic approaches with GARCH-Lévy dynamics
title_short Option pricing and risk management: analytic approaches with GARCH-Lévy dynamics
title_sort option pricing and risk management: analytic approaches with garch-lévy dynamics
topic Options (Finance)
prices
mathematical models
url https://eprints.nottingham.ac.uk/13065/