An empirical investigation of the GARCH option pricing model: Hedging performance

Yung, Haynes H. M.; Hua, Zhang

doi:10.1002/fut.10109

Cited by 32 publications

(13 citation statements)

References 25 publications

(77 reference statements)

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“…3;2016 value-at-Risk for an options portfolio was found to be unsatisfactory. Yung and Zhang (2003) compared the empirical performance of the ad hoc Black-Scholes model of Dumas, Fleming and Whaley with that of the EGARCH option pricing model and found that although the pricing performance of the EGARCH model was better this superior performance was small and insignificant. Also the hedging performance of the EGARCH model was found to be worse than that of the simpler ad hoc Black-Scholes model.…”

Section: Literature Reviewmentioning

confidence: 99%

Empirical Performance of Black-Scholes and GARCH Option Pricing Models during Turbulent Times: The Indian Evidence

Bhat¹,

Arekar²

2016

IJEF

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Exchange-traded currency options are a recent innovation in the Indian financial market and their pricing is as yet unexplored. The objective of this research paper is to empirically compare the pricing performance of two well-known option pricing models -the Black-Scholes-Merton Option Pricing Model (BSM) and Duan"s NGARCH option pricing model -for pricing exchange-traded currency options on the US dollar-Indian rupee during a recent turbulent period. The BSM is known to systematically misprice options on the same underlying asset but with different strike prices and maturities resulting in the phenomenon of the "volatility smile". This bias of the BSM results from its assumption of a constant volatility over the option"s life. The NGARCH option pricing model developed by Duan is an attempt to incorporate time-varying volatility in pricing options. It is a deterministic volatility model which has no closed-form solution and therefore requires numerical techniques for evaluation. In this paper we have compared the pricing performance and examined the pricing bias of both models during a recent period of volatility in the Indian foreign exchange market. Contrary to our expectations the pricing performance of the more sophisticated NGARCH pricing model is inferior to that of the relatively simple BSM model. However orthogonality tests demonstrate that the NGARCH model is free of the strike price and maturity biases associated with the BSM. We conclude that the deterministic BSM does a better job of pricing options than the more advanced time-varying volatility model based on GARCH.

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Section: Literature Reviewmentioning

confidence: 99%

Empirical Performance of Black-Scholes and GARCH Option Pricing Models during Turbulent Times: The Indian Evidence

Bhat¹,

Arekar²

2016

IJEF

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“…However, this best fitted asset model is not necessarily the optimal option pricing model minimizing the mean square error between the model option prices and the market values. To obtain the optimal option pricing model the implied GARCH model is introduced by matching the GARCH option prices with the market plain vanilla values (Fofana andBrorsen 2001, Yung andZhang 2003). This approach is analogous to the implied volatility function model in the Black-Scholes framework (Dupire 1994, Andersen andBrotherton-Ratcliffe 1998).…”

Section: Introductionmentioning

confidence: 99%

Model risk of the implied GARCH-normal model

Huang

Guo

2011

Quantitative Finance

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Model risk causes significant losses in financial derivative pricing and hedging. Investors may undertake relatively risky investments due to insufficient hedging or overpaying implied by flawed models. The GARCH model with normal innovations (GARCH-normal) has been adopted to depict the dynamics of the returns in many applications. The implied GARCHnormal model is the one minimizing the mean square error between the market option values and the GARCH-normal option prices. In this study, we investigate the model risk of the implied GARCH-normal model fitted to conditional leptokurtic returns, an important feature of financial data. The risk-neutral GARCH model with conditional leptokurtic innovations is derived by the extended Girsanov principle. The option prices and hedging positions of the conditional leptokurtic GARCH models are obtained by extending the dynamic semiparametric approach of Huang and Guo [Statist. Sin., 2009, 19, 1037-1054. In the simulation study we find significant model risk of the implied GARCH-normal model in pricing and hedging barrier and lookback options when the underlying dynamics follow a GARCH-t model.

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“…Others such as Nelson (1991) and Bollerslev and Mikkelsen (1996) contributed significantly to the GARCH models. Heston and Nandi (2000), Yung and Zhang (2003) and Barone-Adesi et al (2008) are among the few empirical studies that adopted GARCH models in the option pricing model. There is a large amount of literature on GARCH models that aims to measure volatility, but the models cannot be reviewed as a variant of the BSM model, given that it is a firmly discrete-time theory.…”

Section: Realised Volatilitymentioning

confidence: 99%

“…We noted that there are studies that consider the midpoint of bid-ask quotes in order to reduce non-synchronous problems, such as Heston and Nandi (2000), Yung and Zhang (2003), Li and Pearson (2007) and Barone-Adesi et al (2008). Midpoints are based on bid and ask quotes, which are more frequently refreshed than trade prices.…”

Section: Data Sampling Proceduresmentioning

confidence: 99%

Implied transaction costs by Leland option pricing model: A new approach and empirical evidence

Abdullah²

2012

J Deriv Hedge Funds

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An empirical investigation of the GARCH option pricing model: Hedging performance

Cited by 32 publications

References 25 publications

Empirical Performance of Black-Scholes and GARCH Option Pricing Models during Turbulent Times: The Indian Evidence

Empirical Performance of Black-Scholes and GARCH Option Pricing Models during Turbulent Times: The Indian Evidence

Model risk of the implied GARCH-normal model

Implied transaction costs by Leland option pricing model: A new approach and empirical evidence

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