RCA models with GARCH innovations

Thavaneswaran, A.; Appadoo, S. S.; Ghahramani, M.

doi:10.1016/j.aml.2008.02.015

Cited by 16 publications

(13 citation statements)

References 8 publications

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“…Theoretical properties of this model can be found among others: Górka (2012), Thavaneswaran et al, (2006aThavaneswaran et al, ( , 2006bThavaneswaran et al, ( , 2008Thavaneswaran et al, ( , 2009. It is worth noting, that the adding the sign function has influence the increase of unconditional variance and kurtosis in comparison with RCA(1)-GARCH(1,1), and therefore also with ordinary AR(1)-GARCH(1,1).…”

Section: Option Pricing Under Sign Rca-garch Modelsmentioning

confidence: 99%

Option Pricing under Sign RCA-GARCH Models

Górka

2015

DEM

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A b s t r a c t. After Black and Scholes's groundbreaking work, the literature concerning pricing options has become a very important area of research. Numerous option valuation methods have been developed. This paper shows how one can compute option prices using Sign RCA-GARCH models for the dynamics of the volatility. Option pricing obtained from Sign RCA-GARCH models, the Black and Scholes's valuation and other selected GARCH option pricing models are compared with the market prices. This approach was illustrated by the valuation of the European call options on the WIG20 index. The empirical results indicated that RCA-GARCH and Sign RCA-GARCH models can be successfully used for pricing options. However none of the models can be indicated as the best one for the option valuations for every period and every time to maturity of the options. K e y w o r d s: Sign RCA-GARCH models, option pricing, GARCH models. J E L Classification: G13.

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Section: Option Pricing Under Sign Rca-garch Modelsmentioning

confidence: 99%

Option Pricing under Sign RCA-GARCH Models

Górka

2015

DEM

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“…Thavaneswaran et al [2] use an ARMA representation to derive the kurtosis of various classes of GARCH models such as power GARCH, nonGaussian GARCH, non-stationary and random coefficient GARCH. Recently, Thavaneswaran et al [3], Appadoo et al [4] have extended the results to stationary RCA processes with GARCH errors and Paseka et al [5] further extended the results to RCA processes with stochastic volatility (SV) errors.…”

Section: Introductionmentioning

confidence: 99%

“…Financial, currency, and commodity data also respond to new information entering into the market, which usually have large kurtosis. Recently, there has been growing interest in using volatility models [3,4]. Most of the studies use GARCH models with dummy variables in the volatility equation, and a few of them have been extended to a more flexible form such as the RCA GARCH.…”

Section: Introductionmentioning

confidence: 99%

Option Pricing Applications of Quadratic Volatility Models

Appadoo¹,

Thavaneswaran²,

Muthukumarana³

2012

JMF

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Recently there has been a surge of interest in higher order moment properties of time varying volatility models. Various GARCH-type models have been developed and successfully applied in empirical finance. Moment properties are important because the existence of moments permit verification of how well theoretical models match stylized facts such as fat tails in most financial data. In this paper, we consider various types of random coefficient autoregressive (RCA) models with quadratic generalized autoregressive conditional heteroscedasticity (GARCH) errors and study the moments, mean, variance and kurtosis. We also consider the Black-Scholes model with RCA GARCH volatility and show that these moments can be used to evaluate the call price for European options.

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“…Residuals from the RCA model can be described by the GARCH model (Thavaneswaran, Peiris, Appadoo, 2008;Thavaneswaran, Appadoo, Ghahramani, 2009). Then, the RCA(1)-GARCH(p,q) model described by equation V, where…”

Section: The Family Of Sign Rca Modelsmentioning

confidence: 99%

“…When the sign function is added to the RCA-GARCH model, then the process described by equation VI is obtained (Thavaneswaran, Appadoo, Ghahramani, 2009). The conditions ensuring the positive value of conditional variance of this process are following:…”

Section: The Family Of Sign Rca Modelsmentioning

confidence: 99%

Application of the Family of Sign RCA Models for Obtaining the Selected Risk Measures

Górka

2009

DEM

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A b s t r a c t. Accurate modelling of risk is very important in finance. There are many alternative risk measures, however none of them is dominating. This paper proposes to use the family of Sign RCA models to obtain the Value-at-Risk (VaR) and Expected Shortfall (ES) measures. For models from the family of Sign RCA models and AR-GARCH model the one-step forecasts of VaR were calculated based on rolling estimates from the given model using different window sizes. To obtain the VaR and ES measures the filtered historical simulation was used in new version proposed by Christoffersen. The results were verified using backtesting and the loss function.

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RCA models with GARCH innovations

Cited by 16 publications

References 8 publications

Option Pricing under Sign RCA-GARCH Models

Option Pricing under Sign RCA-GARCH Models

Option Pricing Applications of Quadratic Volatility Models

Application of the Family of Sign RCA Models for Obtaining the Selected Risk Measures

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