• Communications for Statistical Applications and Methods
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• 제18권2호
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• pp.229-236
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• 2011

A continuous time stochastic volatility model for financial assets suggested by Barndorff-Nielsen and Shephard (2001) is considered, where the volatility process is modelled as an Ornstein-Uhlenbeck type process driven by a general L$\'{e}$vy process and the price process is then obtained by using an independent Brownian motion as the driving noise. The uniform ergodicity of the volatility process and exponential ${\alpha}$-mixing properties of the log price processes of given continuous time stochastic volatility models are obtained.

• The Journal of Asian Finance, Economics and Business
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• 제8권2호
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• pp.685-695
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• 2021

This study explores the impact of stochastic volatility in option pricing. To be more specific, we compare the option pricing performance between stochastic volatility option pricing model, namely, Heston option pricing model and standard Black-Scholes option pricing. Our finding, based on the market price of SET50 index option between May 2011 and September 2020, demonstrates stochastic volatility of underlying asset return for all level of moneyness. We find that both deep in the money and deep out of the money option exhibit higher volatility comparing with out of the money, at the money, and in the money option. Hence, our finding confirms the existence of volatility smile in Thai option markets. Further, based on calibration technique, the Heston option pricing model generates smaller pricing error for all level of moneyness and time to expiration than standard Black-Scholes option pricing model, though both Heston and Black-Scholes generate large pricing error for deep-in-the-money option and option that is far from expiration. Moreover, Heston option pricing model demonstrates a better pricing accuracy for call option than put option for all level and time to expiration. In sum, our finding supports the outperformance of the Heston option pricing model over standard Black-Scholes option pricing model.

• KDI Journal of Economic Policy
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• 제40권4호
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• pp.1-22
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• 2018

We estimate three continuous-time stochastic volatility models following the approach by Aït-Sahalia and Kimmel (2007) to compare the Korean and US stock markets. To do this, the Heston, GARCH, and CEV models are applied to the KOSPI 200 and S&P 500 Index. For the latent volatility variable, we generate and use the integrated volatility proxy using the implied volatility of short-dated at-the-money option prices. We conduct MLE in order to estimate the parameters of the stochastic volatility models. To do this we need the transition probability density function (TPDF), but the true TPDF is not available for any of the models in this paper. Therefore, the TPDFs are approximated using the irreducible method introduced in Aït-Sahalia (2008). Among three stochastic volatility models, the Heston model and the CEV model are found to be best for the Korean and US stock markets, respectively. There exist relatively strong leverage effects in both countries. Despite the fact that the long-run mean level of the integrated volatility proxy (IV) was not statistically significant in either market, the speeds of the mean reversion parameters are statistically significant and meaningful in both markets. The IV is found to return to its long-run mean value more rapidly in Korea than in the US. All parameters related to the volatility function of the IV are statistically significant. Although the volatility of the IV is more elastic in the US stock market, the volatility itself is greater in Korea than in the US over the range of the observed IV.

• 대한수학회논문집
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• 제29권3호
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• pp.489-496
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• 2014

We drive a closed-form expression for the price of a European quanto call option in the double square root stochastic volatility model.

• 디지털융복합연구
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• 제7권1호
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• pp.73-80
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• 2009

In this study, the pricing performances of alternative simple option models are examined by creating a simulated market environment in which asset prices evolve according to a stochastic volatility process. To do this, option prices fully consistent with Heston[9]'s model are generated. Assuming this prices as market prices, the trading positions utilizing the Black-Scholes[4] model, a semi-parametric Corrado-Su[7] model and an ad-hoc modified Black-Scholes model are evaluated with respect to the true option prices obtained from Heston's stochastic volatility model. The simulation results suggest that both the Corrado-Su model and the modified Black-Scholes model perform well in this simulated world substantially reducing the biases of the Black-Scholes model arising from stochastic volatility. Surprisingly, however, the improvements of the modified Black-Scholes model over the Black-Scholes model are much higher than those of the Corrado-Su model.

• Journal of the Korean Data and Information Science Society
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• 제22권6호
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• pp.1199-1215
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• 2011

Relaxing an unrealistic assumption of a representative percolation model, this paper demonstrates that herd behavior leads to a high increase in volatility but not trading volume, in contrast with information flows that give rise to increases in both volatility and trading volume. Although detecting herd behavior has posed a great challenge due to its empirical difficulty, this paper proposes a new methodology for detecting trading days with herding. Furthermore, this paper suggests a herd-behavior-stochastic-volatility model, which accounts for herding in financial markets. Strong evidence in favor of the model specification over the standard stochastic volatility model is based on empirical application with high frequency data in the Korean equity market, strongly supporting the intuition that herd behavior causes excess volatility. In addition, this research indicates that strong persistence in volatility, which is a prevalent feature in financial markets, is likely attributed to herd behavior rather than news.

• 응용통계연구
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• 제36권1호
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• pp.85-100
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• 2023

Stochastic volatility (SV) 모형은 시변 변동성을 모델링하는 주요한 수단 중 하나이며, 특히 금융시장 변동성의 추정 및 예측, 옵션의 가격 결정 등의 분야에서 활발하게 사용되고 있다. 본 논문은 SV 모형을 활용하여 비트코인 시장의 시변 변동성을 모델링하고자 한다. 시장의 변동성은 국면 전환의 특성을 갖고 있다고 알려져 있으며, 시장의 변동 국면을 나누기 위해 시계열의 패턴을 인식하는 작업에 유용한 hidden Markov model(HMM)을 결합하여 사용하고자 한다. 본 연구는 암호화폐 거래 사이트 업비트의 비트코인 데이터를 활용하여 비트코인의 변동성 모형을 추정하였으며 SV 모형의 성능을 높이기 위하여 시장의 변동 국면을 나누어 분석을 진행하였다. MCMC 기법이 SV 모델의 모수를 추정하는 데 사용되며 MAPE, MSE 등의 평가 기준을 통하여 모델의 성능을 확인하고자 한다.

• 대한수학회보
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• 제46권2호
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• pp.209-227
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• 2009

We examine a unified approach of calculating the closed form solutions of option price under stochastic volatility models using stochastic calculus and the Fourier inversion formula. In particular, we review and derive the option pricing formulas under Heston and correlated Stein-Stein models using a systematic and comprehensive approach which were derived individually earlier. We compare the empirical performances of the two stochastic volatility models and the Black-Scholes model in pricing KOSPI 200 index options.

• 재무관리연구
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• 제20권1호
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• pp.213-231
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• 2003

본 연구에서는 우리나라 주식시장에서 연속시간모형의 실증적 탐구와 확장을 위하여 정교하고 포괄적인 방법론을 도입하고자 하였다. 즉 확률변동성(Stochastic Volatility) 모형을 이용하여 우리나라 주식수익률 과정을 연속시간모형으로 설정하고 이런 정교한 연속모형의 추정을 위하여 효율적 적률법(EMM)을 도입하였다. 본 연구의 분석기간은 1995년 1월 3일부터 2002년 12월 30일까지이며 분석대상은 일별 KOSPI 지수 2150 관측치 이다. 연구모형 분석결과 우리나라 주가지수 수익률의 비정규성, leptokurtic한 분포 및 확률변동성 등이 추정되었으며 특히 EMM 모형의 추정결과 우리나라 주식시장의 주가지수 수익률과정은 단일요인(one factor) 확률변동성 모형보다는 2 요인(two factor) 확률변동성 모형을 도입하는 것이 더 바람직한 것으로 판명되었고 또한 확률변동성 모형을 설정할 때에는 우리나라의 개별 주식수익률뿐만 아니라 주가지수 수익률 등에도 존재되는 것으로 알려진 점프 특성 고려의 필요성이 증대되었다. 외환위기 이후 주식시장의 변동성 급등락 현상이 갈수록 심화되어 금융자산 위험관리의 필요가 절실히 요구되는 요즘시기에 기초자산의 수익률과정 및 확률변동성 특성을 심층적으로 분석하는 본 연구를 통하여 각종 금융기관 및 투자자들의 투자기회비용과 시행착오를 줄이는데 큰 도움을 줄 수 있을 것으로 기대된다.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제19권4호
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• pp.417-428
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• 2015

Although, in general, the random fluctuation of interest rates gives a limited impact on portfolio optimization, their stochastic nature may exert a significant influence on the process of selecting the proportions of various assets to be held in a given portfolio when the stochastic volatility of risky assets is considered. The stochastic volatility covers a variety of known models to fit in with diverse economic environments. In this paper, an optimal strategy for portfolio selection as well as the smoothness properties of the relevant value function are studied with the dynamic programming method under a market model of both stochastic volatility and stochastic interest rates.