Lévy Process-Driven Asymmetric Heteroscedastic Option Pricing Model and Empirical Analysis

This paper describes the peak, fat tail, and skewness characteristics of asset price via a Lévy process. It applies asymmetric GARCH model to depict asset price’s random volatility characteristics and builds a GARCH-Lévy option pricing model with random jump characteristics. It also uses circular maximum likelihood estimation technology to improve the stability of model parameter estimation. In order to test the model’s pricing results, we use Hong Kong Hang Seng Index (HSI) price data and its option data to carry out empirical studies. Results prove that the pricing bias of EGARCH-Lévy model is lower than that of standard Heston-Nandi (HN) model in the financial industry. For short-term, middle-term, and long-term European-style options, the pricing error of EGARCH-Lévy model is the lowest.

Download Full-text

Good Volatility, Bad Volatility, and Option Pricing

Journal of Financial and Quantitative Analysis ◽

10.1017/s0022109018000777 ◽

2018 ◽

Vol 54 (2) ◽

pp. 695-727 ◽

Cited By ~ 7

Author(s):

Bruno Feunou ◽

Cédric Okou

Keyword(s):

Option Pricing ◽

Stock Price ◽

Asset Price ◽

Jump Diffusion ◽

Quadratic Variation ◽

Pricing Model ◽

Economic Gain ◽

Underlying Asset ◽

Model Free ◽

Option Pricing Model

Advances in variance analysis permit the splitting of the total quadratic variation of a jump-diffusion process into upside and downside components. Recent studies establish that this decomposition enhances volatility predictions and highlight the upside/downside variance spread as a driver of the asymmetry in stock price distributions. To appraise the economic gain of this decomposition, we design a new and flexible option pricing model in which the underlying asset price exhibits distinct upside and downside semivariance dynamics driven by the model-free proxies of the variances. The new model outperforms common benchmarks, especially the alternative that splits the quadratic variation into diffusive and jump components.

Download Full-text

Research on Option Pricing Model under Uncertainty

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.513-517.3156 ◽

2014 ◽

Vol 513-517 ◽

pp. 3156-3159

Author(s):

Kun Long Zhang ◽

Li Xia Song

Keyword(s):

Empirical Study ◽

Option Pricing ◽

Financial Market ◽

Price Change ◽

Asset Price ◽

Pricing Model ◽

Pricing Models ◽

Uncertain Environments ◽

Option Pricing Model ◽

Behavior Choice

In the real financial market, there are always other uncertain phenomena, such as fuzzy phenomenon, random phenomenon. Along with empirical study increasing investigator discovered that this kind of uncertainty affects policy-maker's behavior choice and the asset price change. Researcher pay more and more attention to the problems on the option pricing under in uncertain environments, Therefore, the paper shows that options can be valued successfully in uncertain environments, some option pricing models are established, the corresponding algorithm is designed to solve these models.

Download Full-text