Testing volatility autocorrelation in the constant elasticity of variance stochastic volatility model

2009 ◽  
Vol 53 (6) ◽  
pp. 2201-2218 ◽  
Author(s):  
Gianna Figà-Talamanca
Keyword(s):  
Stochastic Volatility ◽  
Stochastic Volatility Model ◽  
Constant Elasticity ◽  
Constant Elasticity Of Variance ◽  
Volatility Model

scholarly journals Pricing Arithmetic Asian Options under Hybrid Stochastic and Local Volatility

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Min-Ku Lee ◽  
Jeong-Hoon Kim ◽  
Kyu-Hwan Jang
Keyword(s):  
Stochastic Volatility ◽  
Option Price ◽  
Stochastic Volatility Model ◽  
Asian Options ◽  
Partial Differential ◽  
Constant Elasticity ◽  
Local Volatility ◽  
Constant Elasticity Of Variance ◽  
Arithmetic Average ◽  
Volatility Model

Recently, hybrid stochastic and local volatility models have become an industry standard for the pricing of derivatives and other problems in finance. In this study, we use a multiscale stochastic volatility model incorporated by the constant elasticity of variance to understand the price structure of continuous arithmetic average Asian options. The multiscale partial differential equation for the option price is approximated by a couple of single scale partial differential equations. In terms of the elasticity parameter governing the leverage effect, a correction to the stochastic volatility model is made for more efficient pricing and hedging of Asian options.

On the Performance of the Comonotonicity Approach for Pricing Asian Options in Some Benchmark Models from Equities and Commodities

2017 ◽  
Vol 20 (01) ◽  
pp. 1750005
Author(s):  
Jilong Chen ◽  
Christian Ewald
Keyword(s):  
Upper Bounds ◽  
Stochastic Volatility Model ◽  
Asian Options ◽  
Convenience Yield ◽  
Yield Model ◽  
Cev Model ◽  
Constant Elasticity ◽  
Constant Elasticity Of Variance ◽  
Hedging Strategies ◽  
Volatility Model

In this paper, we investigate the applicability of the comonotonicity approach in the context of various benchmark models for equities and commodities. Instead of classical Lévy models as in Albrecher et al. we focus on the Heston stochastic volatility model, the constant elasticity of variance (CEV) model and Schwartz’ 1997 stochastic convenience yield model. We show how the technical difficulties of inverting the distribution function of the sum of the comonotonic random vector can be overcome and that the method delivers rather tight upper bounds for the prices of Asian Options in these models, at least for strikes which are not too large. As a by-product the method delivers super-hedging strategies which can be easily implemented.

scholarly journals Turbo Warrants under Hybrid Stochastic and Local Volatility

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Min-Ku Lee ◽  
Ji-Hun Yoon ◽  
Jeong-Hoon Kim ◽  
Sun-Hwa Cho
Keyword(s):  
Stochastic Volatility ◽  
Uhlenbeck Process ◽  
Variance Model ◽  
Constant Elasticity ◽  
Local Volatility ◽  
Constant Elasticity Of Variance ◽  
Local Volatility Model ◽  
Volatility Model ◽  
Ornstein Uhlenbeck Process ◽  
Sensitive Structure

This paper considers the pricing of turbo warrants under a hybrid stochastic and local volatility model. The model consists of the constant elasticity of variance model incorporated by a fast fluctuating Ornstein-Uhlenbeck process for stochastic volatility. The sensitive structure of the turbo warrant price is revealed by asymptotic analysis and numerical computation based on the observation that the elasticity of variance controls leverage effects and plays an important role in characterizing various phases of volatile markets.

Empirical Performance of the Constant Elasticity Variance Option Pricing Model

2009 ◽  
Vol 12 (02) ◽  
pp. 177-217 ◽  
Author(s):  
Ren-Raw Chen ◽  
Cheng-Few Lee ◽  
Han-Hsing Lee
Keyword(s):  
Option Pricing ◽  
Stochastic Volatility ◽  
Stochastic Volatility Model ◽  
Pricing Model ◽  
Implementation Cost ◽  
Pricing Models ◽  
Cev Model ◽  
Constant Elasticity ◽  
Volatility Model ◽  
Option Pricing Model

In this essay, we empirically test the Constant–Elasticity-of-Variance (CEV) option pricing model by Cox (1975, 1996 ) and Cox and Ross (1976), and compare the performances of the CEV and alternative option pricing models, mainly the stochastic volatility model, in terms of European option pricing and cost-accuracy based analysis of their numerical procedures. In European-style option pricing, we have tested the empirical pricing performance of the CEV model and compared the results with those by Bakshi et al. (1997). The CEV model, introducing only one more parameter compared with Black-Scholes formula, improves the performance notably in all of the tests of in-sample, out-of-sample and the stability of implied volatility. Furthermore, with a much simpler model, the CEV model can still perform better than the stochastic volatility model in short term and out-of-the-money categories. When applied to American option pricing, high-dimensional lattice models are prohibitively expensive. Our numerical experiments clearly show that the CEV model performs much better in terms of the speed of convergence to its closed form solution, while the implementation cost of the stochastic volatility model is too high and practically infeasible for empirical work. In summary, with a much less implementation cost and faster computational speed, the CEV option pricing model could be a better candidate than more complex option pricing models, especially when one wants to apply the CEV process for pricing more complicated path-dependent options or credit risk models.

A non-Gaussian stochastic volatility model

1998 ◽  
Vol 2 (2) ◽  
pp. 33-47 ◽  
Author(s):  
Yuichi Nagahara ◽  
Genshiro Kitagawa
Keyword(s):  
Stochastic Volatility ◽  
Stochastic Volatility Model ◽  
Volatility Model ◽  
Non Gaussian
Sign in / Sign up

Export Citation Format

Share Document