Transformation and weighting in regression
Transformation and weighting in regression
Numerical recipes in FORTRAN (2nd ed.): the art of scientific computing
Numerical recipes in FORTRAN (2nd ed.): the art of scientific computing
An algorithm for nonparametric GARCH modelling
Computational Statistics & Data Analysis
On the applicability of stochastic volatility models
Computational Statistics & Data Analysis
A class of nonlinear stochastic volatility models and its implications for pricing currency options
Computational Statistics & Data Analysis
Generalised long-memory GARCH models for intra-daily volatility
Computational Statistics & Data Analysis
Modelling long-memory volatilities with leverage effect: A-LMSV versus FIEGARCH
Computational Statistics & Data Analysis
Analysis of filtering and smoothing algorithms for Lévy-driven stochastic volatility models
Computational Statistics & Data Analysis
Block sampler and posterior mode estimation for asymmetric stochastic volatility models
Computational Statistics & Data Analysis
Robustness of Fourier estimator of integrated volatility in the presence of microstructure noise
Computational Statistics & Data Analysis
Volatility forecasting using threshold heteroskedastic models of the intra-day range
Computational Statistics & Data Analysis
A GMM procedure for combining volatility forecasts
Computational Statistics & Data Analysis
Comparing stochastic volatility models through Monte Carlo simulations
Computational Statistics & Data Analysis
Evaluating volatility forecasts in option pricing in the context of a simulated options market
Computational Statistics & Data Analysis
An option pricing formula for the GARCH diffusion model
Computational Statistics & Data Analysis
Bootstrap prediction for returns and volatilities in GARCH models
Computational Statistics & Data Analysis
Asian basket options and implied correlations in oil markets
FEA '07 Proceedings of the Fourth IASTED International Conference on Financial Engineering and Applications
| Hi-index | 0.03 |
Modelling the implied volatility surface as a function of an option's strike price and maturity is a subject of extensive research in financial markets. The implied volatility in commodity markets is much less studied, due to a limited liquidity and the complicated structure of commodity options. A new semi-parametric method is introduced for modelling the implied volatility surface and is applied to the option price data from oil markets. This approach combines the simplicity of a parametric method with the flexibility of a non-parametric approach. The method can successfully deal with a limited amount of option price data. Performance of the method is investigated by applying it to prices of exchange-traded crude oil and gasoline options, and the results are compared with those obtained by a purely parametric approach. Furthermore, the investigation of the relationship between volatilities implied from European and Asian options shows that Asian options in oil markets are significantly more expensive than theoretical arguments imply.