Technical paper/Option pricing
A new arbitrage-free parametric volatility surface
A new arbitrage-free volatility surface with closed-form valuation and local volatility is introduced
High-order approximations to call option prices in the Heston model
In the present paper, a decomposition formula for the call price due to Alòs is transformed into a Taylor-type formula containing an infinite series with stochastic terms. The new decomposition may be considered as an alternative to the decomposition of…
Risk-neutral densities: advanced methods of estimating nonnormal options underlying asset prices and returns
This work expands the analysis in Cooper (1999) and Santos and Guerra (2014), and the performance of the nonstructural models in estimating the "true" RNDs was measured through a process that generates "true" RNDs that are closer to reality, due to the…
Numerical simulation and applications of the convection–diffusion–reaction
This paper develops two local mesh-free methods for designing stencil weights and spatial discretization, respectively, for parabolic partial differential equations (PDEs) of convection–diffusion–reaction type.
Deep learning calibration of option pricing models: some pitfalls and solutions
Addressing model calibration and the issue of no-arbitrage in a deep learning approach
ADOL: Markovian approximation of a rough lognormal model
A variation of the rough volatility model is introduced by plugging in a different stochastic process
A pairwise local correlation model
In this paper, the authors develop a new local correlation model that uses a generic function 'g' to describe the correlation between all asset–asset pairs for a basket of underlyings.
Hedging of options in the presence of jump clustering
This paper analyzes the efficiency of hedging strategies for stock options in the presence of jump clustering.
Importance sampling for jump–diffusions via cross-entropy
This paper develops efficient importance sampling schemes for a class of jump–diffusion processes that are commonly used for modeling stock prices.
Importance sampling applied to Greeks for jump–diffusion models with stochastic volatility
In this paper, the authors develop a procedure to reduce the variance when numerically computing the Greeks obtained via Malliavin calculus for jump–diffusion models with stochastic volatility.
Estimating the tail shape parameter from option prices
In this paper, the author proposes a method to estimate the tail shape parameter of the risk-neutral density.
Model calibration with neural networks
Andres Hernandez presents a neural network approach to speed up model calibration
On empirical likelihood option pricing
This paper investigates the application of the empirical likelihood method in the study of option pricing.
Model-free valuation of barrier options
Austing and Li provide a continuous barrier options pricing formula that fits the volatility smile
XVA at the exercise boundary
Andrew Green and Chris Kenyon show how the decision to exercise an option is influenced by XVAs
Error analysis in Fourier methods for option pricing
The authors provide a bound for the error committed when using a Fourier method to price European options, when the underlying follows an exponential Lévy dynamic.
An efficient convergent lattice method for Asian option pricing with superlinear complexity
In this paper the authors present an efficient convergent lattice method for Asian option pricing with superlinear complexity.
Valuation of barrier options using sequential Monte Carlo
The authors present Sequential Monte Carlo (SMC) method for pricing barrier options.
A reduced basis method for parabolic partial differential equations with parameter functions and application to option pricing
The authors introduce an RB space–time variational approach for parametric PPDEs with coefficient parameters and a variable initial condition.
Deconstructing correlation
Peter Austing introduces an analytic or semi-analytic valuation of basket options
A new improvement scheme for approximation methods of probability density functions
This paper develops a new scheme for improving an approximation method of a probability density function.
Johnson-Omega performance measure
Alexander Passow presents a portfolio performance measure that combines the omega measure with Johnson distributions
Stratified approximations for the pricing of options on average
The authors propose stratified approximations of option prices using the gamma and lognormal distributions, with an application to bond pricing in the Dothan model.
A novel Fourier transform B-spline method for option pricing
By means of B-spline interpolation, this paper provides an accurate closed-form representation of the option price under an inverse Fourier transform.