The Journal of Computational Finance is an international peer-reviewed journal dedicated to advancing knowledge in the area of financial mathematics. The journal is focussed on the measurement, management and analysis of financial risk, and provides detailed insight into numerical and computational techniques in the pricing, hedging and risk management of financial instruments.
The journal welcomes papers dealing with innovative computational techniques in the following areas:
- Numerical solutions of pricing equations: finite differences, finite elements, and spectral techniques in one and multiple dimensions.
- Simulation approaches in pricing and risk management: advances in Monte Carlo and quasi-Monte Carlo methodologies; new strategies for market factors simulation.
- Optimization techniques in hedging and risk management.
- Fundamental numerical analysis relevant to finance: effect of boundary treatments on accuracy; new discretization of time-series analysis.
- Developments in free-boundary problems in finance: alternative ways and numerical implications in American option pricing.
The authors propose an efficient, novel numerical scheme for solving the stochastic Heath–Jarrow–Morton interest rate model.
Accelerated trinomial trees applied to American basket options and American options under the Bates model
This paper introduces accelerated trinomial trees, a novel efficient lattice method for the numerical pricing of derivative securities.
This paper develops a new scheme for improving an approximation method of a probability density function.
The authors propose stratified approximations of option prices using the gamma and lognormal distributions, with an application to bond pricing in the Dothan model.
Efficient solution of backward jump-diffusion partial integro-differential equations with splitting and matrix exponentials
A unified approach for solving jump-diffusion partial integro differential equations is proposed.
In this paper the use of B-splines is advocated for volatility modeling within the calibration of stochastic local volatility (SLV) models and for the parameterization of an arbitrage-free implied volatility surface calibrated to sparse option data.
The efficient application of automatic differentiation for computing gradients in financial applications
Automatic differentiation is the theme of this paper. The authors show that many functions in calibration and inverse problems, exhibit a natural substitution structure. A significant speedup is achieved compared with common reverse-mode AD.
This paper updates the option implied probability of default (iPoD) approach recently suggested in the literature.
Adaptive importance sampling techniques are widely known for the Gaussian setting of Brownian-driven diffusions. In this paper, the authors extend them to jump processes.
SLADI: a semi-Lagrangian alternating-direction implicit method for the numerical solution of advection–diffusion problems with application to electricity storage valuations
In this paper, an efficient and novel methodology for numerically solving advection–diffusion problems is presented.
In this paper algorithms are developed using the Hamilton–Jacobi–Bellman approach for parabolic partial integrodifferential equations related to the quadratic hedging strategy in incomplete markets.
The authors present a technique for finding upper bounds on the value of a portfolio in a (possibly high-dimensional) optimal investment problem.
When dealing with nonsmooth functions – such as a combination of a nonsmooth density and a payoff – spectral filters can be applied to deal efficiently with the so-called Gibbs phenomenon. The simplicity and effectiveness of classical filtering techniques...
By means of B-spline interpolation, this paper provides an accurate closed-form representation of the option price under an inverse Fourier transform.
By introducing the set-valued scenario, this paper proposes a unified robust portfolio selection approach under downside risk measures.
A simple approximation for the no-arbitrage drifts in Libor market model–SABR-family interest-rate models
This paper presents a simple approximation for the noarbitrage drifts that appear in Libor market model SABR-family term structure models.
Numerical valuation of derivatives in high-dimensional settings via partial differential equation expansions
This paper presents a new numerical approach to solving high-dimensional partial differential equations that arise in the valuation of exotic derivative securities. The resulting numerical solutions are carefully compared in terms of accuracy and run...
A novel partial integrodifferential equation-based framework for pricing interest rate derivatives under jump-extended short-rate models
Interest rate derivatives under jump-extended short-rate models have commonly been valued using lattice methods. This paper proposes a much faster and more accurate valuation method based on partial integrodifferential equations.
An efficient numerical partial differential equation approach for pricing foreign exchange interest rate hybrid derivatives
This paper discuss efficient pricing methods via a partial differential equation (PDE) approach for long-dated foreign exchange (FX) interest rate hybrids under a three-factor multicurrency pricing model with FX volatility skew.
The damped Crank–Nicolson time-marching scheme for the adaptive solution of the Black–Scholes equation
This paper deals with error estimators and mesh adaptation for a space-time finite element discretization of the basic Black-Scholes equation. An interesting modern numerical mathematical technique for a fundamental pricing equation in finance is explained.