The authors of this paper use power series distributions to develop a novel and flexible zero-inflated Bayesian methodology.
In this paper the authors present an efficient convergent lattice method for Asian option pricing with superlinear complexity.
The authors present Sequential Monte Carlo (SMC) method for pricing barrier options.
This issue contains four technical papers. Two of which deal with an analysis of the SMA, one paper deals with data and another tackles statistical issues around the quantification of operational risk.
The authors of this paper assess the right-hand tail of an insurer’s loss distribution for a specified period (a year), presenting and analyzing six different approaches in doing so.
A mixed Monte Carlo and partial differential equation variance reduction method for foreign exchange options under the Heston–Cox–Ingersoll–Ross model
The paper concerns a hybrid pricing method build upon a combination of Monte Carlo and PDE approach for FX options under the four-factor Heston-CIR model.
An exact and efficient method for computing cross-Gammas of Bermudan swaptions and cancelable swaps under the Libor market model
A new simulation algorithm for computing the Hessians of Bermudan swaptions and cancelable swaps is presented.
South African academics pioneer a quick and easy way of estimating op risk capital
The authors develop a technique, based on numerical inversion, to compute the prices and Greeks of lookback options driven by Lévy processes.
This issue of The Journal of Computational Finance contains four papers that are quite different in terms of their financial applications, and they stand out because of their remarkable mathematical techniques.
The authors propose a novel method for efficiently comparing the performance of different stopping times.
How to calculate expected future carbon costs and optimal valuation and hedging decisions, by adjusting Monte Carlo simulations for the UK market
This paper studies the problem of optimal trading using general alpha predictors with linear costs and temporary impact.
Wujiang Lou presents a framework to compute recursive CVA and FVA via Monte Carlo simulation
This paper discusses a VaR time-scaling approach based on fitting a distribution function so as to apply a Monte Carlo simulation to determine long-term VaR.
The authors propose an efficient, novel numerical scheme for solving the stochastic Heath–Jarrow–Morton interest rate model.