Computational methods for option pricing

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If you have any problems with your access or would like to request an individual access account please contact our customer service team. 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:. This paper presents an autonomous effective trading system devoted to the support of decision-making processes in the financial market domain. This paper proposes a method for overhedging weighted variance using only a finite number of maturities.

This paper presents a natural extension of the LGM that keeps the affine structure and generates an implied volatility smile. The authors build a whole family of local correlation models by combining the particle method with a new, simple idea. In this paper the authors present an efficient convergent lattice method for Asian option pricing with superlinear complexity.

The authors introduce an RB space—time variational approach for parametric PPDEs with coefficient parameters and a variable initial condition. Stock market crash speeds great depression 1929 authors propose a general framework to assess the probability of backtest overfitting PBO. This paper applies a variety of second-order finite difference schemes to the SABR arbitrage-free density problem and explores alternative formulations.

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. The Authors introduce a closed-form approximation for computational methods for option pricing forward implied volatilities.

The paper deals with robust and accurate numerical solution methods for the nonlinear Hamilton—Jacobi—Bellman partial differential equation PDEwhich describes the dynamic optimal portfolio selection problem. This paper presents a high-performance spectral collocation method for the computation of American put and call option prices.

The authors propose so-called tail thinning strategies that may be employed to better connect the calibrated models to the crash cliquets prices.

A new simulation algorithm for computing the Hessians of Bermudan swaptions and cancelable swaps is presented. This paper considers the numerical valuation of swing options in electricity markets based on a two-factor model.

In the paper, real-world and risk-neutral scenarios are combined for the valuation of the exposure values of Bermudan swaptions on real-world Monte Carlo paths. The authors propose a method for determining an arbitrage-free density implied by the Hagan formula. Events Awards White papers Research Books Jobs Newsletters Welcome My account Sign in.

Monte Carlo method - Wikipedia

Energy Risk Europe The professional energy community will gather in London for four days of cutting-edge discussions and networking with fellow industry peers at the 20th annual Energy Risk Summit Europe.

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Computational Methods for Option Pricing (Frontiers in Applied Mathematics) (Frontiers in Applied Mathematics 30)

Don't miss out on new jobs Sign up. Job of the week. Journal of Computational Finance ISSN: The journal welcomes papers dealing with innovative computational techniques in the following areas: Numerical solutions of pricing equations: Simulation approaches in pricing and risk management: Optimization techniques in hedging and risk management.

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