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.
This paper develops a new scheme for improving an approximation method of a probability density function.
Alexander Passow presents a portfolio performance measure that combines the omega measure with Johnson distributions
The authors propose stratified approximations of option prices using the gamma and lognormal distributions, with an application to bond pricing in the Dothan model.
In this issue of The Journal of Computational Finance, we encounter different contemporary approximations and techniques for financial problems.
By means of B-spline interpolation, this paper provides an accurate closed-form representation of the option price under an inverse Fourier transform.
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Time constraints can be binding for ‘heavy’ Monte Carlo calculations of risk analytics – value-at-risk, potential future exposure, credit valuation adjustment – in intraday risk monitoring, so fast approximations are sometimes preferred. Vladislav...
Quantization is applied to price vanilla and barrier options
Wujiang Lou shows the impact of funding costs on option valuation
Stochastic volatility model combining Heston vol model and CIR++
Spread option pricing: importance of forex risk factors illustrated
Prediction of arbitrage-free option prices that outperform existing models