Option pricing
Brexit drama muddies water for FX options market
Traders focusing on new dates – and scenarios – after domestic UK criticism of proposed deal
Podcast: SocGen quants on exotics calibration, machine learning and autocallable pricing
Deep learning techniques are being explored by the quants to speed up exotics pricing
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.
Cash no longer king in European swaptions
Barclays executives explore weaknesses of current pricing formulas for cash-settled swaptions
Quants needed: how finance can use power of quantum tech
New machines have big potential in AI, valuations and VAR, but tech giants like IBM need help from practitioners
Podcast: Callegaro, Fiorin and Grasselli on quantization
High-dimension problems can be solved with discretisation techniques
Quantitative finance still needs mathematicians
Quants develop model that fixes a longstanding problem with pricing American options
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
Why XVAs need to be factored into options pricing
Ignoring valuation adjustments could be storing up problems for the future
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.
Trading calendar spread options on energy futures
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