New paper by Nomura quant applies volatility model used in equities to exotic rate hedging
The combination of two popular volatility models sharpens the hedging of exotic rate derivatives
Risk Awards 2020: New machine learning techniques bring ‘rough volatility’ models to life
A variation of the rough volatility model is introduced by plugging in a different stochastic process
The main goal of this paper is to perform a comprehensive nonparametric jump detection model comparison and validation. To this end, the authors design an extensive Monte Carlo study to compare and validate these tests.
In this paper, the authors construct a Heath-Platen-type Monte Carlo estimator that performs extraordinarily well compared with the crude Monte Carlo estimation.
El Euch, Rosenbaum, Gatheral combine a rough volatility model with the classical Heston model
In this paper, the authors give a preprocessing step for Fourier methods that involves projecting the Green’s function onto the set of linear basis functions.
In this paper, the author describes a simple adaptive Filon method that performs better and more accurately than various popular alternatives for pricing options under the Heston model.
A new closed-form approximation is applied to quanto CDS pricing
BAML quant proposes option pricing model that softens conflict between the two properties
New approach delivers quick and accurate computation of prices
Dominique Bang introduces a novel LSV approach to term distribution modelling
This paper considers the classical optimal investment allocation problem of Merton through the lens of some more modern approaches, such as the stochastic volatility and local volatility models.
Amine Ahallal and Olaf Torne add a knock-out barrier to the standard corridor variance swap
In this paper, the authors combine MS dynamic copulas with the skewed t SV model to study the optimal hedge ratios of portfolios.
SocGen quants calibrate local stochastic volatility models with stochastic dividends
An easy to calibrate and accurate swap market model is proposed
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.
Hybrid finite-difference/pseudospectral methods for the Heston and Heston–Hull–White partial differential equations
In this paper, the authors propose a hybrid spatial finite-difference/pseudospectral discretization for European option-pricing problems under the Heston and Heston–Hull–White models.
UBS quants show prices can differ by up to 25 correlation points if products modelled accurately
A correlation structure is an important element in pricing products such as correlation swaps
Fiorin, Callegaro and Grasselli show how discretisation methods reduce computing time in high-dimensional problems
In this paper, the authors study a hybrid tree/finite-difference method, which allows us to obtain efficient and accurate European and American option prices in the Heston–Hull– White and Heston–Hull–White2d models.