Local volatility models
Quant of the year: Julien Guyon
Risk Awards 2025: Volatility modeller par excellence (and football fan) achieved breakthrough with joint calibration of S&P and Vix options
Smile-consistent basket skew
An analytic approximation for the implied volatility surface of basket options is introduced
Vega decomposition for the LV model: an adjoint differentiation approach
Introducing an algorithm for computing vega sensitivities at all strikes and expiries
Reviving the lost art of perturbation for exotic pricing
Natixis quants find novel way to speed up volatility smile modelling
Singular exotic perturbation
A solution based on local volatility and sensitivities is proposed to calculate exotics' prices
Optimal transport for model calibration
Volatility models and SPX/VIX joint dynamics are calibrated using optimal transport theory
Probabilistic machine learning for local volatility
In this paper, the authors propose to approach the calibration problem of local volatility with Bayesian statistics to infer a conditional distribution over functions given observed data.
Follow the moneyness
Barclays quants extend Bergomi’s skew stickiness ratio to all strikes
Sticky varswaps
Bergomi's skew-stickiness ratio is extended to the setting of variance swaps
The step stochastic volatility model
Extreme short-dated skew can be obtained by decomposing it in two parts
What is the volatility of an Asian option?
An adjustment for the volatility smile in Asian options is proposed
My kingdom for the right copula
Copulas can still deliver if chosen with due attention to intuition and data, says quant fund chair
Breaking barriers in options pricing
A new technique for pricing exotic options unifies two classic models
Finite difference schemes with exact recovery of vanilla option prices
A model unifies the classic local vol and binomial trees to accurately price options
A new arbitrage-free parametric volatility surface
A new arbitrage-free volatility surface with closed-form valuation and local volatility is introduced
One-dimensional Markov-functional models driven by a non-Gaussian driver
The aim of this paper is to move away from a Gaussian assumption and to provide new algorithms that can be used to implement a Markov-functional model driven by a more general class of one-dimensional diffusion processes.
Rising star in quant finance: Blanka Horvath, Aitor Muguruza and Mehdi Tomas
Risk Awards 2020: New machine learning techniques bring ‘rough volatility’ models to life
Calling out autocallable pricing
Quants show popular autocallable pricing technique has a flaw that has been ignored until now
The interplay between stochastic volatility and correlations in equity autocallables
Study shows issues with pricing autocallables using SLV
You don’t need to sacrifice accuracy for flexibility
BAML quant proposes option pricing model that softens conflict between the two properties
Local stochastic volatility: shaken, not stirred
Dominique Bang introduces a novel LSV approach to term distribution modelling