This work presents an efficient computational framework for pricing a general class of exotic and vanilla options under a versatile stochastic volatility model.
HKMA will steer how historical volatility data can be used for valuing new options contracts
In the most realistic simulations, data-driven approach fared 30% worse than conventional hedging
In this paper, the authors introduce two mixing fractions that can be controlled separately to apply impact to the volatility-of-volatility and the correlation in a lognormal LSV model.
New pricer for options with time-dependent barrier shown to be computationally efficient and stable
Research on ‘rough volatility’ gives fresh insight into financial fluctuations, quant expert explains
Use cases for new tech are piling up – from CVA to VAR. But so are the obstacles
Risk managers could use Black-Scholes to help drive strategy, writes René Doff
A new arbitrage-free volatility surface with closed-form valuation and local volatility is introduced
In the present paper, a decomposition formula for the call price due to Alòs is transformed into a Taylor-type formula containing an infinite series with stochastic terms. The new decomposition may be considered as an alternative to the decomposition of…
Risk-neutral densities: advanced methods of estimating nonnormal options underlying asset prices and returns
This work expands the analysis in Cooper (1999) and Santos and Guerra (2014), and the performance of the nonstructural models in estimating the "true" RNDs was measured through a process that generates "true" RNDs that are closer to reality, due to the…
Overhauling pricing models could reap rewards even if prices don’t cross zero again
Model tuned to negative prices has implications for pricing, margining and delta hedging
New tool aims to gauge wider cost of virus control measures
This paper develops two local mesh-free methods for designing stencil weights and spatial discretization, respectively, for parabolic partial differential equations (PDEs) of convection–diffusion–reaction type.
New research addresses fundamental issues with ANN approximation of pricing models
Addressing model calibration and the issue of no-arbitrage in a deep learning approach
A variation of the rough volatility model is introduced by plugging in a different stochastic process
EBA options for lighter capital treatment of parametric curves could prove impractical
In this paper, the authors develop a new local correlation model that uses a generic function 'g' to describe the correlation between all asset–asset pairs for a basket of underlyings.
This paper analyzes the efficiency of hedging strategies for stock options in the presence of jump clustering.
Traders focusing on new dates – and scenarios – after domestic UK criticism of proposed deal
Deep learning techniques are being explored by the quants to speed up exotics pricing
This paper develops efficient importance sampling schemes for a class of jump–diffusion processes that are commonly used for modeling stock prices.