Option pricing
Option pricing using high-frequency futures prices
The authors examine two potential routes to improve the outcome of option pricing: extracting the variance from futures prices instead of the underlying asset prices, and calculating the variance in different frequencies with intraday data instead of…
Jarrow and co find a better way to spot stock market bubbles
Quant team’s options-based approach avoids pitfalls of historical data dependence
An end to replication
Convexity adjustments can be valued with an analytical formula, avoiding replication arguments
The CTMC–Heston model: calibration and exotic option pricing with SWIFT
This work presents an efficient computational framework for pricing a general class of exotic and vanilla options under a versatile stochastic volatility model.
Hong Kong banks await guidance on IRRBB for risk-free rates
HKMA will steer how historical volatility data can be used for valuing new options contracts
Deep hedging strays when volatility gets rough – study
In the most realistic simulations, data-driven approach fared 30% worse than conventional hedging
Introducing two mixing fractions to a lognormal local-stochastic volatility model
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.
Semi-closed-form prices of barrier options in the Hull-White model
New pricer for options with time-dependent barrier shown to be computationally efficient and stable
A step closer to the perfect volatility model
Research on ‘rough volatility’ gives fresh insight into financial fluctuations, quant expert explains
Science friction: some tire of waiting for quantum’s leap
Use cases for new tech are piling up – from CVA to VAR. But so are the obstacles
Valuing scenarios with real option pricing
Risk managers could use Black-Scholes to help drive strategy, writes René Doff
A new arbitrage-free parametric volatility surface
A new arbitrage-free volatility surface with closed-form valuation and local volatility is introduced
High-order approximations to call option prices in the Heston model
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…
A positive response to negative oil prices
Overhauling pricing models could reap rewards even if prices don’t cross zero again
Bachelier – a strange new world for oil options
Model tuned to negative prices has implications for pricing, margining and delta hedging
Two quants use options pricing tools to model Covid-19
New tool aims to gauge wider cost of virus control measures
Numerical simulation and applications of the convection–diffusion–reaction
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.
Three adjustments in calibrating models with neural networks
New research addresses fundamental issues with ANN approximation of pricing models
Deep learning calibration of option pricing models: some pitfalls and solutions
Addressing model calibration and the issue of no-arbitrage in a deep learning approach
ADOL: Markovian approximation of a rough lognormal model
A variation of the rough volatility model is introduced by plugging in a different stochastic process
EU banks grapple with NMRF proposals for volatility models
EBA options for lighter capital treatment of parametric curves could prove impractical
A pairwise local correlation model
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.
Hedging of options in the presence of jump clustering
This paper analyzes the efficiency of hedging strategies for stock options in the presence of jump clustering.