Black-Scholes
What is the volatility of an Asian option?
An adjustment for the volatility smile in Asian options is proposed
Rough volatility’s steampunk vision of future finance
Some of the trickiest puzzles in finance could be solved by blending old and new technologies
Penalty methods for bilateral XVA pricing in European and American contingent claims by a partial differential equation model
Under some assumptions, the valuation of financial derivatives, including a value adjustment to account for default risk (the so-called XVA), gives rise to a nonlinear partial differential equation (PDE). The authors propose numerical methods for…
The volatility paradigm that’s stirring up options pricing
‘Rough volatility’ models promise better pricing and hedging of options. But will they catch on?
Deep hedging strays when volatility gets rough – study
In the most realistic simulations, data-driven approach fared 30% worse than conventional hedging
Nowcasting networks
The authors devise a neural network-based compression/completion methodology for financial nowcasting.
Ex-SunGard chief Cris Conde’s random walk to fintech and beyond
Technologist talks artificial intelligence, angel investing and accidentally contributing to the Basel framework
A step closer to the perfect volatility model
Research on ‘rough volatility’ gives fresh insight into financial fluctuations, quant expert explains
Finding the nearest covariance matrix: the foreign exchange market case
The authors consider the problem of finding a valid covariance matrix in the foreign exchange market given an initial nonpositively semidefinite (non-PSD) estimate of such a matrix.
Valuing scenarios with real option pricing
Risk managers could use Black-Scholes to help drive strategy, writes René Doff
A positive response to negative oil prices
Overhauling pricing models could reap rewards even if prices don’t cross zero again
A tale of two (or three, or four) models
Performance measure based on quality of replicating portfolios outperforms ‘P&L explain’, new paper claims
Quantifying model performance
Quality of replicating portfolio is used to measure performance of a model
Bachelier – a strange new world for oil options
Model tuned to negative prices has implications for pricing, margining and delta hedging
CME was ill-prepared for negative oil prices, FCMs say
Bourse draws criticism over timing of options model change; delay in sending key margin file
Three adjustments in calibrating models with neural networks
New research addresses fundamental issues with ANN approximation of pricing models
Pricing American call options using the Black–Scholes equation with a nonlinear volatility function
In this paper, the authors investigate a nonlinear generalization of the Black–Scholes equation for pricing American-style call options, where the volatility term may depend on both the underlying asset price and the Gamma of the option.
The Chebyshev method for the implied volatility
In this paper, the authors propose a bivariate interpolation of the implied volatility surface based on Chebyshev polynomials. This yields a closed-form approximation of the implied volatility, which is easy to implement and to maintain.
Path independence of exotic options and convergence of binomial approximations
In this paper, the authors analyse the convergence of tree methods for pricing barrier and lookback options.
Deep hedging and the end of the Black-Scholes era
Quants are embracing the idea of ‘model free’ pricing and hedging
How AI could tear up risk modelling canon
BlackRock, MSCI, LFIS among firms looking to replace traditional, linear risk models
Podcast: Hans Buehler on deep hedging and harnessing data
Quant says a new machine learning technique could change the way banks hedge derivatives
JP Morgan turns to machine learning for options hedging
New models sidestep Black-Scholes and could slash hedging costs for some derivatives by up to 80%
Application of the Heath–Platen estimator in the Fong–Vasicek short rate model
In this paper, the authors construct a Heath-Platen-type Monte Carlo estimator that performs extraordinarily well compared with the crude Monte Carlo estimation.