A numerical method to obtain stable deltas and gammas for complex payoffs is presented
New pricer for options with time-dependent barrier shown to be computationally efficient and stable
New research addresses fundamental issues with ANN approximation of pricing models
This paper considers the problem of efficiently computing the full matrix of second-order sensitivities of a Monte Carlo price when the number of inputs is large.
Regulator proposal could lead to less reliable market risk data, critics warn
Quants are embracing the idea of ‘model free’ pricing and hedging
Quant says a new machine learning technique could change the way banks hedge derivatives
New models sidestep Black-Scholes and could slash hedging costs for some derivatives by up to 80%
Swings in dividends and volatility reveal year-end stress as European index slump tests “peak vega”
Risk Awards 2019: French bank hits options windfall in Turkey during currency crash
Vibrato and automatic differentiation for high-order derivatives and sensitivities of financial options
This paper deals with the computation of second-order or higher Greeks of financial securities. It combines two methods, vibrato and automatic differentiation (AD), and compares these with other methods.
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.
Rates market is exposed to some of the same factors that caused equity volatility to explode in February
Quants study ways to reduce noise in XVA Greeks calculations
The calculation of XVA Greeks for portfolios with early-exercise products is discussed
Lorenzo Bergomi exposes a condition important to the use of LSV models in trading
Three industry experts argue initial margin calculations for uncleared trades won't work without centralised calibration of sensitivities
The efficient application of automatic differentiation for computing gradients in financial applications
Automatic differentiation is the theme of this paper. The authors show that many functions in calibration and inverse problems, exhibit a natural substitution structure. A significant speedup is achieved compared with common reverse-mode AD.
Lorenzo Ravagli shows how to exploit a risk premium embedded in the vol of vol in out-of-the-money options
Reghai, Kettani and Messaoud present new technique to calculate CVA using adjoints
This paper explores the implications for risk management of mental accounting of a call option with its underlying.
Quant Congress USA: Quant departments have become “sterile” and “dumbed-down”
Mathematical technique allows dealers to perform risk-sensitivity calculations 50 times faster
Marzio Sala and Vincent Thiery show the derivation of the continuous adjoint problem for PDEs