Greeks
Floating start date for 2020 stress test alarms EU banks
Regulator proposal could lead to less reliable market risk data, critics warn
Deep hedging and the end of the Black-Scholes era
Quants are embracing the idea of ‘model free’ pricing and hedging
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%
Eurostoxx dislocations signal autocall hedging pain
Swings in dividends and volatility reveal year-end stress as European index slump tests “peak vega”
Currency derivatives house of year: BNP Paribas
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.
Importance sampling applied to Greeks for jump–diffusion models with stochastic volatility
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.
Volatility trap: how gamma roused a market monster
Rates market is exposed to some of the same factors that caused equity volatility to explode in February
Reducing noise is as important as radical change
Quants study ways to reduce noise in XVA Greeks calculations
Pathwise XVA Greeks for early-exercise products
The calculation of XVA Greeks for portfolios with early-exercise products is discussed
Local-stochastic volatility: models and non-models
Lorenzo Bergomi exposes a condition important to the use of LSV models in trading
Sense and sensitivities: Isda Simm is not so simple
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.
Isolating a risk premium on the volatility of volatility
Lorenzo Ravagli shows how to exploit a risk premium embedded in the vol of vol in out-of-the-money options
CVA with Greeks and AAD
Reghai, Kettani and Messaoud present new technique to calculate CVA using adjoints
Managing option-trading risk when mental accounting influences prices
This paper explores the implications for risk management of mental accounting of a call option with its underlying.
Citi exec laments plight of the quants
Quant Congress USA: Quant departments have become “sterile” and “dumbed-down”
Structured products desks join the AAD revolution
Mathematical technique allows dealers to perform risk-sensitivity calculations 50 times faster
Greeks with continuous adjoints: fast to code, fast to run
Marzio Sala and Vincent Thiery show the derivation of the continuous adjoint problem for PDEs
Fast gammas for Bermudan swaptions
Fast gammas for Bermudan swaptions