The authors compare JLSMC DIM estimates with those produced by two other methods, finding that the JLSMC algorithm is accurate and efficient, producing results comparable with nested Monte Carlo with an order of magnitude less computational effort.
Using Monte Carlo model extension for forward IM calculation avoids excessive outputs for MVA
Credit Suisse has stalled on call to expand XVA remit; others think it would have helped, but disagree on how
Intelligent robots can value complex derivatives in minutes rather than hours
Can a centenarian maths idea speed up the calculation of forward sensitivities?
Differential machine learning produces results “thousands of times faster and with similar accuracy”
Rivals UOB and OCBC enjoy another year of pricing flexibility
CCPs need new tools to scrutinise their members, for everyone’s good health
One clearing member's disproportionately large position increases the credit risk for all CCP members
Banks warn of overly complex revaluation process and heightened risk of backtest fails
Numerix quant presents a model aimed at showing the total cost of a trade
Funding and credit risk with locally elliptical portfolio processes: an application to central counterparties
In this paper, the authors extend the scaling approach of Andersen et al (2017a) from a model driven by Brownian motion to one driven by an arbitrary isotropic Lévy process.
Fast stochastic forward sensitivities in Monte Carlo simulations using stochastic automatic differentiation (with applications to initial margin valuation adjustments)
In this paper, the author applies stochastic (backward) automatic differentiation to calculate stochastic forward sensitivities.
Risk Awards 2019: A glimpse of the future? Quant uses ML to model term structure and crunch margin costs
Quants propose faster technique for Simm-MVA based on algorithmic differentiation
StanChart quant proposes new technique to compute MVA quicker
Algorithmic differentiation are used to simulate sensitivities to calculate MVA
Post-Libor environment and financial crime detection to drive future research, says top quant
Sell-side quants develop machine learning technique to optimise margin costs
Alexei Kondratyev and George Giorgidze apply two evolutionary algos to MVA optimisation
Slow model development and approval processes mean banks yet to see benefits expected under margin rules
Fair value adjustment for initial margin should be reflected in accounting statement