Margin valuation adjustment (MVA)
New developments in XVA: bank strategy in a changing world
Derivatives valuation has grown in complexity since the the financial crisis that began in 2007–08. It now encompasses a broader range of risk factors, including credit, funding, margin and capital – all of which can affect banks’ competitiveness and…
Is stochastic cross-currency basis a better way to model IM?
Using Monte Carlo model extension for forward IM calculation avoids excessive outputs for MVA
After Archegos, a bigger role for XVA desks?
Credit Suisse has stalled on call to expand XVA remit; others think it would have helped, but disagree on how
Deep XVAs and the promise of super-fast pricing
Intelligent robots can value complex derivatives in minutes rather than hours
A look at future exposures, through a 19th century lens
Can a centenarian maths idea speed up the calculation of forward sensitivities?
Danske quants discover speedier way to crunch XVAs
Differential machine learning produces results “thousands of times faster and with similar accuracy”
Initial margin delay disadvantages DBS
Rivals UOB and OCBC enjoy another year of pricing flexibility
Small, speculative clearing members – are they worth the risk?
CCPs need new tools to scrutinise their members, for everyone’s good health
One bad apple: default risk at CCPs
One clearing member's disproportionately large position increases the credit risk for all CCP members
European FRTB proposals spark XVA overload fears
Banks warn of overly complex revaluation process and heightened risk of backtest fails
Podcast: McClelland on why you need a good MVA model
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.
Quant of the year: Alexei Kondratyev
Risk Awards 2019: A glimpse of the future? Quant uses ML to model term structure and crunch margin costs
Is AD the answer to quicker MVA calculation?
Quants propose faster technique for Simm-MVA based on algorithmic differentiation
Podcast: Antonov on MVA, algorithmic differentiation and model validation
StanChart quant proposes new technique to compute MVA quicker
Efficient Simm-MVA calculations for callable exotics
Algorithmic differentiation are used to simulate sensitivities to calculate MVA
Podcast: Mercurio on Libor, fraud and writing models on a plane
Post-Libor environment and financial crime detection to drive future research, says top quant
Machine learning is not just for the buy side
Sell-side quants develop machine learning technique to optimise margin costs