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Three adjustments in calibrating models with neural networks
New research addresses fundamental issues with ANN approximation of pricing models
Outsmarting counterparty risk with smart contracts
A digital transaction system developed by quants at DZ Bank could slash margin costs for derivatives
No silver bullet for AI explainability
No single approach to interpreting a neural network’s outputs is perfect, so it’s better to use them all
Small, speculative clearing members – are they worth the risk?
CCPs need new tools to scrutinise their members, for everyone’s good health
Degree of influence: Regulatory policies drive quantitative research
Counterparty risk and market risk hold centre stage, data science moves up, quantum computing debuts
Hedging rate exotics, Bergomi-style
New paper by Nomura quant applies volatility model used in equities to exotic rate hedging
Quants bring ‘triptych’ of variables to risk measurement
Risk and portfolio managers at La Francaise and LFIS are squeezing more information out of stress tests
Game theory plays well for capital management
Barclays quants use Shapley method to optimise capital allocation
Backtesting expected shortfall: mission accomplished?
A rigorous backtest for ES cannot exist, but a good approximation might do the job
Fishing for collateral with neural nets
SocGen quant uses deep learning technique to optimise collateral substitution
No forward-looking rates? No problem
A commonly used quant model could be the answer to the replacement of forward-looking Libor
Podcast: Gregory and Chung on wrong-way risk modelling
Quants discuss a better way to model wrong-way risk
Podcast: Hans Buehler on deep hedging and harnessing data
Quant says a new machine learning technique could change the way banks hedge derivatives
Podcast: Venturelli and Kondratyev on quantum annealing
Authors show how quantum theory could aid portfolio construction
Podcast: Hong on quanto derivatives and Asia’s quant drought
Credit Suisse quant talks about new paper on valuing quanto options
SA-CCR may need more fundamental fixes
Quants propose tweaks to improve Basel counterparty credit risk framework
Podcast: Mathieu Rosenbaum on the rough Heston model
Combination of rough volatility and the classical Heston model gives promising results
Will the Nasdaq default spur CVA for CCPs?
Quant proposes model to calculate bank credit risk exposure to CCP
Podcast: Mercurio and Henrard on the impact of Libor reform
Some derivatives products will become more complex if there are no forward rates, say quants
Could machine learning improve CVA and IM calculations?
Banks have built ways to calculate CVA more quickly, but neural networks could offer more accurate method
Podcast: Princeton’s Carmona on the future of quant education
Course director discusses machine learning explainability and reclaiming game theory from economists
Calling out autocallable pricing
Quants show popular autocallable pricing technique has a flaw that has been ignored until now
Podcast: Kenyon and Berrahoui on the pitfalls of PFE
Quants propose replacement to existing credit risk measure
Degree of influence: are machines starting to learn finance?
This year's analysis recognises a turning point in machine learning applications