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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
You don’t need to sacrifice accuracy for flexibility
BAML quant proposes option pricing model that softens conflict between the two properties
Doing well by doing good
Drug approval swaps and megafunds can channel capital towards world’s greatest problems, writes MIT’s Lo
Podcast: Dominique Bang on his stochastic local vol model
New approach delivers quick and accurate computation of prices
How replication simplifies pricing of vol exotics
Barclays quants replicate knock-out corridor swaps using barrier options in bid to make pricing easier
All the news that’s fit to print
While the benefits of the information revolution are clear, the risks it brings should not be underestimated, says Andrew Lo
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
Financial risks don’t go on holiday
Better mapping of financial system would help avoid seasonal surprises, argues Andrew Lo
Podcast: SocGen quants on exotics calibration, machine learning and autocallable pricing
Deep learning techniques are being explored by the quants to speed up exotics pricing
How old calibration techniques can be applied to exotics pricing
SocGen quants propose technique to more accurately calibrate exotic options
Podcast: Lo on adaptive regulation, machine learning, bitcoin
MIT quant says next project will be to combine behavioural science with tech such as machine learning
Swaptions vol modelling tweak opens up pricing possibilities
Nomura quant proposes local volatility model that can directly calibrate to swaption smiles
If regulations don’t bend, they’ll break
Financial regulation should be adaptive, not reactive, argues Andrew Lo
Podcast: Richard Martin on EM debt, copulas, machine learning
Quant sceptical of machine learning algos and black boxes
How machine learning could aid interest rate modelling
Standard Chartered quant proposes machine-learning technique to better capture rate dynamics
Model risk in the transition to risk-free rates
Transition is an opportunity to reduce multi-rate complexities, say Bakkar and Brigo
Podcast: Quantum computing to boom in next three to five years
Quant speaks of collaboration with Nasa and machine-learning algos for yield curves
Putting swaptions pricing in the fast lane
Derivatives consultant proposes a model for arbitrage-free pricing
Simple models won’t cut it for systemic risk
Understanding interconnectedness and capturing it within models is a key challenge, say quants
Podcast: Roos on swaptions arbitrage and benchmark reform
Benchmark reform means additional work for rates quants
Podcast: Fries on Monte Carlo, Greeks and the future of AAD
Research on AAD is not complete until it becomes easier to implement, says quant