Views
An ‘optimal’ way to calculate future P&L distributions?
Quants use neural networks to upgrade classic options pricing model
Podcast: turbo-charging derivatives pricing
Quants achieve more speed by reducing number of dimensions in price calculations
Machines can read, but do they understand?
A novel NLP application built on a Google transformer model can help predict ratings transitions
Podcast: NYU’s Kolm on transaction costs and machine learning
TCA methodologies that ignore partial fills “might be off by 20% to 30%”
Podcast: Colin Turfus on short-rate models and Libor’s end
Deutsche Bank quant proposes a lean model to quickly produce benchmark prices
Derivatives pricing starts feeling the heat of climate change
Quants find physical and transition risks can lead to significant rise in CVA
Podcast: Claudio Albanese on how bad models survive
Darwin’s theory of natural selection could help quants detect flawed models and strategies
The case for reinforcement learning in quant finance
The technology behind Google’s AlphaGo has been strangely overlooked by quants
Synthetic data enters its Cubist phase
Quants are using the theory of rough paths to distil the essence of financial datasets
Podcast: Piterbarg on medians and machine learning
How the Libor transition inspired NatWest quant’s latest paper on exotic derivatives valuation
Podcast: Hagan on convexity, volatility and the London Whale
Ex-JP Morgan quant discusses his latest work and the risk failures that cost the bank $6bn in 2012
Podcast: Barclays’ Ben Burnett on how banks can implement HVA
New valuation adjustment may lead to more efficient management of derivatives books
A look at future exposures, through a 19th century lens
Can a centenarian maths idea speed up the calculation of forward sensitivities?
Podcast: Richard Martin on improving credit migration models
Star quant proposes a new model for predicting changes in bond ratings
Put options power up variable annuities
Insurance quants increase risk-adjusted profits using novel hedging technique
As machines disrupt investing, people still have a role to play
Despite AI’s growth, investing still needs human adaptability and judgement, writes Schroders’ Lim
My kingdom for the right copula
Copulas can still deliver if chosen with due attention to intuition and data, says quant fund chair
Putting the H in XVAs
Barclays quant proposes methodology for factoring hedging costs into derivatives valuations
Setting boundaries for neural networks
Quants unveil new technique for controlling extrapolation by neural networks
Random matrix theory provides a clue to correlation dynamics
A growing field of mathematical research could help us understand correlation fluctuations, says quant expert
Degree of influence: volatility shakes markets and quant finance
Volatility and machine learning were among the top research areas for quants this year
A step closer to the perfect volatility model
Research on ‘rough volatility’ gives fresh insight into financial fluctuations, quant expert explains
Breaking barriers in options pricing
A new technique for pricing exotic options unifies two classic models
Whales or minnows? Sizing up crowded trades
Strategies for measuring crowding in trades can help to avoid its effect, writes quant fund founder