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Risk.net Volatility and machine learning were among the top research areas for quants this year Perhaps fittingly in a year of unexpected turbulence, Risk.net’s Cutting Edge section published a flurry of papers on volatility modelling in 2020. Among them was a pair of solutions to a problem that has baffled quants for more than a decade – the joint calibration of S&P 500 and Vix options. Julien Guyon, a senior quantitative analyst at Bloomberg, performed the calibration with a discrete-time optimal transport model, which, according to the Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content. ....