Podcast: Damiano Brigo on derivatives, AI, machine learning and more

Genuine artificial intelligence remains "very, very far away", says Imperial College's Brigo

Damiano Brigo (left) and Mauro Cesa, Risk's quant finance editor

In February, we welcome professor Damiano Brigo, chair of mathematical finance at Imperial College London, as an occasional Risk.net columnist. For this podcast – the first of a monthly series – Brigo visited our office to share his thoughts on the lost causes, current role and future prospects of quantitative finance.

The derivatives market, he says, “has moved from having complex payoffs in a simple system on to simple payoffs in a complex system”, and the models needed in this new environment are still being studied. Elsewhere, quants’ expertise is being applied in a number of newer areas such as risk optimisation, development of machine learning algorithms or analysis of the impact of central clearing on markets.

Brigo sees machine learning and data science having a big impact in finance, but is sceptical of the near-term prospects for artificial intelligence: “We are still very far from a real intelligence and human-like thinking,” he says. Rather, voice recognition, chess and other game-playing applications, or interactive software that is able to answer questions, are simply examples of sophisticated statistical algorithms.

He also explains how the UK government’s plan to change its funding policy for academic research will incentivise projects that have more of an impact on society.

To hear the full interview, listen in the player above, or download. Future podcasts in our Quantcast series will be uploaded to Risk.net. You can also visit the main page here to access all tracks or visit the iTunes store.

Further reading

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