
Podcast: CFM’s Bouchaud on agent-based models and ESG investing
Hedge fund quant, and Risk.net’s new columnist, shares his unique take on markets

In this episode of Quantcast, Jean-Philippe Bouchaud, chairman of Paris-based quant hedge fund Capital Fund Management, talks about agent-based models, sustainable investing and liquidity shocks.
As he explained in the first of a series of columns he is writing for Risk.net, Bouchaud is unsatisfied with standard quantitative models, viewing them as oversimplified and ill-suited to spotting tail events, or black swans, in complex markets.
He is increasingly drawn to agent-based models (ABMs) – a simulation technique that creates a synthetic system where agents interact with each other following a set of rules. Such models can better reflect the complexity of markets and serve “as a scenario generator” for risk managers, alerting them to risks standard models might miss.
“They are able to open your eyes on things that you wouldn’t have imagined possible,” he says.
Bouchaud believes the versatility of ABMs, coupled with technological advances that make them more accessible, will lead to their broader application in finance.
He also previews some other topics he will cover in upcoming columns. He argues that hedge funds are not responsible for liquidity shocks in the market, noting that the industry consists of players that contribute liquidity as well as others that absorb it.
Bouchaud also explains his positive view of environmental, social and governance (ESG) investments, even though the lack of historical data makes it difficult for quants to build and back-test reliable ESG strategies.
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 go to the iTunes store or Google Podcasts to listen and subscribe.
Index
01:40 Intro to systematic hedge fund Capital Fund Management
05:25 Agent-based models
23:05 Hedge funds and market liquidity
31:26 Machine learning functions at CFM
36:15 Next challenges for systematic funds
42:55 Dealing with ESG investments
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