Scott Treloar: Skiing in Singapore and how to quantify investor skill

In this episode of the Curious Quant podcast series, I sit down with Scott Treloar from Noviscient where we look at the shape of the hedge fund industry and talk about how to create better systematic allocation to funds using machine learning techniques. Reflecting back on his career at Deutsche Bank in Asia and running a statistical arbitrage fund, we discuss the pragmatic applications of quantitative methods and the use of AI in society. He makes some excellent observations.

The future of asset management:

“What I think needs to be happening is to use machine learning and AI not just to improve operational efficiency and lower your cost, but actually to introduce new business models into the industry.”

The human problem:

“These new algorithms, big data and computing capabilities that enable new business models is obviously the big opportunity, but it runs into the human problem, vested interests and uncertainty around the industry.”

The need for human skill:

“You need innovative humans, at least at this stage, to be involved, to bring market and product understanding and some innovation about where the opportunities may be.”

You can download the podcast from the Apple and Spotify podcast players or listen below:

 

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Super system on the inexorable path towards ten mega-funds

With the super industry facing into headwinds that raise the floor on minimum scale and increase complexity, the pressure towards further consolidation should ultimately prove unstoppable, and a natural end-point could be ten mega-funds over $200 billion in size managing more than 90 per cent of system assets. The path to that destination, however, could be bumpy.

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