Quant screens a tonic for thematic robos

17-Mar-2017

By Leanne Abbas

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Quantitative screens can increase returns from thematic robo-advice portfolios using two distinct approaches to building indices, according to a new whitepaper from wealth management software provider Quantifeed.

The firm’s ‘Designing thematic indices with a quantitative factor’ report suggested that based on empirical research of past investment performance, robo advisers could boost returns on their model portfolios by selecting securities based on both investment themes and factor indices.

The fintech’s senior quantitative strategist and author of the paper, Gaudi Schneider, said while the thematic indices approach was based on a forward-looking growth story for a niche industry, the factor indices approach used quantitative variables, including volatility, yield, size and momentum.

“At Quantifeed we believe that through a calculated combination of both, financial institutions can deliver a much better risk-adjusted performance,” he said.

Quantifeed’s senior executive for strategic partnerships on Australia Graeme Brant told financialobserver that while quantitative screens were designed to enhance performance, they should not be used as a substitute for robo advisers’ existing stock selection processes.

“Quantitative screens can add a lot of value to portfolio performance, but they are not a panacea that should be applied to all portfolios,” Brant said.

“At Quantifeed, we believe that the risk-return profiles of thematic indices can be enhanced by combining traditional selection with factors and other quantitative metrics.”

Brant also noted that many of the portfolios Quantifeed had developed for its clients across Asia had a quantitative screen applied in their construction, providing them with the option to remotely service their clients, while promoting growth within portfolios.

One way of introducing a factor to a thematic portfolio is to assign weights to securities based on a specific variable, for example, volatility, instead of the standard weights based on market capitalisation, according to Schneider.

“Low volatility stocks have been shown to outperform higher volatility stocks over extended periods of time,” he said.

“Taking advantage of this phenomenon can be achieved by giving stocks with low volatility a greater weight in the portfolio. We call this inverse volatility-weighted.”

In order to test the theory, the paper revealed Quantifeed looked at a group of US listed companies that were commonly used in robo portfolios.

It found that by applying a particular quantitative factor to this group of stocks, a portfolio could outperform the S&P 500 index by 11 per cent over a three-year period between February 2014 and February 2017.

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