Credit Suisse has launched its US Systematic Alpha Equity Fund to exploit market inefficiencies by combining a quantitative stock selection model with actively managed event-driven strategies. This serves to diversify the risk profile of the portfolio and exploit return opportunities, says Credit Suisse.
The CS US Systematic Alpha Equity Fund has been created by converting the CS Transatlantic Fund and reducing the annual management charge from 1.5% to 1.25% on the retail share class. “We have recognised for some time that the CS Transatlantic Fund has been underperforming and that it was time to take action,” says Toby Hogbin, director, product management, Credit Suisse’s Asset Management business.
The fund combines the advantages of passive and active fund management, taking expected risk and return into consideration simultaneously during portfolio construction, according to Credit Suisse. “The efficiencies in the US market make it hard for large-cap active managers to beat the index consistently so we believe a ‘systematic alpha’ type of management, which combines quantitative and active strategies, offers an effective way of managing large-cap- biased US equities going forward,” says Hogbin. “The new Fund has been rigorously back-tested to make us confident in the ability of the Fund to meet its investment objectives,” he adds.
Under the new investment process, the quantitative stock selection model identifies factors that forecast equity returns over multiple market and style cycles. The team reviews the efficacy of any one factor’s ability to identify the winners and losers over a long period of time and multiple market cycles. They also study the economic rationale of factor performances as well as the factors’ correlation with the broad market, the value/growth cycle and size cycle.
The model categorises stocks into the following sector groups: Cyclicals, stable growth, technology, financials, and energy and utilities. This reduces structural bias in the portfolio modelling, says Credit Suisse. Low correlation between the sector groups improves the potential performance and consistency of the overall model.