A strategy long used by hedge funds draws increasing investor interest
Quantitative or quant investment strategy has become a buzzword in the asset management world, thanks in part to the success of quant funds in 2018, when major stock markets tumbled.
Although quant funds overall registered a decline last year, the best performing quant funds significantly outperformed the best performing conventional funds.
According to Investopedia, Odey Asset Management’s Odey European fund and Northlander Advisors’ energy-focused Northlander Commodity fund gained over 50% in 2018 and were the top performing quant funds of the year. The two asset managers are based in London. Meanwhile, the best performing conventional fund, US asset manager Baillie Gifford’s American Fund, gained 22.07%.
Understanding the strategy
The quant investment strategy, which some refer to as systematic investing, is an approach that uses advanced mathematical modelling, computer systems, and data analysis to calculate the optimal probability of executing a profitable trade. They are typically run by highly educated teams that use proprietary models to increase their ability to beat the market.
The quant strategy isn’t new as hedge fund managers have been using it widely for decades. But despite rising investor interest, there are still some misconceptions about the strategy, according to Anthony Lawler, co-head of GAM Systematic at Zurich-based asset manager GAM Investments.
He says quant strategies are often seen as “complex, opaque and lacking human intuition”.
“In fact, systematic investing can be, and typically now is, highly transparent with rule sets that are straight forward to understand. Systematic investing is at its core simply a (written) rules-based and evidence-driven investment approach,” Mr. Lawler tells Asia Asset Management. “That is what the quantitative algorithms are – investment rules operating analytics in real time on large data sets.”
He says the strategy may be seen as complex because “it can operate across very many markets instantly” but “at core, the approach is following simple clear rules, just on a large scale and in real time”.
GAM had 137.4 billion Swiss francs (US$136.75 billion) of assets under management as of end-March 2019, with around $4.5 billion of that amount coming from GAM Systematic.
Hanqing Tian, deputy general manager and quantitative portfolio manager at Chinese quant manager Huatai-PineBridge, says quant strategies have been considered “one of the mainstream investment approaches for capturing alpha” across the US and other major global markets.
But it’s still relatively new in China where investors only began to recognise the value of quant investing in the A-shares market over the last five years. According to Ms. Tian, one of the reasons for the growing interest is that quant investment managers were able to generate “persistent performance and alpha due to the idiosyncratic characteristics of the China market that support quant and factor investing”.
“As a result, a number of China-focused quantitative strategies with three to five years’ track record have been doing very well compared to fundamental strategies in the market,” she says.
Investor education is also helping to drive interest in the strategy. “As a result, we have been seeing greater adoption by institutional investors, who have started to shift to quantitative strategies as part of their China allocation approach,” Ms. Tian says. “At the same time, onshore retail investors have also started to see the benefits of quantitative strategies for both short- to mid-term market timing as well as long-term investments.”
Huatai-PineBridge is the largest active quant manager in China, with over US$3.2 billion of quant assets under management at the end of March. The company, which is based in Shanghai, is 49% owned by US asset manager PineBridge Investments, 49% by Nanjing-based Huatai Securities, and 2% by conglomerate Suzhou New District High-Tech Industrial Co Ltd.
Ms. Tian says almost 80% of the company’s quant assets are from onshore institutional investors, including insurance companies and commercial banks. “In recent years, we have received a number of large mandates from institutional clients in strategies that are benchmarked to the CSI 300 or CSI 500 total return indexes,” she adds.
According to Mr. Lawler, institutional investors typically seek a risk-reward profile and are not looking specifically for a systematic investment or a discretionary investment.
“We see growing interest in quant approaches from institutional investors because the risk-reward profile can be helpful to their portfolio outcome needs. Systematic strategies can often exhibit low correlation to traditional asset classes and to traditional investment styles,” he says.
Quant investing’s “robust” risk management is another attractive feature of the strategy.
“This approach will never ‘fall in love with a trade’ or make an exception to a risk limit. The risk management is unbending. Large institutions are also drawn to customisable strategies which can be tailored to best complement a client’s portfolio need,” Mr. Lawler says.
According to Ms. Tian, the challenges for greater adoption of the quant strategy lie in two areas. One is that it’s still a relatively new concept compared to conventional, fundamental-based strategies, and requires more investor education.
The second challenge is the longer time frame of the strategy. “Investing time horizons for many local institutional investors are still very short-term driven versus the longer-term focus for quantitative strategies,” she says.
Still, as far as Mr. Lawler is concerned, it won’t be surprising if there comes a time when allocations to the strategy outweigh conventional strategies. He says there is already “a move afoot for investors diversifying away from their historic dependence on discretionary stock pickers”, which has led to flows into systematic strategies and passive investments.
“There is room for each of these – passive, discretionary stock pickers and systematic approaches – in a portfolio because of the diversification benefit,” he explains.
He believes quant strategies and stock-picking skills are complementary. “Quant approaches are good at having a small edge over a very large universe of names, while the skilled discretionary manager can have a large edge on a very small universe of names,” he says. “Those can be complementary to own together for an investor.”