Amid plenty of mutual funds in the country, there is one category that has failed to catch investor fancy. Quant funds, which are rule-based mutual fund schemes driven by customised statistical models, are 0.01 per cent of overall MF universe with only three funds in the category. While the first quant fund - Nippon India Quant Fund - was launched in 2008, it's only in 2019 that the second fund -- DSP Quant Fund -- joined the fray, followed by Tata Quant Fund in early 2020.
Quant funds fall between the passive and active funds. It has low expense ratio and no human bias like passive funds. Unlike active funds, where fund managers play a role in stock picking, buying and selling happen via algorithms in quant funds. Such funds are quite popular in global markets, but have failed to generate interest in India.
"There is no story or a personality of a fund manager to make a sale pitch. When you explain investors that your money will be deployed based on a mathematical system, it does not enthuse confidence in them. Secondly, there is no incentive for bankers and distributors to push these products because they don't get commission which they do in regular funds. So, lack of personality, story and cheap cost work against these products," explains Ashutosh Bhargava, Head Equity Research and Fund Manager, Nippon India Mutual Fund.
How quant funds work
Each quant model looks for a pattern in the past to extrapolate it in the future, which could either be purely mathematical like in technical analysis or factor-based strategies like value or growth.
"The job of the quant fund manager is to assess whether the pattern observed in past data is persistent i.e it will repeat in the future and thus can be profited from or just a data artifact which has to be ignored," says Gaurav Rastogi, CEO, Kuvera.
Nippon India Quant Fund, which underperformed the market in its initial years, revamped its model recently to boost returns. "Earlier it was a Nifty-based fund, so we were supposed to buy only 20 stocks. Now we buy at least 30 stocks out of BSE-200. The new avatar is broad-based, but still focused on largecaps. It has mainly quality-cum momentum strategies, different from what we used to have in past," says Bhargava of Nippon India MF. On a year-to-date basis, the fund is down 6 per cent compared to 12 per cent fall in benchmark S&P BSE 500 TRI.
DSP's Quant model puts an emphasis on elimination first. It has returned 2.63 per cent in last one year compared to 9.91 per cent fall in S&P BSE 500 TRI. "Our fund avoids highly levered companies, companies with poor quality of reported earnings and the like. This has helped the model outperform the benchmark since the portfolio companies in general have strong balance sheets and thereby better ability to weather a slowdown," says Aparna Karnik, Senior Vice President and Head -Risk and Quantitative Analysis, DSP Investment Managers.
Another aspect that helped DSP was its multi-factor approach that blends quality, growth and value investing styles into the investment process. "We have tried to create an all-weather portfolio, that aims to be relatively immune to the economic cycle."
Tata Quant Fund, launched in January 2020, is an AI-powered and ML-enabled open-ended mutual fund scheme.
What may go wrong in quant funds
Quant fund strategies are based on historical data, so it may not respond well to black swan events like coronavirus-led crash or sentiment-driven rallies. "Since these are driven by quantitative models, there could be some blind spots which may be otherwise picked up by fund managers through a more qualitative lens," says Kaustubh Belapurkar, Director - Manager Research, Morningstar India.
Quant models that rely on artificial intelligence (AI) and machine learning (ML) face another hurdle. "If the machine has not witnessed an event in the past or has neither been fed with information about it, it will not be able to account for the same in its future predictions," points out Tarun Birani Founder and CEO TBNG Capital Advisors.
Besides, since quant fund managers back-test their models on the past data, there is every possibility that it may not perform the same in the future. "Do not invest just because the back test looks good. Investors have burnt their hands chasing such fictitious returns quite often. So, investors with a certain level of sophistication in evaluating and understanding statistical significance should invest in quant funds," cautions Rastogi of Kuvera.
Should you invest?
Quant funds should be analyzed based on the investment model that they follow. However, since these are at a nascent stage in India, it is difficult to find a differentiator. "Data is the fuel here as the entire model is constructed based on historic data and every model is likely to face a scenario or an unanticipated event where it might not function as expected," says Birani.
Birani says whichever fund an investor chooses, he must build exposure to it in a staggered manner. "At the moment it is difficult to pinpoint a specific fund as we barely have any history or time period to analyze its performance against. However, since the human emotion quotient in investing is out of equation, this becomes an interesting strategy for long term investors."
Belapurkar of Morningstar India says if the underlying model of a quant fund fits well in an investor's portfolio, typically up to 10 per cent of the portfolio in quant funds could be suitable.
Why choose quants funds over passive or active funds
Undoubtedly, low-cost passive funds are best for conservative investors who do not seek market beating returns. However, if you wish to diversify beyond index funds, but do not want exposure in high-cost active funds, you may choose quant funds. Bhargava says with every sector facing disruption quite often now, it has become difficult for even experienced fund managers to have a medium to long-term view on the market, thus alpha is shrinking. "That's where you need objective rule-based system which simplifies the job, and makes the process repeatable. Investors are right in asking for alpha when they are paying 2.5 per cent fees. That is becoming a challenge."
Quant funds may not have progressed in India yet, at least low cost index funds and ETFs have piqued investor interest. "Globally also, ETFs progressed first and smart beta quant funds came later. so, if you believe ETFs are future, quant and smart beta products will also follow suit," says Bhargava.
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