Are Quant Funds Worth The While?
In this article, we will focus on defining quant funds, how they work and whether or not you should have them in your investment portfolio.
Globally, quantitative investing is picking good pace. India is also not behind and we have seen around four quant fund launches in a matter of one year. What is that which makes it so trending? The following example will help you to comprehend the trend better. There is a fund that delivered more than 66 per cent annualised return before fees and 39 per cent after fees over a horizon of 30 years from 1988 to 2018. This is the Medallion Fund, managed by James Harris Simons, the founder of Renaissance Technologies, who has earned the name of being the best money manager on earth for delivering such a spectacular performance.
The said fund is currently open only to employees of Renaissance Technologies and a few other people connected to the firm. It is interesting to know that this firm uses mathematical and statistical methods in order to create and manage its portfolio. Here they apply computer models and algorithms along with other vast sets of data to predict future prices of a particular security. Moreover, it eliminates the human error in security selection by keeping behavioural biases at bay which affect the performance of the fund in some or the other way. That said, one should never forget that these quant models are themselves designed by humans.
Defining Quant Funds
Quant funds are mutual fund schemes that adopt rule-based investing for short-listing and designing a portfolio of stocks. Such funds have a minimal role of a fund manager as they apply a number of pre-determined filters for picking stocks. Here the role of the fund manager is to review the model annually and tweak it, if necessary.
According to a study by Morningstar in 2015, 65 per cent of the alpha comes from exposure to broad market factors such as value, momentum, yield, volatility, liquidity and size – these are primarily quantitative factors – whereas the remaining 35 per cent comes from stock selection – fundamental analysis and human judgment. At present there are five funds in India that operate on a quant model having collective assets under management (AUM) of Rs 960 crore as on April 2021.
Working of Quant Funds
A quant fund usually works on a model that looks for a pattern in the past to extrapolate it in the future. This could purely be mathematical like in technical analysis or it can even adopt single factor, bi-factor or multi factor-based investing strategies like value, low volatility, alpha, momentum, high beta, etc.
And it is the job of the fund manager to assess the relevance of the assessed pattern and whether or not the pattern observed in past data is persistent enough to repeat in the future and is not just a data artefact which needs to be ignored. Let us take Nippon India Quant Fund, for instance. This is the oldest quant fund that we have so far, whose inception is dated April 2008. In the initial years, this fund underperformed the benchmark. However, it revamped its model that has certainly helped it to generate better returns. Initially, Nippon India Quant Fund was benchmarked against Nifty 50 Total Returns Index (TRI), and hence it used to invest only in 20 stocks from its universe. But recently it has changed its benchmark to S & P BSE 200 TRI and now invests in a minimum of 30 stocks from S & P BSE 200 TRI.
Even though now it is broad-based, it is still tilted more towards large-cap and mid-cap stocks. It chiefly adopts the combination of quality and momentum factor-based investment strategies. Moreover, in case of DSP Quant Fund, its model has an emphasis on elimination first. This fund avoids investing in companies that are highly leveraged, having poor reported earnings and the like. However, apart from this, DSP Quant Fund does adopt a multi-factor approach that blends quality, growth and value investing factors into its investment process. Talking about the recently launched Tata Quant Fund, it is a machine learning and artificial intelligence (AI)-powered scheme.
Performance
As we have learned in the above paragraphs, despite being a quant fund, these funds are fundamentally different as they run on their own model, which is different from others. Therefore, it makes no sense to compare them with each other as it won’t be an apple-to-apple comparison. However, we have one thing in common here, which is their benchmark. All these quant funds are benchmarked against S & P BSE 200 TRI. So, in order to evaluate any such fund’s performance, we would be comparing its one-year, three-year and five-year trailing returns as against the benchmark. Moreover, we would also be comparing such funds in terms of risk with category as well as the benchmark.
As we can see, in none of the periods did the quant funds beat the benchmark. However, we should not just look at returns but also the risk undertaken by funds.
When it comes to overall risk, Nippon India Quant Fund and DSP Quant Fund seems to take less risk compared with Tata Quant Fund and even with low risk in a one-year timeframe, DSP Quant Fund and Nippon India Quant Fund posted better returns than Tata Quant Fund.
Conclusion
Since quant funds are at a nascent stage in India, they need to be analysed based on their investment models. Presently, it is difficult to recommend one specific fund as we hardly have any history to analyse its performance in a holistic manner. Typically, conservative to moderate investors should avoid investing in them. However, aggressive investors can do so from a diversification perspective. However, we would suggest that you should not allocate it to your core portfolio but can include it in your satellite portfolio. Moreover, quant funds need to be analysed based on how they select securities. As of now, mostly we see them adopting factor-based investing strategy. Though, they have been tried and tested globally, in India they are still new. So, invest in them only in staggered manner and any such fund should not form more than 10 per cent of your satellite portfolio.