As the landscape of investment strategies evolves, quantitative investing has been gaining significant traction for its data-driven approach to stock selection.
On the Indian General Election result day (June 4), market volatility surged, with the India VIX spiking more than 25 per cent in a single day. Such extreme swings often trigger human emotions of greed and fear, affecting decision-making.
Quant-based funds mitigate this emotional bias by minimising human intervention and adhering to back-tested, validated models. The latest entrant to this space is the Aditya Birla Sun Life (ABSL) Mutual Fund.
The ABSL Quant Fund, open for subscription until June 24 with a minimum investment of ₹500, joins nine other quant funds in India, which collectively manage around ₹6,000 crore.
Let’s explore what the Aditya Birla Sun Life Quant Fund offers.
Investment Strategy
Quantitative funds, typically, employ single- or multi-factor models to refine their investment scope, transitioning from broad indices to tailored portfolios based on factors such as fundamentals, technicals and risk measures.
The ABSL Quant Fund differentiates itself with a unique stock selection process.
Unlike other quant funds, it begins by selecting the top 75 stocks from each of the top 15 asset management companies, provided they have at least five years of history and substantial equity assets, narrowing the universe to around 200-250 stocks.
Focusing on the large- and mid-cap space, the fund first eliminates small-caps and those with abnormal past returns and then applies quality and momentum factors. Finally, stocks in the bottom two quintiles with lower revisions in estimates (like EPS and EBITDA) by sell-side analysts are excluded, resulting in a final portfolio of 40-50 stocks.
Regarding stock weightage, constituents are weighted based on lower volatility, with no stock exceeding a 5 per cent weight, similar to an equal-weighted index. While model signals primarily guide sell decisions, occasional fund manager intervention will occur during black swan events like the Covid-19 pandemic.
Benchmarked against the Nifty 200 TRI, the ABSL Quant Fund will be managed by Harish Krishnan and Dhaval Joshi.
The fund will invest a minimum of 80 per cent of its net assets in equity and equity-related securities selected based on the quant model theme. It should be noted that Harish Krishnan previously managed the Kotak Quant Fund, launched in August 2023.
The fund also aims to diversify through overseas investments, potentially enhancing returns by tapping into markets with strong economic growth or undervalued assets, limited to a maximum of 20 per cent of net assets.
Importantly, the scheme may also invest in equity and equity-related instruments outside the quantitative model.
Other funds
There are nine actively-managed funds exclusively focused on quant-based investing as a theme with the benchmark being either S&P BSE 200 TRI or Nifty 200 TRI.
While SBI Equity Minimum Variance Fund (benchmarked to Nifty 50 TRI) strictly doesn’t follow any proprietary quant models, it aims to minimise volatility through a blend of risk and factor-based parameters such as portfolio volatility, correlation and covariance.
Nippon India Quant and DSP Quant are two funds that have been in existence for more than five years.
While most funds, except DSP and Tata, outperformed their benchmarks over the past year, only Nippon India Quant and Quant Quantamental funds have generated alpha over a three-year period.
Significantly, only the Nippon fund has consistently outperformed across all three timeframes. This indicates that despite the sophisticated ‘quant’ strategies, the category has not universally delivered superior returns.
Additionally, it is important to note that quant funds typically exhibit higher portfolio turnover compared to other diversified equity funds.
Our take
Globally, quantitative strategies have demonstrated considerable success, with some of the largest hedge funds, like the Medallion Fund of Renaissance Technologies founded by Jim Simons, following quant-based investing.
In contrast, quant thematic mutual funds in India are still in their infancy, representing less than 1 per cent of total equity assets under management (AuM).
While quant-based mutual funds offer the potential for high risk-adjusted returns through sophisticated data analysis, they also come with significant risks stemming from model limitations, market changes, data issues and execution challenges.
Although the back-tested results of the ABSL Quant Fund appear promising, its performance in real-time market conditions remains to be seen.
Should the fund establish an exceptional track record in the foreseeable future, it could be a valuable addition to an investor’s portfolio.