Quant Funds 101 – Part 3

Future Trends of Quants

Quantitative investing is advancing on several different fronts, and the future is likely to see the convergence of various techniques & platforms. Developments in other areas, including the introduction of new investment products and asset classes (cryptocurrencies and tokenized securities for example), will create new opportunities.

The continued globalization of markets will also play a role in the future, as investors can access new markets. The biggest opportunities may lie with AI and Big Data. These technologies, when used together, allow analysts to find relationships between stock prices and data not traditionally used by investors. Satellite images, social media content, and GPS data from vehicles and devices are all potential sources of intelligence.

Sentiment analysis has become a viable solution for quantitative investing. Both AI, ML, and Big Data are being used extensively to model sentiment and its predictive powers. Advances in AI may eventually allow qualitative factors to be modeled. This has been reducing the gap between quantitative and traditional active fund management, by taking more subjective factors into account. With more and more data subjective data being used, predictive analytics are growing more powerful. Therefore, in some cases, this would also make quantitative investing better as quant funds may see some trends that may be reported later to the active fund manager.

Hedge fund managers can use nowcasting models as a part of Quantitative investing. Nowcasting models can assist hedge managers to nowcast the current economic indicators that may have bearing on the performance of the stock portfolio. Further, fund managers can use a predictive nowcasting model to predict the policy responses of the Government and take positions accordingly.

Now that we know the future of quant funds, it would be interesting to see where is in India in terms of quant funds adoption.

Quantitative Investing in India

Quant funds in India have a pretty rough ride, to say the least. The oldest quant fund of India Nippon India Quant Fund was launched as early as 2008. However, the only Indian quant fund has been grossly unsuccessful at beating the benchmark index over both shorter as well longer time horizons. Its underperformance has been majorly attributed to the non-identification of subjective factors like corporate governance while buying the securities.

Also, the Indian markets are at a nascent stage where the family-owned businesses have yet not ceded control to professional management. Therefore, conflicts in family-owned businesses are another factor that the quantitative funds have not been able to capture. Therefore, the returns have lagged the indices.

As per Ashutosh Bhargava, Head of Equity Research at Nippon India Mutual Fund,

“There is no story or a personality of a fund manager to make a sale pitch. When you explain to 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 commissions which they do in regular funds. So, lack of personality, story, and cheap cost work against these products.”

Another argument could be that India does not have savvy investors and, therefore, the concept of Quant Fund has not been popular. The AUM of Nippon India Quant Fund is merely INR 26 crores, which is very low. Underperformance, as compared to the benchmark, has not helped the performance of quant funds either.

However, despite the shortcomings, in 2019, DSP Mutual Fund came up with its quant fund after a long drought of Quantitative Fund NFOs in India. Further, Tata Mutual Funds launched their quant fund in January 2020. The performance of the quant fund category has been mediocre in India. While DSP Quant Fund has been able to beat the benchmark index, Tata Quant Fund has lagged the index.

However, the set of mixed performances did not stop other Asset Management Companies in India to start their own quant New Fund Offering (‘NFO’). Some new players have joined the Quant Fund race in India like ICICI Prudential Mutual Fund launched their quant fund in December 2020 & Quant AMC has recently come up with their Quantamental Fund NFO in April 2021. Quantamental is not exactly similar to a quant fund. The differences between a quant and a quantamental fund are later explained in the article.

Positioning of Quants in India

Due to the efficiency of quant funds in cost savings, the expense ratio of quant funds (1%) is lower than actively managed funds (2%). Quantitative Funds are positioned between the low-cost ETF / Index Funds and the actively managed funds.

 In terms of returns, Quantitative funds in India are positioned above the index funds but lag in their returns below the actively managed categories like large-cap, mid-cap, etc. Therefore, both in terms of returns and the expense ratios, quant funds are placed between actively managed & index funds.

Applications for Quant based investing in India

Quantamental Fund – Used by Quant Mutual Funds

Quantamental strategy combines two types of investment strategies in India i.e. Fundamental + Quantitative Investing. Therefore, quantamental investing combines complex algorithms of the mathematical model and fundamental analysis involving subjective factors. Going quantamental improves the performance of the fundamental investors as it 1) increases the discipline of investing 2) leverages the power of algorithms and models.

In India, Quant AMC has recently launched a quantamental fund that combines fundamental and quantitative investing. The fund uses the Nifty 500 as its investment universe. It applies its quantamental model that includes a predictive set of analytics indicators to shortlist a few securities. From the shortlisted, stocks they apply their VLRT framework that they use for fundamental analysis. Therefore, the quantamental model helps the fund use a quantitative model to reduce the universe of stocks (basis predictive analytics). They apply their stock selection framework to shortlisted stocks to come up with a model portfolio.

Further, as mentioned earlier, purely quantitative funds have not been popular in India. It involves no fund manager whose personality can be used for making a sales pitch. However, with quantamental, the limited involvement of a fund manager + the usage of complex models having a wide coverage can be a pull factor for investors to invest in the quantamental model of investing.

Decision Corroborating Tool

Fund managers can also use quantitative models to corroborate the model portfolio with the existing portfolio. It will help them identify mistakes/biases in their decision-making. It will also help them to verify any securities that they may have missed.

Quantitative analysis has introduced a more scientific and systematic approach to investing. There are several advantages to making investment decisions based on empirical evidence, including lower relative costs and the elimination of emotion from decision making.

A strategy based on a quant model is not a silver bullet, and there is no guarantee of performance, but for the most part, quant funds have a better chance of achieving their objectives. The recent introduction of new products, technologies, and asset classes suggests that there is still a long way to go and the industry will continue to grow and evolve in the coming decade.

Drop a comment or write us an email at info@pirimidtech.com for any feedback about this article. Do check out our portfolio in building Robo advisory, Large Scale Trading Systems, Algo Trading, Stock Sentiments, Price Trends Forecasting, Backtesting frameworks, Credit Model, Open Banking, etc. on our website. Connect with us to discover how our Fintech expertise can help you build cutting-edge solutions powered by AI/ML.

This is a guest post by Yash Surana, who is a CA and an MBA (Finance) from SPJIMR, Mumbai, and loves writing about finance, strategy, startups & Personal Finance.













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