MUTUAL FUNDS: Know the risks associated with quant funds

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June 15, 2021 3:15 AM

Though quant funds operate on the basis of a set of rules and are free from fund manager bias, the method used for stock selection is not transparent

However, fund managers monitor and make minor changes to the model as and when required.

Quant funds are a type of mutual fund, wherein the investing and portfolio construction is carried out with minimal human (fund managers) intervention by using Artificial Intelligence (AI), algorithmic trading, etc. So, to a greater extent, quant funds eliminate the component of human error including emotional and other behavioural biases which normally happens while investing. Let us discuss in detail the mechanics behind quant funds and associated risks and whether investors should have such funds in their portfolio.

Mechanics behind quant funds
Quant funds generally use rule-based investing strategies. Such funds use a variety of tools ranging from established and innovative financial models, algorithms, machine learning, AI, using Big Data, etc., to project future share price and invest accordingly. These rules are developed by fund managers after considering a significant fundamental and technical analysis. But, once the rules are set, there is involvement of the fund manager on a day-to-day basis as these funds will update on their own.

However, fund managers monitor and make minor changes to the model as and when required. Essentially, the models use past data and variables such as trading value, volume, volatility, beta, yield, liquidity, momentum, alpha, correlation, covariance and other multi factor models and look for a pattern so that it can predict the future price.

Associated risks in quant funds

As of now in India, there are six funds—DSP Quant Fund, ICICI Prudential Quant Fund, Nippon Quant Fund, Quant Quantamental Fund, SBI Equity Minimum Variance Fund and Tata Quant Fund that operate purely on quant model and their collective assets under management is worth around `990 crore.

Though quant funds are free from fund manager bias, the method used for stock selection is not transparent as each fund keeps its model ‘proprietary’ and does not disclose it in the public space. Another risk is that these funds’ performance cannot be compared against the benchmark indices like Sensex or Nifty. So, to assess the performance of such funds one should consider S&P BSE 200 or Nifty 200 total return index (TRI) as they will provide a clear picture of the performance.

Whether one should invest?
As such the concept of quant funds is new in India and each of the funds as mentioned above have their own rules. Investors should understand each fund model and assess the benchmark for its performance comparison before investing. Quant funds base their stock selection purely on quantitative data; thus they might miss out action in the stock market owing to qualitative information such as efficiency of the board, business ethics and other intangible factors which are hard to quantify.

Further, these funds are relatively new and do not have a long performance track record to assess their performance and efficiency. So, conservative and moderate risk appetite investors should preferably avoid such quant funds. However, aggressive investors may consider investing a small percentage of their total investment in quant funds as a diversification strategy.

To conclude, quant funds definitely have a great future when technology as well as Indian capital markets develop and mature.

The writer is a professor of finance & accounting, IIM Tiruchirappalli

risks in quant
Quant funds are relatively new and do not have a long performance track record to assess their performance and efficiency
Quant funds base their stock selection on quantitative data. Thus they may miss out action in the stock market owing to qualitative information
Conservative investors with moderate risk appetite should preferably avoid quant funds. Aggressive investors may consider investing a small percentage of their total investment in quant funds as a diversification strategy

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