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Quant funds use advanced statistical, mathematical, and computational techniques to identify investment opportunities. They select from a predefined universe without any human intervention.
In this type of investment, the fund houses employ algorithms that process vast amounts of data to take decisions about the securities, asset allocation and risk management.
Currently, there are 8 quant funds in Indian MF industry. These funds have total AUM of around Rs. 6300 crore. Comparing the three years return among these 8 funds, 5 funds beat their benchmark returns by comfortable margins while two funds underperformed compared to the benchmark return in three year period. One fund did not have three year track record.
Key features
- A data-driven investment approach using historical data, market trends, and predictive analytics to eliminate emotional or subjective biases
- The fund houses have their own pre-programmed algorithms to take investment decisions based on specific conditions
- The decision-making algorithms in the quant funds can be designed as per the investment goals like capital appreciation, wealth generation or risk mitigation
- Quant funds often include wide range of securities to spread the risk of the fund
How do they invest?
- The algorithms in the quant funds are based on factors like value, growth, momentum, or volatility
- These funds balance long and short positions to reduce market risk
- The algorithm allows the managers to choose high-frequency trading that is based on short-term market inefficiencies
Advantages
- Quant funds are focused on objective decision making based on data and predefined rules. They eliminate human biases like overconfidence, fear, or greed
- These funds take investment decisions as per the digital calculation which can help identify the opportunities that might be overlooked by human analysts
- Clear rules and mathematical methodology help the investors to have a understanding about the operation of the fund
Risks and limitations
- The risk of model may also reflect in the overall fund performance as the algorithms are trained on the historical data which may not be bias free
- Excessive reliance on data is not useful in predicting or hedging against the developing trends in the market
- Investment models and their algorithms are complex set of rules, they may not be easy for the retail investors to understand
- Quant funds are mandated to churn or trade only at specific times making it difficult to adjust to rapidly changing market conditions
Who should invest?
- Quant funds are optimal investment option for those who are tech savvy and believe in data driven approach of investment
- Investors who are comfortable in understanding the complexities of quantitative models
What does the future holds?
The example of US market can be quoted to show the importance and relevance of quant mutual funds in maturing markets. Till 1989, the assets under management under quantitative approach-based funds were non-existent but today these funds manage 35% of total AUM in US markets.
Although the total AUM in Indian MF industry has crossed Rs.68 lakhs but the quant funds cover only around 1.5% of total AUM. This along with the continuous maturing of Indian markets will result in further growth in such investment options.
Further, the prevalence of artificial intelligence and large language models will also increase the acceptance of this category of investments.
