Gaining Traction: Understanding Quant Funds

Quant-based funds or quantitative funds have gained traction recently in India. Basically, quant funds involve a mix of active and passive investing in mutual funds.

The stock selection and investment decisions are undertaken following a rule-based approach to statistical and mathematical models.

The fund manager’s ability to pick stocks while forming a portfolio is not relied upon completely. However, they are often involved in the design and monitoring of the portfolio.

Artificial intelligence (AI) and machine learning (ML) approaches are adopted for fund management. As human interference is minimal in the selection of funds, bias-free investing is assured.

Generally, quant funds are classified based on quantitative factors such as value, momentum, yield, volatility, liquidity and size or statistical measures in the model.

The quant fund follows single-factor or multi-factor-based models in India. Single-factor models are represented as ratios such as price-to-earnings (P/E), price-to-book (P/B), and so on. The model evaluates the quality as well, using return on equity (ROE) and return on capital employed (ROCE). Statistical phenomena such as volatility using standard deviation or beta are also studied.

On the other hand, the multi-factor model approach looks forward to combining two or more factors that seek to deliver better risk-adjusted returns more consistently over a period.

Most quant funds are present in alternative investment vehicles, including portfolio management service (PMS) and alternative investment funds (AIF).

Considering that quant funds adopt specialised techniques for investment selections, seasoned investors who are well-versed with stock valuation techniques should ideally go in for quant funds. Also, investors with a long-term investment horizon can consider quant funds.

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