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Quant-based mutual funds: What they are and how they work

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The Indian capital market has been largely dominated by active investing for several decades, where the expertise of fund managers in selecting high-performing equities and sectors has been highly valued.

However, with the rise of machine learning and Artificial Intelligence (AI) technologies, the mutual fund industry has increasingly embraced these advancements to enhance investment decision-making. The shift reflects the growing trend towards technology-driven investment strategies – enter Quant Funds.

  • Table of contents
  1. What are quant funds?
  2. Types of quant-based investing in mutual funds
  3. The mechanism behind quant mutual funds
  4. The process of quantitative investment in quant mutual funds
  5. Who should invest in quant-based mutual funds?
  6. Pros of investing in quant-based mutual funds
  7. Cons of investing in quant-based mutual funds

What are quant funds?

Quant funds are mutual funds that use mathematical models, algorithms, and data analysis to inform investment decisions. The fund manager relies on an algorithm to identify patterns, trends, and market inefficiencies to predict market trends for higher return potential.

Quant mutual fund schemes are analogous to semi-active and semi-passive investing. Quantitative models drive the stock identification process. Subsequent portfolio management and rebalancing can also be done with the assistance of these models. By reducing human biases and emotions in the decision-making process, quant funds aim for an objective and efficient approach to investing that can potentially provide relatively predictable return potential.

Types of quant-based investing in mutual funds

Quant-based investing in mutual funds can generally be categorised into two types: Single-factor investing and multi-factor investing.

1. Single-factor investing

  • Description: Focuses on one specific factor or attribute to guide investment decisions.
  • Examples of factors

o Value: Stocks with low valuation ratios (e.g., P/E, P/B).

o Momentum: Stocks with strong upward price trends.

o Quality: Companies with robust financial metrics (e.g., high ROE, low debt-to-equity).

Low Volatility: Stocks with historically lower price fluctuations.

2. Multi-factor investing

  • Description: Combines multiple factors to build a diversified portfolio, reducing reliance on the performance of any single factor.
  • Examples of possible factor combinations:

Value + Momentum: Exploiting undervalued stocks or those that are gaining market traction.

Quality + Low Volatility: Selecting relatively stable and financially healthy companies to mitigate risk.

Growth + ESG: Investing in companies with high growth potential that also meet environmental, social, and governance criteria.

The mechanism behind quant mutual funds

Now that you know “what are quant funds”, let’s look at the typical steps involved in creating such a mutual fund portfolio.

  • Data collection: Quant-based mutual funds gather vast amounts of historical and real-time market data, including stock prices, financial statements, and macroeconomic indicators.
  • Model development: Advanced mathematical models and algorithms are developed to identify patterns, correlations, and trends from the data.
  • Strategy design: Based on these models, quant mutual fund schemes design systematic strategies (e.g., factor-based) to make investment decisions.
  • Continuous optimisation: Models are constantly tested, refined, and optimised with new data to adapt Quant mutual fund investments to changing market conditions.

The process of quantitative investment in quant mutual funds

The quantitative investment process in quant-based mutual funds can be broken down into three stages:

  • Input system: At this stage, essential data, including market information such as interest rates and GDP growth; and company-specific data such as revenue growth, earnings and P/E ratio is gathered. Stocks with undesirable characteristics, such as high volatility or excessive debt are filtered out.
  • Forecasting engine: At this stage, expected returns, risks, and other performance factors are estimated to evaluate stocks.
  • Portfolio construction: The final stage uses optimisation techniques to build the portfolio, assigning appropriate weights to each stock. The main goal here is to optimise the risk/return balance. Depending upon the scheme’s investment approach, the fund manager may make the final stock pick, or the entire process would be entirely algorithm-driven.

Who should invest in quant-based mutual funds?

Now that you know “what are quant funds” and how they work, you will be able to understand if quant mutual fund investments may be suitable for your portfolio. You should consider investing in quant mutual funds if:

  • You are a tech-savvy investor who prefers data-driven, algorithm-based investment strategies over human decision-making.
  • You have a high risk appetite and a long investment horizon.
  • You are an experienced investor who understands the limitations and potential risks associated with quant investment strategies.

Pros of investing in quant-based mutual funds

Here are the benefits of Quant mutual fund investments:

  • Data-driven decisions: Quant mutual funds reduce human bias and error in judgement by relying on data and algorithms. This can lead to objective and consistent decision-making.
  • Diversification: Mutual funds based on quant-based investing models often reduce volatility and optimise portfolios for better risk distribution.
  • Lower costs: Quant-based mutual funds typically have lower management fees compared to actively managed funds since investment decisions are primarily made by the algorithms.
  • Scalability: Mutual funds based on quant strategies can efficiently handle large portfolios, providing scalability without compromising performance.

Cons of investing in quant-based mutual funds

Some of the disadvantages of quant mutual funds are:

  • Quality of data and investing model: The accuracy of quant-based mutual funds depends on the quality and accuracy of data. Poor data can lead to subpar results. In the same way, a flawed model can make considerable errors in finding stocks and result in significant losses, especially in volatile markets.
  • Lack of flexibility: Quant strategies may struggle to adapt to sudden, unforeseen market changes because trends do not always follow clear patterns that AI-based models can easily predict.
  • Based on historical performance: As the common adage in mutual fund investing goes: “Past performance does not indicate or predict future returns”. Along the same lines, quant-based investing models may not yield optimal results in real-world scenarios due to their reliance on historical data.

Conclusion

In conclusion, quant-based mutual funds offer a data-driven, systematic approach to finding investment instruments that are more likely to perform well. Quant mutual fund schemes can be a valuable tool for investors seeking consistency and risk management by reducing human bias and enhancing decision-making consistency. However, quant mutual funds also require careful monitoring and ongoing adjustments because of their heavy reliance on historical data. Ultimately, they are suitable for investors who prefer an automated, rule-based investment strategy with a focus on long-term growth and risk optimisation.

FAQs

What is a quant-based mutual fund?

Quant-based mutual funds use mathematical models, algorithms, and data-driven techniques to make investment decisions and drive stock selection. Instead of relying on human judgment, these funds apply quantitative methods to identify opportunities, allocate assets, and manage risks systematically.

How are quant-based funds different from traditional mutual funds?

Quant-based funds rely on data analytics and pre-defined algorithms, limiting subjective decision-making. Traditional active mutual funds, on the other hand, rely more on the expertise and judgment of fund managers to select investments.

What are the risks associated with quant-based investing?

  • Model risk: Quant models can fail if the assumptions or inputs are incorrect.
  • Overfitting: Excessive reliance on historical data may not work in future market conditions.
  • Market risks: Like any other fund, quant funds are subject to broader market fluctuations.
  • Technology dependence: Relies on robust systems and quality data, which can pose operational risks.

Who should invest in quant-based mutual funds?

Quant-based funds are suitable for:

  • Investors seeking a systematic, data-driven approach to investing.
  • Those interested in reducing reliance on human decision-making biases in fund management.
  • Investors who want diversified exposure across market factors or want to complement actively managed funds in their portfolio.

However, as with any investment, understanding the strategy and associated risks is essential.

Mutual Fund Investments are subject to market risks, read all scheme related documents carefully. This document should not be treated as endorsement of the views / opinions or as an investment advice. This document should not be construed as a research report or a recommendation to buy or sell any security. This document is for information purpose only and should not be construed as a promise on minimum returns or safeguard of capital. This document alone is not sufficient and should not be used for the development or implementation of an investment strategy. The recipient should note and understand that the information provided above may not contain all the material aspects relevant for making an investment decision. Investors are advised to consult their own investment advisor before making any investment decision in light of their risk appetite, investment goals and horizon. This information is subject to change without any prior notice.

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