Multi-factor funds: Opt for quant model-run fund to eliminate manager risk

Be mindful that these funds do not have a track record, and changing market conditions can render a model obsolete

While passively managed multi-factor funds that track a multi-factor index have been around for some time, now several fund houses are launching multi-factor funds that do not track an index. Instead, all portfolio-related decisions are based on a quant model. New fund offers of Sundaram Multi Factor Fund and Bandhan Multi Factor Fund hit the market recently. Mirae Asset Mutual Fund is reportedly planning a similar offering through the fund-of-funds route.

 

Single- vs Multi-Factor Strategies 

Single-factor index funds mimic indices based on a single factor, such as quality, momentum, or value. The problem with such strategies is that they can underperform during certain periods. “If you have invested only in one factor strategy, your entire portfolio might go through prolonged underperformance when these factors or styles go out of favour,” says Jiral Mehta, manager–research, FundsIndia. 

Multi-factor strategies combine several factors into one fund. Their advantage is that when one factor is underperforming, the others could perform.

 

“Over time, multi-factor funds are expected to deliver stable alpha, making them an attractive proposition for long-term allocators,” says Anand Radhakrishnan, managing director and chief executive officer, Sundaram Mutual Fund.

 

These funds offer true diversification. “The portfolio is split between various factors, as opposed to funds which, even though they may be diversified across sectors, stocks, and the market cap curve, may not be diversified across factors,” says Radhakrishnan.

 

Risk and volatility tend to go down, and the investor has a more stable experience. “Multi-factor funds reduce risk by spreading exposure, leading to more consistent performance and lower volatility,” says Sirshendu Basu, head–products, Bandhan Mutual Fund. 

 

Rule-Based Approach 

These schemes will not track a passive index. All decisions will be made by a model, with no scope for human discretion. “Multi-factor funds offer a rule-based, data-driven approach that is expected to enhance portfolio performance. The model determines stock selection and weightages based on predefined factors,” says Radhakrishnan.

 

“A systematic, rule-based investment approach reduces the risk of human error,” says Basu.

 

Risks Remain 

Despite the benefits of a rule-based approach and diversification, risks persist. One could arise from the quant model being used. “Models rely heavily on historical data and assumptions that may not hold in changing market conditions,” says Basu.

 

Frequent rebalancing of the portfolio could result in a higher turnover. “This could increase transaction costs, which may erode net returns over time, particularly in cost-sensitive or illiquid environments,” says Basu.

 

Stay Invested for Long 

Experts recommend a long investment horizon to allow these funds to ride through at least one market cycle. Short-term performance, as with any equity scheme, can be volatile.

 

“These funds are suitable for patient, long-term investors (seven years or more) who can stick to the overall strategy,” says Mehta.

 

Most of these funds, however, do not have a track record. “We prefer funds built on proven investment factors and a strong real-world track record,” says Mehta.

 

Investors should cap exposure to them at 10 per cent of their core equity portfolio.

 

These funds are quite similar to the quant funds launched by several fund houses earlier. “There could be an overlap between how quant funds and these multi-factor funds are run. If you already own quant funds, then watch out for overlaps within your portfolio,” says Vishal Dhawan, chief financial planner, Plan Ahead Wealth Advisors. He also suggests checking the expense ratio: if they are on the higher side, that could make it harder for these model-based funds to generate alpha.

Weigh the Pros and Cons

Pros

 

*  Rule-based approach

 

*  No scope for human error

 

*  Multi-factor-based, hence suited for varied market conditions

 

Cons

 

-  No track record

 

-  A quant model that has worked in the past may not work in the future

 

-  Good back-tested results do not always translate into sound performance in real market conditions