Reliance Quant fund: The arrival of new-age ‘smart’ funds

If you followed developed equity markets in the rest of the world, you would have read that index and ETF-based investing are often touted to be the smart, efficient way to invest. However, in the Indian context, actively managed funds, even post their expenses have convincingly managed to beat index funds; so much so that we have maintained that there is little to no case for investing in index funds in India. However, we have been cognizant of the fact that large-cap funds, save for a few, have over the years reduced their margin of outperformance of key indices, even as diversified and midcap funds continue to outperform in style.

Smart Beta indices in India

We have therefore been keenly watching the development of newer, ‘smarter’ indices that are not too static, that use certain stock return driving factors to arrive at their portfolio and that are rebalanced more efficiently. Whether it is the factor indices such as Nifty Alpha or Nifty Low volatility or Nifty Quality or a combination of these (called Multi factor indices) we have been running checks on new indices. Our analysis of these suggest that they comfortably beat traditional indices, especially when used in a combination (eg. – alpha, value and quality parameters). Still, a good number of consistently performing actively managed funds beat these indices. That basically means that these indices are still not nimble enough or smart enough.

Elsewhere in the globe multi-factor investing (smart beta) strategies have been gaining ground. Multi-factor investing is investing based on a set of identified factors that drive returns. When factors that can complement each other well and enhance returns and contain downsides well are identified, they can be used to build a metric-driven model. Such factors can be created as composites by assigning weights to the individual factors, and building an automated model. With a basic set of rules and occasional rebalancing, they can generate returns efficiently. In other words these are semi-active or rather semi-passive funds. What can these funds return? They have the potential to generate superior returns than the index and may also well beat their active peers, especially with a lower cost structure. They may need less interference from fund managers and therefore their cost is also not high.

In the Indian context, there are a couple of funds from the Sundaram and DSP BR houses that have equal weighted indices. But they are built on existing indices with stocks simply weighted equally. They are a tad better than plain vanilla index funds.

In recent times, Reliance Quant Plus fund, a quant-based fund has undergone a facelift by donning a new strategy based on multi-factor investing.

Reliance Quant Fund

Reliance Quant fund (earlier called Reliance Quant Plus) is a low-cost, smart beta fund that seeks to generate alpha through a quantitative structure of investing in the BSE 200 stocks. Please note that the past returns of Reliance Quant fund are almost irrelevant now, as it is undergoing an entire rejig in terms of strategy based on the new quant model. In its earlier avatar, the fund was picking stocks only from the Nifty.

• Reliance Quant fund will provide weights of one-third each to quality (which are identified fundamental parameters), momentum and value metrics to filter a bunch of stocks from the BSE 200. It ensures a minimum 30% weight to banking and financial space and rest to other sectors.
• It will place about 80% weight to the top 100 stocks in the BSE 200 and about 20% to the remaining 100. That essentially means it will act like a large-cap fund.
• The fund will seek to contain individual stock weights to less than 8%.
• It will have minimum sector deviation from the benchmark.
• Given that it will invest only from the BSE 200 universe, its liquidity will be maintained.

What the fund is not

• It is not an index fund. It is a semi-active fund.
• The fund manager cannot take opinion-based calls not supported by the model.
• The fund will not take active calls. It will only rejig its portfolio every quarter based on the model’s metric

What is the genesis behind using a combination of factors? We know that no one strategy works always. A value strategy can underperform in rallying markets. A growth strategy can fail to contain downsides. A momentum-driven strategy can turn around before one anticipates. A good performing fund sometimes starts underperforming because some of these calls may have gone wrong. In other words, a fund managers’ forecasts may have turned bad. The multi-factor model avoids the risk of prediction or opinion and simply runs the portfolio based on evidence.

Our observations

Since this fund seeks to avoid human intervention save for the model and the rules, we got its expense-adjusted NAV back-tested. The results threw some surprises:

• The rolling 1-year returns for the past 5 years (until mid-May 2018) showed a 91% outperformance of the BSE 200 TRI. On a rolling 3-year basis, the outperformance was 100%. The average margin of outperformance over the index, in the same period was 9%.
• The fund beat some of the top performing large-cap funds by 4-6 percentage points on a rolling 3-year return basis.
• We further tested it with a combination of the NSE factor indices. Among the NSE factor indices, the combination that provides the best results is an equal weighted approach to Nifty Alpha 50, Nifty Low Volatility 50 and Nifty Quality 30. When compared with this combination, the fund beat this blended index all the times on a rolling 3-year return basis and the average margin of outperformance was 6%. This, after adjusting for expense ratio.
• In all, the fund delivered an average 3-year rolling return of 25% annualized (rolled over for 5 years), compared with our blended smart beta index return of 19.4% annualized.

What you need to aware of is, these are returns on portfolios back-constructed on the model. While there is an element of returns under ideal scenario bias that creeps in, even a few percentage points of lower returns would have kept the fund above many large-cap funds. There will obviously be periods when funds with such strategies can underperform. It can be when markets rally for too long or when value signals do not pay off. But then, the downside, post such scenarios can also be contained.

Portfolio

Reliance Quant is still in the process of rejigging its portfolio to suit the new model. However, higher positions in finance, technology and auto is currently evident. We will update you more about the portfolio once the rejig is complete.

Suitability

Reliance Quant is suitable for those looking for low-cost ways to invest in large-cap funds but do not want to settle for mediocre index returns. It is also for those who want to contain downsides better. Since its model is new and still tested, the ideal way to enter this fund would be to add it in addition to the existing funds, test waters and then decide whether to use it in lieu of large-cap funds.

The fund’s expense ratio is at around 1%. The fund is managed by Ashutosh Bhargava from September 2017. It is classified as a thematic fund under the new SEBI categorization. It is benchmarked against the S&P BSE 200. It is to be noted that the fund’s AUM was little under Rs 30 crore as of April 2018.

FundsIndia’s Research team has, to the best of its ability, taken into account various factors – both quantitative measures and qualitative assessments, in an unbiased manner, while choosing the fund(s) mentioned above. However, they carry unknown risks and uncertainties linked to broad markets, as well as analysts’ expectations about future events. They should not, therefore, be the sole basis for investment decisions. To know how to read our weekly fund reviews, please click here.