Alpha focused low cost large cap fund
Reliance Quant Fund
Reliance Quant Fund aims to deliver “true alpha” by using a scientific model based investment approach that focuses on the “sweet spot” confluence between growth, momentum and value investing styles. Ashutosh shares back tested data for his model which seems quite encouraging in an environment where large cap alpha is increasingly becoming a challenge. Its smart beta positioning enables the product to be offered at a lower cost relative to actively managed strategies – a welcome move especially in the large caps space.
WF: Your fund aims to participate in the “sweet spot” that sits at the confluence of growth, value and momentum styles of investing. Can you please elaborate how this will be done?
Ashutosh: Investors adopt different investment styles like Value, Growth and Momentum to generate ‘Alpha’ (excess fund returns vs. respective benchmark). Each of these styles use different factors for evaluation of potential investments, for eg., – Price to book, beta, dividend yield etc.,
Each of these strategies/ factors can potentially outperform the markets, however, no one strategy / factor works all the time. We believe a combination of these investment styles can create potential Alpha across all types of market conditions.
Quant funds attempt to generate Alpha or excess return over benchmark by adopting a scientific model based investment approach. This fund selects stocks/securities using a combination of various investment factors with a view to generate potentially superior returns across market phases.
In Reliance Quant Fund, we attempt to select securities based on a scientific Quantitative model that uses a combination of Styles. The model uses a combination of improving fundamentals, acceptable valuations and favorable momentum shortlists about 30 stocks, which as a portfolio, has the potential to outperform the market under all kinds of market conditions.
WF: Do you have weights assigned to each style? How will this be dynamically managed to reflect changing market dynamics? What are the quantitative measures that will guide stock selection and what is the rationale for choosing these?
Ashutosh: After extensive research and back-testing, we have chosen 8 quantitative parameters from across Fundamentals, Value and Momentum. We have assigned approximately 50% weight to Quality / Fundamentals, because evidence suggested that stocks were largely driven by quality such as the earnings growth, and sustainability of the same, about one-third (33%) weight to Momentum indicators and another 17% for Value indicators.
We do not intend to dynamically change the variables, unless over time, there is a strong merit to reconsider the weights or the metrics considered within them.
We are fairly confident that the quantitative parameters we have chosen are robust, and have the capability to identify stocks, and hence help us construct the portfolio, which could generate sustained alpha.
WF: Your fund relies on the hypothesis that “evidence” based portfolio construction works better than opinion based models. Do we have evidence to back this hypothesis? How does back testing of your model stack up vs traditional active investing oriented funds?
Ashutosh: The back-tested results are quite encouraging. The strategy has delivered 1 year rolling return of 24% (including expenses) vs BSE 200 TRI of 16% during the period of testing – from the beginning to 2012 till date. The strategy has also outperformed S&P BSE 200 TRI index across market conditions:
The Fund has also outperformed CRISIL Large Cap Average. Rs. 100 invested in the strategy has become Rs. 340 vs Rs. 220 of the large cap funds (data till Dec 2017, since the Crisil Large Cap index data is available only till then).
Reliance Quant Fund would be positioned against the actively managed large cap funds, with an attempt to outperform them on a sustained basis over the period.
WF: What elements of alpha generation are attempted to be captured in this smart beta product?
Ashutosh: Reliance Quant Fund is a unique fund which in the first place diversifies in terms of style, and thereby attempts to deliver sustained alpha over a period of time. Not only does the fund endeavor to generate alpha, it does so within well-defined contours:
WF: What are the key risk management practices that have been inducted in this quantitative model?
Ashutosh: Reliance Quant Fund follows a defined approach for investments, which goes a long way in controlling risks, while attempting to generate sustained alpha.
WF: Given its smart beta positioning, how does the expense ratio compare with actively managed equity funds?
Ashutosh: The positioning of the Fund is somewhere between passive funds like ETFs / Index Funds and actively managed diversified equity funds. While ETFs / Index Funds are designed to generate index-minus returns (Index returns minus expenses), the endeavor in such smart beta products is to generate better returns than the index (or markets), without ‘actively’ managing the funds.
Given the nature and positioning of the fund, we are keeping expenses moderate. The Regular Plan expenses would be <1%.
WF: How do you see the road ahead for smart beta offerings in India?
World-over, smart beta products are extremely popular. They are almost as popular as ETFS / index funds and actively managed funds, commanding nearly one-third of the total assets. As markets mature, as may be the case with Indian markets already, generating alpha would become increasingly challenging. Funds like Reliance Quant Fund, which attempt to generate ‘True Alpha’ within a well-defined contour would find a lot of takers.
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