DSP ELSS Tax Saver Fund Regular Plan Growth INF740K01185

However, since investors in this fund tend to be retail in nature, the manager is slightly more risk-averse in this fund compared with the latter.

When constructing the portfolio, Singhania primarily looks for stocks where he feels the price has deviated significantly from what he believes to be fair value of that business. His estimate of the fair value is based on conservative assumptions about the future, shaped by the strength of the business model, its historical track record, and the quality of people leading it.

While evaluating business, Singhania focuses on the business model, quality of management, and financial metrics. When it comes to business models, the manager looks at the durability of various factors like competitive advantage, demand and growth drivers, product positioning, supply chain management, and so on over time and the execution during recessions and down cycles in particular. He likes businesses that can remain profitable at the bottom of the cycle and, even better, continue to grow and gain market share.

Analysts construct sector-based model portfolios comprising the best ideas from stocks in their investment universe. Businesses are evaluated using quantitative ratios such as return on capital employed, return on equity, price/earnings, price/book value, and EV/EBITDA, among others, with the analysis and research inputs of key sell-side analysts incorporated into the model.

While the stock selection is largely bottom-up, he does ply some macro-overlay focusing on government policy actions, business cycles, and interest rates to determine the sector overweightings/underweightings. Singhania, however, prefers to generate alpha from stock selection rather than sector calls.

Historically, the manager used to churn the portfolio frequently to extract positive alpha from the fund. However, over the last few years, we have seen the turnover of the fund drop significantly. Additionally, he is more benchmark-aware now than before and doesn’t shy away from aligning the sector weights with the benchmark index in case he doesn’t have a strong view either positive or negative on the sector. While this hasn’t affected the performance of the fund so far, we would like to watch this closely going ahead. For now, we assign an Average rating for the Process Pillar.

Rohit Singhania has traditionally employed an unconstrained, benchmark-agnostic strategy without favoring any specific stock or sector when constructing his portfolio. However, there has been a slight shift in his approach in the recent past. Having said that, he broadly divides his portfolio into two parts. The core allocation of the portfolio is approximately 70%, which constitutes companies with good growth prospects, good balance sheets, and sufficient margins of safety. These could also include companies close to cyclical lows in their business that are available at distressed valuations. On the other hand, the remaining 30% of the portfolio includes companies with strong growth and profitability metrics that may not meet the margin of safety criterion. Investments in these companies are made only if there are visible near-term catalysts for growth or an improved return/risk profile. Typically, these companies do not have a positive active weight in the portfolio.

Singhania prefers a diversified portfolio, consisting of 60–70 stocks, with the top 10 names accounting for roughly 35%-40% of assets. He employs a basket approach, taking small positions in two to three stocks from each sector that he believes will perform well because of favorable dynamics, while avoiding large positions in any single stock. From a market-cap perspective, the fund will continue to be biased toward large-cap names, which account for 60%-70% of the portfolio.

When Singhania has strong conviction in an idea, the active share for a sector or stock will be high. Conversely, when opportunities are scarce, he reduces deviations from the benchmark. The more expensive stocks in the portfolio, valuationwise, are typically benchmark stocks without a positive active weight. High active weights are generally in stocks recovering from cyclical lows or laggards in a sector showing an improving business trajectory.