Indian equity markets have remained under pressure over the past year, with returns moderating amid a combination of tariff-related disruptions, earnings slowdown and heightened geopolitical uncertainty. In this environment, strategies that focus on risk management and capital preservation have come into sharper focus, especially among high-net-worth investors evaluating alternatives beyond traditional mutual funds.
In an exclusive conversation with BW Businessworld, Rishabh Nahar, Partner and Fund Manager at Qode Advisors, outlines how quant-driven investing is positioned to navigate such market conditions. He also discusses the performance of SIPs during volatile phases, the structural advantages of portfolio management services (PMS) over mutual funds and the evolving role of data-driven models in sector allocation, risk management and long-term wealth creation for high-ticket investors.
Edited excerpts:
Indian markets have delivered muted returns amid tariffs, earnings slowdown and geopolitical risks. How has a quant-driven strategy performed in this environment compared to traditional discretionary investing?
The last 18 months have been genuinely painful for most investors, and the data tells a very clear story. Indian benchmarks delivered muted returns in calendar year 2025, and the broader mid and small-cap universe saw far sharper corrections. Our Quant All Weather (QAW) strategy, delivered over 30 per cent over the last one year with the strategy of downside protection and volatility management. When everyone was taking the hit in March 2026 as geopolitical shocks rattled markets and FII outflows crossed USD 12 billion in a single month, our portfolio was structurally hedged and did not participate in that fall to anywhere near the same extent.
This is exactly what a quant strategy is built for. We stress-test the portfolio against all types of events and shocks, rate spikes, geopolitical flares, earnings collapses, liquidity crunches and build guardrails that aim to navigate those environments better than an unprotected discretionary book. A discretionary manager in October 2024 could rationalise staying invested because of conviction in a story. Our model does not rationalise. It responds to data, adjusts and protects.
For investors allocating Rs 50 lakh or more, how does a quant PMS stack up against actively managed mutual funds in terms of risk-adjusted returns and drawdowns?
The comparison really comes down to two things: what you earn and how much pain you absorb getting there. On both counts, we believe a well-constructed quant PMS has a structural advantage over a traditional actively managed mutual fund, and our own numbers bear this out.
Our sharpe ratio since inception stands at 1.13. For context, a sharpe ratio above 1 is considered strong; it means you are generating more than one unit of return for every unit of risk you are taking. Most active mutual funds in India struggle to consistently sustain a sharpe ratio above 0.8 over a full market cycle. More importantly, our maximum drawdown since inception has stayed below 7 per cent, even through a period when the broader market experienced drawdowns of 15 to 20 per cent. That gap is not a rounding error, it is the difference between a client staying calm and a client redeeming at the bottom.
A mutual fund, by its structure, is a pooled vehicle with constraints on position sizing, sector limits and redemption pressures that can force selling at exactly the wrong time. A PMS sits in a segregated demat account, is run without those structural pressures, and in our case, is governed by a rules-based model that does not make emotional decisions.
Retail SIP investors have seen limited returns recently. For high-ticket investors, does a lump-sum allocation to a quant PMS make more sense than staggered investing in current market conditions?
QAW strategy is built does not require you to time the market to get a good outcome. When markets fall, the portfolio is protected through hedges and downside guardrails. When markets rally, you participate in the upside. That design gives investors the comfort of deploying capital and not needing to second-guess the timing.
This is actually a structural advantage over the SIP model for high-ticket investors. A SIP is a retail solution for averaging out volatility over time. For someone deploying Rs 50 lakh or more, doing a 24-month SIP means a large portion of your capital is sitting idle earning near-zero returns while you wait for the last instalment. With QAW, you can put the money to work immediately because the strategy itself manages the volatility for you.
There is also a second layer to this. Because QAW is built as a defensive all-weather core, it gives us the flexibility to layer tactical calls on top when the environment warrants it. If the market corrects to attractive levels and macro conditions look favourable, we can shift allocation toward a more aggressive strategy.
What are the key factors your models are currently favouring, and how frequently do these factor preferences shift in a volatile macro environment?
Our models are dynamic, they are adjusted when market conditions change, not on a fixed calendar schedule. The signals we act on are a function of what the environment is telling us, not what a quarterly review meeting decides. That responsiveness is part of the edge.
Right now, in a volatile macro environment marked by elevated crude oil, geopolitical uncertainty and range-bound equity markets, our models are leaning more heavily on quality and low volatility relative to aggressive momentum. Quality which captures return on equity, balance sheet strength, earnings consistency and cash generation tends to be the most resilient factor in uncertain markets. Low volatility similarly reduces the portfolio’s sensitivity to broad market swings, which matters a great deal when the macro backdrop can change on a headline.
Momentum remains part of our factor mix because it is one of the most academically validated signals in investing, but we are blending it carefully. Pure momentum exposure in a choppy, range-bound market like the one we have today can be very dangerous between September 2024 and March 2025, the Nifty 200 Momentum 30 Index fell over 31 per cent, which was a stark reminder of what happens when you chase trend without adequate diversification across factors.
The key discipline here is that while our factor tilts respond to market conditions, we never over-rotate. If you are adjusting your model every two weeks, you are no longer running a systematic process you are making discretionary calls with extra steps. The edge in quant comes from consistency and trust in the model, especially when it feels uncomfortable.
Given the current macro backdrop, which sectors are your models overweight and underweight on, and what signals are driving those allocations?
Over the last year, our stock-picking models have concentrated more heavily on PSU banks and domestic manufacturing companies, and that has been a meaningful contributor to our performance. PSU banks were an interesting call they came into this period with clean balance sheets, improving return ratios, and attractive valuations relative to private peers. As credit growth held up and the rate environment turned more supportive following RBI rate cuts, that thesis has played out well.
Manufacturing, including defence and capital goods, is a structural overweight for us driven by policy tailwinds, healthy order books and India’s ongoing import substitution story. This is not a new theme, but it is one that our models continue to score highly on earnings momentum and quality metrics.
On the underweight side, we have been selective on IT services since the sector is navigating a genuinely complex set of headwinds, client caution, shifting tech priorities and the longer-term question of what generative AI does to pricing models. Oil marketing companies could be interesting if crude corrects from current levels around USD 107 a barrel, but that is more of an event-driven thesis than a factor-driven one.
Where are you seeing the best opportunities today across large-cap, mid-cap and small-cap segments, especially after the recent valuation correction?
Our valuation indicators show that large-caps, mid-caps and small-caps are all still in expensive territory relative to historical averages, even after the correction of the last 18 months. The derating has happened, but it has not yet created broad-based cheapness.
The one segment that stands out as relatively and absolutely cheaper is microcaps. This is a part of the market that saw extreme froth in 2023 and 2024, corrected very sharply, and is now trading at valuations that look genuinely interesting on a risk-adjusted basis compared to the rest of the market. For investors with the right risk appetite and time horizon, quality microcap names that our models flag on earnings consistency and balance sheet strength represent one of the more interesting opportunity sets right now.
Within large-caps, domestic financials and consumption remain the most defensible allocations not because they are cheap, but because they have the earnings visibility and pricing power to justify their valuations in a strong domestic demand environment.
The overall message is be selective, be quality-oriented, and do not confuse a correction with a clearance sale across the board.
What kind of investor is best suited for a quant PMS in terms of time horizon, risk appetite and expectations, especially at the Rs 50 lakh entry threshold?
PMS is not designed for first-time investors or people who will track their portfolio daily and call us every time the market moves 2 per cent. That kind of investor will not get the best out of any PMS, quant or otherwise. The most important quality in our ideal investor is process faith. Quant strategies will, in certain phases, underperform a concentrated discretionary bet or a hot thematic fund. That is not a failure of the model, it is the model doing its job of being disciplined rather than chasing.
An investor who understands that and stays the course is the one who ultimately benefits from everything the strategy is designed to deliver. As data shows, roughly 79 per cent of PMS strategies have beaten their benchmarks over a 10-year period. The investors who captured that outperformance are the ones who stayed invested through the uncomfortable quarters, not the ones who jumped in and out chasing short-term performance tables.
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