In an interaction with Kshitij Anand of ETMarkets, she said the firm analyses more than 300 data points—from valuations and earnings momentum to macroeconomic indicators and sectoral trends—to identify alpha-generating opportunities.

She also shared how Wright PMS dynamically adjusts its allocations across factors and sectors, with current preferences tilted towards data centre-linked plays, power transmission, select pharma stocks and domestic-facing themes. Edited Excerpts –

Kshitij Anand: Can you take us through the performance of the fund vis-à-vis the benchmark in the recent period?

Sonam Srivastava: See, we have two funds: one is the Factor Fund and the other is the Alpha Fund. Our Factor Fund has had a good run. We are now almost three years since inception, and the fund has delivered close to a 20% CAGR compared to around 11% by the market. So, it has performed very well since inception.

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Over the last one year, we have been able to beat the benchmark by around 10%. Even over six months, three months, and one month, we are outperforming the benchmark. The reason for this is our tactical, quantitative approach. We were able to shift into the right set of sectors.
We have significant exposure to companies in the data centre space, power transmission, etc., which our factors and models picked up. That is why the performance has been strong.
Kshitij Anand: Can you explain what factor investing means in simple terms and why you believe it can outperform traditional stock-picking strategies?
Sonam Srivastava: See, factor investing is something that people have been doing for years. Factor investing essentially means trying to understand the underlying forces in the market that drive returns.

There are some very well-known factors, such as valuation—anything that is undervalued tends to outperform; growth—anything that is growing fast tends to attract investors; quality—high-quality companies attract investors; and behavioural factors like momentum, where stocks that pick up a trend tend to attract investors.

What factor investing does is try to break down these metrics for each stock. It is a very good quantitative way to look at the market. While four or five factors are widely known, we try to dig deeper and identify what else we can look at.

We analyse more than 300 data points. For example, we may have factors that identify the impact of inflation, showing which stocks are likely to be affected by inflation and which are not, or which stocks have exposure to North America or Africa, and so on.

So, there can be a very interesting set of factors, and we believe it is a very effective approach to gain a holistic understanding of a stock and the different forces influencing it. Through that, you can generate alpha. A lot of people associate factor investing with passive funds.

While that approach also has its own value, you will find that in one scenario, a momentum fund can be a great investment opportunity, while in another, a quality fund may be more attractive.

However, our approach is more active in nature—we actively evaluate factors, and we believe that can generate meaningful alpha over the long term.

Kshitij Anand: Let us look at this more deeply now. The fund mentions dynamic asset allocation between equity, factors, bonds, and gold. So, what indicators determine these allocation shifts, and how frequently do they occur?
Sonam Srivastava: See, again, it is a very interesting question. There are two parts to it. First of all, getting the right set of factors. As I said, we are not constrained to only five factors or 10 factors.

We are looking at anything and everything that is interesting. And even if you are looking at valuation, it does not have to be the PE ratio. It can be any other metric that makes more sense. So, that is the first part.

Second, we look at something called a market regime. Is it a growth market, a consolidating market, or a market where there is capitulation and things are falling sharply?

What you will see is that throughout the market cycle, certain sets of factors work well in different phases. For example, quality works well when the market is falling. Secondly, once growth starts from the bottom, you will see value stocks doing well. And when growth really picks up, momentum stocks tend to do extremely well.

So, we try to model that market regime using macroeconomic indicators. Again, we do everything quantitatively. We look at metrics such as liquidity in the market, sentiment, and valuations, etc., to identify which regime we are in.

Once we know the regime, based on that we modulate the amount of risk we are going to take. If we are taking less risk, quality automatically gets more weight. And if we are taking more risk, momentum automatically gets more weight.

Kshitij Anand: Good that you mentioned the quantitative and qualitative aspects. So, how do your quantitative models adapt during periods of extreme market volatility, such as geopolitical events or the sudden economic shocks that we have seen recently?
Sonam Srivastava: See, I think that is a very, very apt question for today’s time, and we have seen this throughout the cycle. I will give you some context here. We started the PMS three years ago.

The first one-and-a-half years after starting were probably the best period. It was like the peak, and I think we were among the top-performing funds. We did extremely well.

Then, when volatility hit last year, it did have an impact because in 2025, almost anything and everything got affected. So, there have been lessons as well.

What happens during volatile periods is that our strategy starts allocating more towards lower-risk factors such as quality and adopts a more defensive stance. Throughout 2025, we saw that the allocation was relatively more defensive.

Eventually, we started adding more exposure to sectors such as cement and chemicals, and towards the end of last year, we significantly increased our allocation to industrials. So, the portfolio adapts with the market. But yes, the models definitely handle such situations really well.

Kshitij Anand: Now, with the portfolio turnover of around 250%, how do you balance active management with transaction costs and tax efficiency?
Sonam Srivastava: That is also a very good question. See, if you look at any active manager, they tend to have a decent turnover. Many active managers, even in the traditional space, have turnover north of 150% or so.

Some value investing funds, on the other hand, typically have very low turnover because they buy a stock and hold it for a long time before selling it.

When we are working with data, what happens is that if we simply let the data run, it changes every day, which can lead to very high churn. In fact, 250% is actually quite low. So, what we do is implement turnover controls.

We try to strike a balance between the amount of returns we can generate and the level of churn we can afford. We aim to find that sweet spot, and we believe 250% is a very reasonable figure.

If you look at some other quant funds, I have heard of managers reporting turnover of 600%. So, ours is a decent number, and we think it is justified. For example, last year we saw a lot of churn from defensive sectors into industrials, which was completely justified because that is what has been working in the market.

Kshitij Anand: Earlier in the conversation, we spoke about factors. Are there any specific factors, such as momentum, value, quality, or low volatility, that currently dominate your allocation, or does the model decide that dynamically?
Sonam Srivastava: As I was telling you, I recently wrote a newsletter about this. We carried out a detailed analysis of the macroeconomic environment, and the picture is mixed. Obviously, we are seeing some recovery in sentiment with the Iran deal coming in, and there could be some euphoria going forward.

However, if you look at factor trends and dispersion—which means the difference between the top-performing momentum stocks and the least-performing momentum stocks—you will find that price momentum, earnings momentum, where we track the growth projections of stocks and how they are evolving, and value are the factors that are working really well right now.

On the other hand, low volatility and quality are currently underperforming for some reason. We are also seeing that plain beta is not working because there are so many forces at play. You have developments related to Iran, domestic factors like El Niño, and broader domestic market churn.

So, simply relying on beta will not work. You have to be very strategic, and that is where these factors have helped us identify the right set of stocks.

Kshitij Anand: Given the current market valuations, where do you see the best opportunities for factor-based investing over the next, let us say, 12 to 18 months?
Sonam Srivastava: As you mentioned, we are currently recovering from a weak market phase. Typically, during such recoveries, you will see momentum and earnings momentum deliver stronger returns.

In terms of market segments, what we have observed within our own strategies is a significant allocation towards stocks with exposure to the data centre theme. For example, we hold one stock, MTR Technologies, which has gone up nearly three times in our portfolio in 2026.

We also have exposure to several companies in the power transmission segment that are benefiting from the data centre opportunity, and they have been performing very well.

More recently, I have also started seeing pharma names emerge in our models, along with a few consumer stocks.

Kshitij Anand: Does factor-based investing work better in a bull market, a bear market, or a sideways market?
Sonam Srivastava: See, factor-based investing is just an umbrella term. It can mean many different things. There can be a quant investor or a factor-based investor who focuses only on quality.

There can be a factor investor who focuses only on momentum. We know there are some people who only do momentum, some who only do quality, and others who only focus on growth.

So, there is a whole spectrum of approaches. And because of that, you will have managers who outperform in different market conditions.

If somebody has a quantitative focus only on quality, they will do well in volatile markets. Somebody with a quantitative focus on momentum will do well in a bull market but may struggle when the market becomes volatile.

So, it is a broad term. We did have exposure to momentum in 2025, which is why we saw a correction, and then we gradually shifted towards quality. Now, momentum has started picking up again.

The reason I started Wright Research is because I believe that if I can make the correct tactical allocation through these factors, then I can identify the right strategy for every market.

It is very difficult to do because you not only have to focus on factor strategies but also identify the type of market you are in. It can be tricky, but that is our approach. If we can do that correctly, then we can obviously generate higher alpha. So, I believe factor investing has that potential.

Kshitij Anand: Are there any sectors that are looking attractive to you at this point in time?
Sonam Srivastava: Sectorally, we are at an interesting stage. We have seen a good run-up in the themes I was talking about earlier, such as proxy AI plays like data centres. We have witnessed a very strong bull run there, and we are still allocated to that theme.

We also had exposure to metals, although we have reduced it slightly in recent times. On the consumer side, we have picked up a few names, as well as some pharmaceutical stocks, where we are seeing a lot of stability and growth.

In the consumer space, we prefer specific names rather than the entire basket because factors like the monsoon could have an impact. However, certain companies are definitely doing well.

We do not have any exposure to IT at the moment. In banking, we have exposure to a few NBFCs, and we believe there is some positive news flow on the NBFC side as well. Broadly, that is the kind of exposure we currently have.

Kshitij Anand: So, more domestically oriented sectors, actually.
Sonam Srivastava: Yes, there is a strong domestic orientation. I will also share the newsletter with you. We analysed what worked and what did not work over the last year.

We found that companies with exposure to the US dollar or the US market itself have not performed particularly well. However, companies with exposure to Europe, the Middle East, and Africa have delivered better performance during the same period.

(Disclaimer: Recommendations, suggestions, views, and opinions given by experts are their own. These do not represent the views of the Economic Times)