Motilal Oswal: Keeping emotions off the equation relatively easier in passive investing: Sankaranarayanan, Motilal Oswal AMC

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Being disciplined and managing risks are the key while investing rather than getting the picks right every time, believes Sankaranarayanan Krishnan, a quant fund manager at Motilal Oswal AMC.

Passive funds or quant-based funds are gaining traction, and Krishnan believes that the availability of abundant data has been the primary reason for the same.

“In addition, quant funds come with the promise of bias-free investing, with lesser dependence on directional market views, which may have resonated with investors,” Krishnan told ETMarkets in an interview. Edited excerpts:

What’s your mantra on savings and investment?

My central belief is that investment has more to do with discipline and risk management than getting the picks right all the time. This is definitely easier said than done.

My goal is to try and keep emotions out of the equation to the extent possible. Being a quantitative fund manager makes it relatively easier to adhere to this.

Quant Funds are gaining much popularity and many fund houses have recently launched factor-based funds. Can you give us a broad overview of a few quant strategies?
Sure. Factor investing is a quantitative strategy that captures company-specific attributes (like valuation, quality, etc.) that have contributed to a company’s outperformance over the broader market.

Typically, factor strategies rely on the company’s fundamentals and price/volume information to generate signals.

However, factor strategies are arguably more effective in a long-short manner, where you go long the basket of companies with the best attributes and short-sell the basket with the worst attributes that are expected to underperform the benchmark. Such strategies require extensive use of derivatives and are only available in the AIF format.

Outside of factor-based quant funds, there exists multi-asset quant funds that utilise quantitative models based on macroeconomic data, along with valuation and trends to take long or short positions on various asset classes.

The third category of quant funds, called statistical arbitrage, uses advanced mathematical models to decipher statistical patterns in the prices of different tradable instruments. The trades in statistical arbitrage funds are characteristic of brief duration and largely intra-day.

What are the factors driving growth in such funds?

The primary reason is the availability of abundant data and computational power, which ushered in demand for evidence-based investing. In addition, quant funds come with the promise of bias-free investing, with lesser dependence on directional market views, which may have resonated with investors.

A similar rise in the popularity of quant funds has already been seen in the western world, where multiple trillion dollars of assets are currently being managed quantitatively. If that is anything to go by, we are just getting started.

Can quant funds replace discretionary fund managers?

I would view them as complementary rather than contradictory. The quant fund’s strength lies in analysing a wide variety of securities – and taking positions in a diversified basket so that the extrapolation of historical performance into the future plays out on average.

On the other hand, the discretionary side specialises in the depth of analysis on a narrower list of securities, where conviction regarding future growth can be expressed much better.

What kind of strategies are you currently managing/researching?

We are currently running public money on long-only and hedged equity portfolios. The long-only funds are run in a PMS structure, and the hedged fund is run in a CAT-3 AIF structure. The equity portfolios in both structures are created using our proprietary multi-factor model.

In addition, our current research is focused on factor-timing, multi-asset allocation and long-short strategies.

Do your portfolios have a sector tilt? How frequently do your allocations change?

Our strategies are largely sector agnostic. That said, there could be periods when our strategy overweighs specific sectors purely as an outcome of our multi-factor model. We don’t take any discretionary sector calls. Typically, we have a quarterly rebalancing schedule for long-only and long-biased strategies. Multi-asset and long-short strategies typically warrant more frequent churning.

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

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