Equity Insights : Fund Manager Perspectives 20th June 2015
Will computers replace humans in equity fund management?
Anand Radhakrishnan, CIO-Franklin Equity, Franklin Templeton Investments

imgbd Equity Insights is a joint initiative between Franklin Templeton Investments and Wealth Forum, where we aim to provide 360 degree business, advisory and fund management perspectives on equity investing, to enable advisors and distributors to position equity funds better and help investors genuinely gain from the long term wealth creation potential of equity funds.

Investing in large caps internationally is gravitating increasingly away from alpha to beta and now towards smart beta strategies. What's in store for us in India? Will large cap investing be codified into smart beta products, thus eliminating the need for human fund managers? How will active managers compete against beta and smart beta products in the information rich large caps world? Anand Radhakrishnan draws insights from the game of chess to share very interesting perspectives on this key issue.

WF: In mature markets, alpha generation has become a challenge in the large caps space, resulting in the rapid growth of low cost beta products. What are the sources of alpha in the Indian large caps space and how sustainable is alpha generation in Indian large caps?

Anand Radhakrishnan: Yes, as markets have become wider and deeper with more participants, information gets priced in fairly rapidly. And therefore time to act and time to react comes down. This makes it pretty challenging to outperform on a consistent basis. And my guess is that markets will become more and more efficient, as we move ahead.

As we stand today, our funds are able to comfortably outperform large cap benchmarks. From a longer term point of view, looking ahead, this is likely to become more challenging. One source of alpha in this context is to increase your active positions. Many fund managers in the large caps space tend to be benchmark hugging, some even going to the extent of closet indexing. Risk aversion is much higher in the large caps space - perhaps because of a combination of investor and distributor expectations and competitive performance pressures. There is a strong disincentive to underperform. We now also have regulatory oversight on performance, which kicks in for funds that underperform benchmarks over a 3 year period.

The more closely you align with the benchmark, the more difficult it gets to outperform, but the less is your chance of going way below in terms of performance. Fund managers who are able to take active bets away from the index, based on their own research and their own convictions, stand a better chance to continue delivering alpha. Going forward, I believe alpha will continue to be generated by those who take calibrated active risks.

WF: Internationally, smart-beta funds are posing a new round of threat to traditional actively managed large cap funds. How do you see smart-beta funds in the Indian context?

Anand Radhakrishnan: I think all of you would like to believe that we are also smart but some of these algorithms can be built into rules. Some of the things which we think in our mind can be built into rules and those rules can be implemented without any human intervention. The thing is as with anything else it will get competed away pretty fast because everyone would be doing it. So in some sense today's smart beta will become tomorrow beta. But the challenge for active managers is to remain ahead of beta and ahead of smart beta but that's a big challenge. And as I said earlier as you decode some of the simpler elements of the portfolio management and make them into rules, what is only left is the complex thing.

Think about chess. Initially, when humans began playing chess against computers, humans won easily. But, as more and more rules and variations got embedded into the computer systems, it became more and more difficult for humans to beat computers at chess, and today only some grandmasters are able to beat the computer.

So, I guess as more and more rules on different scenarios get built into smart beta products, they can compete over time against alpha generated by pure active management. It is possible to codify certain rules, but perhaps not all. Its possible to visualize certain scenarios, perhaps not all. So, in many ways it's a lot like chess, but not entirely.

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