Nimesh Chandan, Head - Investment Equities, Canara Robeco Mutual Fund, shares his perspective. You can access more such insights in the India Markets Observer. All you have to do is register and gain free access to the entire online publication.
There are three sources of alpha. The Information Edge (superior information), the Analytical Edge (quant models), and the Behavioural Edge (save losses by understanding your biases, and profit from the mistakes of the crowd).
The beauty about stock markets is that nothing works every single time. But a good process will necessarily lead to a good long-term outcome, though in the near term it may not work.
Our idea generation is through top-down and bottom-up analysis, the sectors and the companies that look good.
Good businesses (scalability, sustainable growth rates, RoC, franchise value) and good management (quantitative and qualitative analysis). Business comes before management, because even if you put a good management in a business, which has bad economics and unfavourable dynamics, it will not be able to do much.
- Improve the top-down approach.
There is an inside view and an outside view. Assume you are writing a book about investments and the publisher asks you how long you will take to complete it. You confidently commit to a year (inside view). Then the publisher informs you that only 1% of the writers and authors in the same field have completed such a project within 12 months (outside view). Now you know what you're out against and your perspective changes.
Often, due to a high growth rate, cycles are ignored. Take Amazon, for instance. An analyst actually came out with a note that the company can grow 15% for 20 years. But check from the 1950s, the history of any company that is close to the size of Amazon, inflation-adjusted. How many have grown at 15% a year over two decades? None. Not that Amazon can't do it, but now you know what you're put up against.
Collecting data on long cycles is important. Regression to mean is important.
We are focused on business cycles. We collect around 250 data points of the global and Indian economy to understand where we are on a cycle. Forecasting macros is difficult, understanding a cycle is easier.
- Improve the bottom-up approach.
In a study on the U.S market, Richard Thaler and De Bondt collected data over 60 years. The best-performing companies of the last five years went into the winner portfolio and the worst-performing ones into the loser portfolio. They found that in the subsequent five years, the losers consistently outperformed the winners.
We tried this research for India with 15 years of data. It works 75% of the times. Why?
Thaler and De Bondt said that a lot of investors hold on to their losers before eventually giving them up. Analysts stop recommending some of the stocks which are consistently going down, people don't want them in their portfolios or they are embarrassed to show it to their clients. These companies come to a value which is so low that they become vulnerable to any positive news that comes.
The opposite happens for the glamour stocks, which are highly valued and loved. Even if an individual got just 10 shares in an IPO, he would flaunt it to his friend. Then they become vulnerable to negative news.
In The Checklist Manifesto, Atul Gawande speaks about two kinds of errors that doctors make; the error of ignorance where you attend a patient, you try to understand what the ailment is, but you really don't know what medicine to give. The second is where you know what's to be done, but you don't do it.
Checklist helps in creating a discipline, it helps in creating a thoroughness. Everybody can't make all the mistakes. So, you actually learn from others' mistakes. You put others' mistakes also on the checklist so that before you evaluate a company, you have gone through what all can be a downside for that.
We use an investment checklist for all the companies that enter into our investment universe and which look at the major parameters that we would want to analyze a company before getting into the investment universe side.
We follow growth at a reasonable price (GARP). However, there are two biases that come in when valuing a stock.
One is overconfidence. If you ask people in a room how many of them believe that they are better drivers than an average person, almost 80% actually would raise their hands.
We are always more confident about our abilities than reality. Hence, we make wrong projections. How do you get over it? Bu looking at scenarios that examine what can go wrong. A pre-mortem, instead of a post-mortem. Pre-mortem is looking at 2020 with the scenario that the investment has gone wrong. Now we work backwards to figure out what went wrong.
The other problem is cognitive dissonance - twisting the facts to fit your theory. If a stock price is going down, an analyst would be happy that it is reaching his target price. If it keeps dipping, the analyst would actually change the reason as to why that stock should still be bought, rather that admit he was wrong. By creating a bull case and a bear case scenario, you are able to give an out to the analyst. And in return, you also know the risk and the returns of a particular investment. So we do this B3 analysis, every analyst, instead of giving one target price, gives a range of bull case, a base case and bear case.
Feedback is important, reviews are important and learning from mistakes is important. One of the best industries that learns from mistakes is the airlines industry, since it is critical to human life and has improved tremendously over the last 100 years. If something has gone wrong, they thoroughly analyze the Blackbox, see what's the problem and then put it into their procedures or checklist, so that these problems are not repeated, or they can be avoided.
What can take from that? Every fund manager keeps a journal about decisions taken at that particular time. Later, it helps analyze what worked and what did not. Sometimes, the fund manager would be right, but for the wrong reason. It is to understand and learn. Whatever mistakes we are making on a consistent basis or some big bloopers we could have avoided, they are put into the investment checklist. This actually becomes a reservoir of our mistakes.
Let’s say you have a cricket team and you select the best 11 players. But in the lineup, your best batsman comes at No. 7. Clearly, the score will not be optimal. It happens in investment, too.
You would line-up the portfolio in such a way that is psychologically comfortable, and you justify a risk-return based on that.
John Kelly came up with this beautiful criterion for bet sizing for gamblers in such a way that they don't go bust. It takes the odds and the pay-offs and creates a kind of a number that you should be betting on that particular bet. It is fairly complicated, but easier to do on an excel sheet. It also works for analysts. So, when analysts are looking at recommending stocks, on their own bull/bear case scenarios, the Kelly formula will show which is actually their best recommendation rather than a biased one. This offers strong opportunity for generating alpha.
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