How to make rational investing decisions

By Ravi Samalad |  22-07-20 | 
 
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About the Author
Ravi Samalad is Assistant Manager - Editoral for Morningstar.in.

Staying the course by ignoring market noise is difficult. Whether you are a novice or a seasoned investor. Nimesh Chandan, CIO - Equities, Canara Robeco Mutual Fund, shares some practical and valuable advice.

What common mistakes do investors typically make in a market environment like the one we are facing currently?

Myopic Loss Aversion.

While people want to invest for longer, they are worried about the short-term losses. This loss aversion causes them to focus their efforts towards timing the exact top and bottom of the market. It’s very difficult to predict short-term market movements. Tops and bottom are only clear in hindsight. So myopic loss aversion leads to certain decisions by individuals which can impact the overall returns adversely. Also, because they are trying to time the market, they also succumb to the noise in the market.

Confirmation Bias leading to Cognitive Dissonance.

Once investors make a certain allocation, they like to meet people who agree with them or read and focus on news that confirms their previous belief. This is confirmation bias. Ideally, investors should test out their beliefs. They should actively look for a contrary opinion.

If one has taken a decision and if there is any negative news about it that changes the initial thesis, he/she tries to rationalize such things rather than accept the mistake and change the view. This leads to cognitive dissonance. They stay invested in an asset or a security even when the reason they made the investment has changed.

Regret aversion stops them from booking a loss.

In such uncertain times, when trying to get a grip on what is happening on the ground, how must investors sift information from noise? 

After the lockdown, investors have been rushing to collect more information on the ground. They are looking at consumer, dealer and supplier surveys, attending conference calls, etc. They are analyzing the incoming high frequency data. Then there are anecdotes based on personal experiences with something like “I know someone who…”.

It is important to understand the strength and weight of that information.

If you have done a survey in Mumbai among 34 dealers of a consumer company. Most of them tell you that things are bad. Now you extrapolate these results to entire country and conclude demand is extremely bad for this consumer product. Here the strength of the survey is good; but the weight is low because it is just once city which is being surveyed. And Mumbai is the most affected city due to lockdown. Ideally, you have to expand your sample size by covering more cities.

Say you survey 34 dealers across India. 19 of them tell you that things are bad. Now that has lower strength as compared to survey in just one city (Mumbai) but it has better weight.

Typically, we as human beings give a lot of importance to the strength rather than weight of the information being analyzed. It has to be the other way around. If you give too much importance to the strength (noise) of the information you tend to be overconfident and make wrong decisions.

And the information keeps getting updated.

But the source of the information is important.

Suppose you are selecting a car model and you have zeroed down on two brands. You prefer brand A versus brand B after going through all consumer reports. You go to a party and tell you friend that you are planning to buy brand A. The friend tells you that he knows a friend who has gone through a terrible experience with brand A. You have to realize that this is just one input.

Does it really change the number of customers that are satisfied with brand A versus brand B overall?

Besides looking at the strength and weight you have to look at how much the new information changes your prior perception. But, you have to look at the source of the information and how it changes your past perception or initial thesis.

This is where the “this time it’s different” comes into play.

This time it’s different. In this scenario, they ignore historical cycles while making investment decision. They buy into bubbles and sell at the troughs ignoring the negative experiences of the previous cycle.

Everything is always the same. No. History doesn’t repeat exactly, it rhymes. Historically, if people observe that the market has bottomed at 12PE and topped at 28PE, they invest by specifically looking at those numbers. You have to anchor yourself on the previous cycle or the base rates but at the same time adjust yourself from that position based on new information and changes in circumstances.

Is that what you do in your analysis?

We look at the strength versus weight, and when new information comes in, we look at how much it changes our base case.

People who understand the concept of probability tend to have an edge over others.

As fund managers, what kind of biases do you’ll face?

We also face very similar biases as individual investors. However, there would be some differences because the impact of some emotions is less on fund managers because we are managing third party money.

Also, as professionals, we constantly are in discussion to test one’s theory and point out where we could go wrong.

We follow an investment checklist which has everything we look for in a business. It is also a reservoir of our mistakes and decisions.

Our analysts don’t give one target price. They give three target prices based on different scenarios. This helps reduce cognitive dissonance by looking at the negative scenarios. It helps fund managers understand the risk reward payoff of a particular investment.

Whenever a trade is executed, we record the reasons for doing this trade. This helps us understand and improve upon our past mistakes/learnings. It is designed to help us improve our decision-making process.

These are just some practices we follow to keep us in check.

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nagarajan balasubramanian
Jul 24 2020 10:31 PM
 Such general articles do not add value. Using only jargons is not helpful to any ordinary investor.
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