Thursday, March 29, 2018

6 Behavioral Errors in Investing: Prof:Sanjay Bakshi

Gyan on Treadmill dated 29-Mar-2018

It is a pleasure to listen to the investment wisdom of Prof.Sanjay Bakshi. He is one of the rare breed of preachers who are practitioners too. He is the adjunct Professor of Behavioural Finance and Business Valuation at MDI Gurgaon. He is also an ace value investor in the Indian equity market with a portfolio valuation of about 400 Crores. He is credited with identifying multiple value stocks including Relaxo Footwear, long before they caught the investors fancy.

Today while walking on the treadmill in the gym in my apartment, I was listening to his presentation on 7 Behavioural Errors in Investing that he made the IFA Galaxy Knowledge Summit 2015. (IFA stands for Independent Financial Advisors, a group that originated in Chennai)

In his presentation Professor spoke about the following errors, also called as 'Heuristics'. These are behavioural traits and belief systems that impede our decision making in life as well as in value investing. The six errors / biases are blunders people make during our day to day decision making.

Error #1: Availability Heuristics (WYSIATI: What you see is all there is)
We tend to make decisions based on information available to us. Even if the information is irrelevant, we tend to try and make meaning of that information. Most of us never tend to analyse the available information and see if they pass the relevance test. Making solution from irrelevant information tend to us solving the wrong problems. Recency and Vividness are subsets of availability heuristic. For example, when you make an investment decision, you tend to give higher weightage to information that is recently available. He gives example of doctors. All the doctors had studied about the negative impact of smoking when they were studying. However, a study found that the proportion of smokers among doctors increased as they went farther away from chest X Rays. Which meant that skin specialists and orthopaedists tend to smoke more than a cardiologist. Another aspect of this heuristic is that people perceive things are more risky, exactly when it is less riskier, for example, more people buy earthquake insurance immediately after the occurrence of an earthquake. This is an example of vividness. All that images on the TV, tend to make the impact of a quake more vivid.

Our risk map is influenced by availability heuristics. While focusing on recency and vividness, the incremental changes go unnoticed. For example, the risk of extreme weather (which is in the news and hence recent and vivid) is over rated but the risk of climate change (which is gradual, and hence not in news) is underrated, even though the risk is far higher. 

He talks about the scam of Stock Market newsletter where prediction is correct 6 consecutive times. On the 7th time, the recipient of the news letter pays money to buy the subscription. This is explained in this post.

Error #2: Perceptual Contrast
He gives example of people buying a lamp and a car. In both cases you have another option which is 1000 rupees cheaper. But you have to walk 10 minutes to walk to the nearby store. All are ready to walk the extra 10 minutes to get a discount of 1000 rupees on a lamp that costs 10000 rupees. Then he gives an offer of 1000 rupee savings on the purchase of a car that costs 10 Lakhs. To avail this discount you have to walk 10 minutes. In this case, even though the amount of discount is the same in both cases (1000 rupees), in the second case no one is willing to walk an extra 10 minutes.

Perceptual contrast is best exemplified by the concept of Industry PE. If a stock is selling at 30 PE (expensive), where Industry PE is 40, we think the stock is undervalued. However, in reality, both may be overvalued.

One aspect of perceptual contrast is the low contrast effect, where incremental changes go unnoticed. This happened to Kodak, the landline phone, the audio tape, Uber and Taxi industry etc..The change may be very gradual, but the trend is important. For instance, it took almost 15 years for Kodak to die. The idea that the company has been there for a long time doesn't mean that it will go on forever.

Bias #3: Deprival super reaction syndrome.
The anger that a dog shows when a bone is taken out of him is higher than the amount of happiness exhibited when a bone is given. Similarly, the pain of loss of 100 rupees is three times higher than the happiness of gain of 100 rupees. Desperation felt after a huge loss induces people to take higher risks.

Bias #4: Commitment and Consistency
We continue to do things even though we know that is wrong because we do not want to look stupid. We tend to rationalize our decisions. He gives the example of how we rationalize smoking. We may say that it doesn't  apply to me, or that smarter people than us are smoking, or we know someone who smoked regularly and lived a long life, or we say that we may live a short life, but it will be enjoyable....Man is a rationalizing animal. One of our biases is confirmation bias, where we overweigh evidence that support our decisions and underweigh those that counters them.

One of the reasons for commitment is the 'justification of effort'. We do not want to reverse a decision, because we have already incurred significant costs in arriving at a decision.

Investing is a probabilistic activity, mistakes are bound to happen. What is not acceptable is perpetuating those mistakes. 

Lesson? You should be ready to change your mind (decisions and perceptions) once facts change.

Bias #5: Social Proof
The need to align our decisions with that of the crowd is a very powerful behavioural bias. We see that every day in mutual fund managers who tend to buy the same stocks. 

"If you want to do better than the crowd, you should be ready to do things differently from the crowd"

Bias #6: Dopamine (temporary high)
You see this in the later stages of bull market when euphoria takes over and we make decisions based on the 'Dopamine rush'. This makes people credulous, they will believe what they want to believe.

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