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Treading markets with caution: Not falling for 'relative behaviour' trap

How often have we found ourselves looking at a business more favourably just because its peer is trading at twice the valuation? How often do we sit back and evaluate whether the implicit assumptions that come with high valuations are even achievable?

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By Jigar Mistry  Jun 18, 2021 3:43:54 PM IST (Published)

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Treading markets with caution: Not falling for 'relative behaviour' trap
Imagine that you wanted to buy a subscription to your favourite magazine. Which of the following options are you most likely to opt for? (a) Web-only service priced at $59/year; (b) Print only subscription priced at $125/year; or (c) Print and web subscription priced at $125/year.

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Well, if you chose option c, you are in great company. In his book, Predictably Irrational, Dan Ariely asked the same question to 100 students at MIT’s Sloan School of Management, and 84 percent chose option c. They obviously saw the advantage of the print plus web over the print only offer.
However, if you are confused with the presence of option b altogether, you have a point too. Two options priced the same, but one with a visibly inferior value proposition is a no brainer, right? After all, who in their right minds would choose option b. And, come to think of it, which ‘rational’ publication would even make such an offer?
Dan deals with the subject of ‘relativity’ in a nuanced manner in his book. He has worked for a long in the field of behavioural economics and makes this fundamental observation: “most people do not know what they want unless they see it in context. We not only tend to compare things with one another but also focus on comparing things that are easily comparable—and avoid comparing things that cannot be compared easily.”
Marketers have understood this all along. New York Times ran a story about Gregg Rapp, a restaurant consultant who specialises in the pricing for menus at restaurants. He suggests that restaurants often use “decoys”. For example, they place a really expensive item at the top of the menu, so that the other dishes look more reasonably priced; research shows that diners tend to order neither the most nor the least expensive item, drifting towards the middle. Thus, by creating an expensive dish on the menu, a restaurant can lure customers into ordering the second most expensive choice (which is engineered to deliver a high-profit margin).
To prove his point, Dan ran the same problem by his students after removing option b from the choices above. Since no student had chosen option b in the first place, the end outcome should be the same, right? (i.e., 84 percent students would still go with print + web subscription). However, when presented with just option a and c, 64 percent students chose option a—totally contrary to their earlier choice. Dan concludes that because our minds understand, with absolute clarity, that option c is better than option b, it sub-consciously becomes the best of the three alternatives as well (i.e., we no longer consciously evaluate whether option c is better than option a also).
And come to think of it, it isn’t limited to choosing web subscriptions; it impacts us in our everyday lives. How often have we found ourselves looking at a business more favourably just because its peer is trading at twice the valuation? How often do we sit back and evaluate whether the implicit assumptions that come with high valuations are even achievable?
Last week we introduced our ‘What If’ series—our attempt to answer crazy and fun financial questions that can be answered only with lots of data. We had urged readers to send us some of their questions and received many; thank you for sending them.
Among the questions received, one was: “Markets are hitting highs every day; What IF there was a way to tell if this looks more like 2004 or 2008?" Just so we are on the same page, the market rally started somewhere in 2004 and peaked in 2008 (Sensex rose 3x and small-cap index 7x).
Well, it is an interesting question, and whereas there are no right answers, there are several fun ways to investigate it. Several factors are at play here—global economic cycle, domestic corporate and earning cycle, valuation cycles etc.). While several brokerage houses have published a lot of analysis on how valuations (PE, EV/E, PB etc.) have behaved at different points, we found the following analysis particularly insightful.
We divided the past two decades into three∗ cycles: (a) Years 2004, 2009 and 2016 as ‘start of the cycle’; (b) Years 2010 and 2015 as ‘middle of cycle’; and (c) Years 2008 and 2018 as ‘peak of the cycle’. For all years, we compared the (a) total stocks traded during the given period against (b) the stocks that traded within 95 percent of their 52-week highs. We then juxtaposed it with the situation today.
Historically, at the start of a cycle, on average, 6 percent stocks have been close to their 52-week highs. In the middle of the cycle, that number inches up, but only marginally, to 8 percent. At the peak of the cycle, on average, 29 percent of all stocks that got traded on those days traded within 5 percent of their 52-week highs. That number, for this week, was at 23 percent †.
While this may not be a conclusive data set to predict market tops in and of itself, when looked at in conjunction with several other factors and, it does behove us to tread with caution. It is rather easy at such junctures to be caught up in ‘relative behaviour’—i.e., comparing our portfolio’s performance with several anecdotes of circuit-hitting stocks and getting the feeling of having missed out. In such moments, one might look to “catch up” by increasing the risk on the portfolio, while historically it has precisely been the time that one should have been doing the exact opposite.
PS:
If you are wondering which “irrational” publication was smart enough to include that decoy choice that we mentioned in paragraph one, it was The Economist. Well, it was fun trying to answer this question, please do send across more, if you have them.
–∗ Data chosen for 5-day average as follows: For 2004 cycle, data is for 30th Aug to 3rd Sept 2004 and so on for the rest of them. 2008 cycle: 30th Dec 2007 to 4th Jan 2008; 2009 cycle: 10th May to 15th May 2009; 2010 cycle: 1st Nov to 5th Nov 2010; 2015 cycle: 23rd Feb to 28th Feb 2015; 2016 cycle: 12th Jun to 17th Jun; 2018 cycle: 8th Jan to 12th Jan 2018 and Now: 11th Jun to 15th Jun 20216
As of 15th June 2021
Jigar Mistry is the co-founder of Buoyant Capital. The views expressed in the article are his own
Disclaimer: Information in this letter is not intended to be, nor should it be construed as investment, tax or legal advice, or an offer to sell, or a solicitation of any offer to make investments with Buoyant Capital. Prospective investors should rely solely on the Disclosure Document filed with SEBI.

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