Haven’t seen anything yet, or have we?

Letter # 46, 18 June 2021

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 USD59/year; (b) Print only subscription priced at USD125/year; or (c) Print and web subscription priced at USD125/year.

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% chose option c. They obviously saw the advantage of 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 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 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 (1) about Gregg Rapp, a restaurant consultant who specializes 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% students would still go with print + web subscription). However, when presented with just option a and c, 64% 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 (2) 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, 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 (3) 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 5% of their 52-week highs. We then juxtaposed it with the situation today.

Historically, at the start of a cycle, on average, 6% stocks have been close to their 52-week highs. In the middle of the cycle, that number inches up, but only marginally, to 8%. At the peak of the cycle, on average, 29% of all stocks that got traded on those days traded within 5% of their 52-week highs. That number, for this week was at 23% (4).

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 (5) and (6), 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 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.

 

 Notes:
(1) Restaurants Use Menu Psychology to Entice Diners – The New York Times (nytimes.com)
(2) What IF – Buoyant Capital
(3) 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
(4) As of 15th June 2021
(5) Arguments matter, but stories sell better – Buoyant Capital
(5) https://www.buoyantcap.com/what-if/
This letter was originally published here: Treading Markets With Caution: Not Falling For ‘Relative Behaviour’ Trap (cnbctv18.com)

Disclaimers:
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 Disclosure Document filed with SEBI. Any description involving investment examples, statistical analysis or investment strategies are provided for illustration purposes only – and will not apply in all situations and may be changed at the discretion of principal officer. Certain information has been provided and/or based on third-party sources and although believed to be reliable, has not been independently verified; the investment managers make no express warranty as to its completeness or accuracy, nor can it accept responsibility for errors appearing herein.

What IF

Letter # 45, 11 June 2021

Imagine you had a magic wand, which gave you the amazing power to time the market with complete accuracy, but with a small glitch—you can only trade indices (not individual stocks) and must always stay invested. Over the past two decades, how much do you think the magic wand would have been worth? i.e. how high would the returns have been had you sold at top and bought at bottom? For context, the Sensex has returned 14% CAGR and BSE Small-cap index 16% CAGR since 2003. A brief detour before we return to answer this.

Randall Munroe studied until the age of 22; first at a high school that specialized in mathematics and science, and graduated with a degree in physics. It was like a dream come true when Langley Research Centre, NASA, hired him as a programmer and roboticist. However, in 2006, NASA ‘ran out of money’ (1) to rehire him and had to let him go within a year.

On the basis on what I wrote above, would you be surprised to read this bio of Randall in Wikipedia: Randall Munroe is an American cartoonist, author, and engineer.” That’s right… 15 years later, he is a “cartoonist” first, “author” later, and the education that landed him the NASA job, last!

Randall went on to write an extremely successful blog titled xkcd (not an acronym) that bore the tagline ‘A webcomic of romance, sarcasm, math and language’. His webcomic had already started garnering 70 million hits a month by October 2007.

He also wrote a blog titled ‘what if’, where he answered totally absurd questions regarding math and physics. Questions like, ‘what if… the earth stopped spinning, but the atmosphere retained its velocity’ or ‘what if… I took a swim in a typical spent nuclear fuel pool; how long can I safely stay at the surface?’ or ‘what if… everyone on earth aimed a laser pointer at moon at the same time, would it change its colour?’

While the questions are absurd, Randall’s answers are well researched, nuanced, and profound. In 2014, he published a collection of some of the questions in a book titled ‘What if’, which reached the top of New York Times bestsellers list within a month and got featured as the ‘Amazon Best Book of the Month’. Randall also has a tremendous sense of humour, which makes his book an informative as well as a fun read for people of all ages. Do give it a shot.

I am trying to follow in Randall’s footsteps by taking up random questions in finance that can be answered with tons of data.

And, the answer to the magic wand question is, a whopping 31.4%! Yes, that is what the magic wand was worth. You would have invested in the Sensex between December 2003 and June 2004, December 2007 and February 2009, October 2010 and December 2011, and December 2017 and March 2020 (and long Small-cap index all the other times).

The elephant in the room however is…we don’t really have a magic wand, do we? But we have the next best thing–the benefit of hindsight.

So, let’s formulate this. We start with buying one index (say small cap) and hold it till it outperforms the other (Sensex) by certain percentage points. Once it does, we swap (sell small cap and buy Sensex), and repeat. We need to optimise for just one variable–that outperformance number at which we will flip and switch.

Assuming we switched after 20% outperformance, the strategy would have generated 18% CAGR– higher than individual returns of Sensex or the Small-cap index, but a far cry from the ‘magic wand’ number. The chart below gives the returns that one would have generated under different thresholds of outperformance. As we can see, the closest we could get to the magic wand number is by switching out when the outperformance hits 80% (i.e., we do not sell small cap until it outperforms Sensex by 80%, and vice-versa).

This exercise highlights a few important aspects: (a) The market operates in cycles. There are times when large caps outperform mid and small caps, and vice-versa. Over the past 2 decades, there have been 9 distinct cycles of reversals. While we are in a cycle, it appears as if things will likely never reverse (small-cap cycle now or large-cap cycle between December 2017 and March 2020), but historically, the cycle has always, invariably, and inevitably, reversed.

(b) For a portfolio to outperform over a longer period, a judicious mix of large, mid and small cap businesses is essential. Even with a suboptimal switch (after 20% outperformance), returns have been higher than either the Sensex or the Small-cap index. Our recency bias prevents us from noticing the cyclical nature of the ‘trend’ that is ongoing for a few years – say between December 2017 and March 2020, the small-cap index underperformed ferociously (down 50% vs. 13% for Sensex). So marketing geniuses came up with heuristics like ‘there are only 20-25 investible stocks in India’, ‘buy strong growth, high ROE large caps, and they will generate strong returns forever’ etc. Even professional money managers had given in, when large caps formed more than 75% of allocation in many multi-cap mutual funds (90% in a few cases).

(c) At the cost of repetition from my previous letters, there are no fixed formulae that allow one to generate superior long-term returns. A cycle has reversed within 5 months (December 2003-May 2004) and has, at times, sustained for years (May 2004 to December 2007). An upcycle has generated 70% outperformance (April 2003 to December 2003) as well as 330% outperformance (May 2004 to December 2007). A down cycle has generated 9% underperformance (December 2003-May 2004) as well as 37% underperformance (December 2017-March 2020).

The idea behind this exercise is one, to have fun with data (like Randall does) and two, to be aware that like the previous cycle (of large caps outperforming) has not lasted, the current cycle (of small caps outperforming) will also eventually change. I would have told you when, but then…I am missing my magic wand!

PS: I intend to make ‘What IF’ a routine part of my writing. Do write back to me if you have some crazy fun financial questions that can be answered only if you have tons of data (we already do!). Also, remember the model where switching at 80% outperformance generated the highest returns? In that cycle, today, we are already at 60% outperformance by small caps!

Notes:
(1) Many news things, some overdue – xkcd
This letter was originally published here: Small caps outperforming Large caps big time; what does history suggest? – cnbctv18.com

Disclaimers:
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 Disclosure Document filed with SEBI. Any description involving investment examples, statistical analysis or investment strategies are provided for illustration purposes only – and will not apply in all situations and may be changed at the discretion of principal officer. Certain information has been provided and/or based on third-party sources and although believed to be reliable, has not been independently verified; the investment managers make no express warranty as to its completeness or accuracy, nor can it accept responsibility for errors appearing herein.

Formulae don’t work; here is why

Letter # 44, 4 June 2021

The year is 1988 and tennis fans are keenly watching two players – Andre Agassi, ranked No. 3 (1), and Boris Becker, ranked No. 4. By 1989, they would face each other on three separate occasions and Becker would win all the three matches (Agassi did not win even one set in two matches). By the end of 1989, Becker went on to occupy No. 2 spot on ATP rankings and Agassi was pushed to No. 7.

Then… something snapped. They played three matches in 1990, and as if by a stroke of luck, Agassi won all three (won 2 matches in straight sets). In 1991, they played two more games, and again, Agassi won both. Over the course of their careers, they faced each other on 14 occasions, and Becker managed to win only 4 matches or just one more after three wins by 1989, and Agassi won 10! What happened there? A brief detour before we go there.

In the fall of 1948, most of the newly arrived post-grad math students at Princeton University were cocky, but one was even cockier, writes Jonathan Aldred in License to be Bad. Still in his twenties, he made an appointment to see Einstein to discuss a few things. The meeting lasted an hour, at the end of which, Einstein grunted, “you’d better study some more physics, young man.”  That young man was John Nash, who later went on to win the Nobel prize for his contribution to ‘game theory’. Initially, Nash had to face lot of criticism and was about to give up, until his PhD supervisor decided to present Nash’s thesis in the form of a story.

Two members of a criminal gang are imprisoned separately and cannot communicate with each other. The police have enough evidence to convict both of a minor crime, but not the major one that they suspect them of having committed. They offer both the following deal: “confess and implicate your partner; you receive immunity from prosecution, while your partner gets 10 years.” If both stay silent, both get two years for the minor crime. The dilemma for both prisoners is, if the other speaks out, I get 10 years, and he gets a free pass and vice versa. The best course of action, obviously, is to stay silent. But the question is, should I take the deal first, under the assumption that the other will take it first?

In 1950, no one had an inkling that the Prisoner’s Dilemma would later become the most influential game in game theory and was widely practised in the nuclear arms race between the US and USSR. In 1955, however, the philosopher Bertrand Russell took the game theory forward (in context of nuclear disarmament) by publicizing a game called Chicken. Imagine US and USSR are rival hot-blooded drivers, speeding towards each other down the middle of a long, straight road. If neither moves out of the way (‘chickens out’), both will die. If one chickens, both survive; but the one who moves out earns the everlasting contempt of his rival.

Coming back to Agassi vs. Becker. Agassi later revealed in an interview (2) that he kept watching the tape of Becker’s service and noticed a tell. Just as Becker was about to serve, he would stick his tongue out–in the middle if he was serving up the middle and to the left if he was serving wide. Having discovered his tell was only half the victory; resisting the temptation of reading his serve for majority of the match and rather choosing the moment when he could use that information to break the game open was harder.

Now, what do tennis and game theory have to do with investments? Over the course of the past few months (3), I have vehemently argued (with data) that in markets there are no formulae (buy high growth companies that generate strong return ratios or avoid commodities of PSU stocks etc.) that allow the portfolio to outperform across market cycles. I have also written that historical data does not support the several myths–a portfolio always outperforms if you buy leaders, buy companies with highest ROCEs, buy only large-cap businesses or small-cap business etc.

The reason that a fixed formula cannot work is because the very knowledge of its existence will make the formula worthless. Let’s assume that everyone starts believing that say… buying “high growth strong return ratio companies” will result in outperformance at all times, and they start buying. While demand for shares of such companies rises, supply remains limited; as a result, their stock prices catapult swiftly over a short period of time.

At certain point, new investors realize that these businesses are quoting at stratospheric valuations (earnings can rise only so much) and decide to wait. Now, if earnings growth is cyclical and starts shrinking, stock prices will collapse (Nifty 50 in 1970s, tech bubble in early 2000s). If earnings rise at a steady pace, the stock price stops rising for multiple years till the valuations start looking decent again (Coca Cola, Walmart, Hindustan Uniliver and Colgate between 1998 and 2010). Investors are in a constant state of Prisoner’s Dilemma–do I keep buying under the assumption that everyone still believes that this formula works? And, if I ‘chicken out’ while everyone else continues to believe the theory, I stand to miss out.

Agassi knew that if Becker found out the ‘tell’ was made, the advantage would be lost. He could have decimated Becker by exploiting the tell on every serve; but, apparently, that was still too large a risk to take. He chose to use it just for those crucial moments.

Now take RenTec for example. The firm founded by Jim Simons, which has generated 66% returns (pre-fees)–exceptional returns– between 1988 and 2018. They did manage to build something akin to a formula (albeit not a fixed one, but one that was ever evolving based on new information) to beat the market across cycles. RenTec used to charge 5% fixed fee and 44% performance fees (highest fees ever in the asset management business) and yet, when they found that the strategy is not scalable enough, they stopped running clients’ money altogether (they just ran their own money).

Now, compare that to the “free advice” you get from self-proclaimed market experts on how doing a, b or c will get the job done. While the narrative is important on how decisions are made, the narrative that a few fixed sure shot formulae help a portfolio outperform the market on all occasions have neither worked in the past and are unlikely to work in the future.

Notes:
(1) Ultimate Tennis Statistics – Rankings Table
(2) WATCH: The amazing story of how Andre Agassi read Boris Becker’s serve by watching his tongue – Tennis365
(3) All historical letters one can find here: blog – Buoyant Capital
The letter was originally published here: In investing and life, change is the only constant – cnbctv18.com

Disclaimers:
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 Disclosure Document filed with SEBI. Any description involving investment examples, statistical analysis or investment strategies are provided for illustration purposes only – and will not apply in all situations and may be changed at the discretion of principal officer. Certain information has been provided and/or based on third-party sources and although believed to be reliable, has not been independently verified; the investment managers make no express warranty as to its completeness or accuracy, nor can it accept responsibility for errors appearing herein.

Letting the facts interrupt a good story

Letter # 43, 28 May 2021

Over years of investing in equity markets, have you amassed a few sets of rules and formulae that have always turned profits for you? That ONE formula that always seems to work? How about buying companies that have the highest return ratios? Or investing in leaders of a sector? Something that just works, irrespective of market cycles!

Adam Grant, in his book, Think Again makes remarkably interesting points on the matter. This story from him will help set the context.

In 1949, a massive fire had engulfed the forest around the Missouri river, with flames stretching as high as 30 feet. After a while, it became evident to the smokejumpers that fighting was no longer an option, and they will have to run for their lives. But the fire was catching up on them fast and it was an uphill climb. That’s when Wagner Dodge did something that baffled others.

Instead of outrunning the fire, he took a matchbox and burnt the grass around him. He then dampened a towel and lay face down for fifteen minutes in the vacant space as the fire raged directly above him. Essentially, he had taken away the fuel that a fire needs to keep going. This method did not make sense to the crew, which chose to follow the textbook. Tragically, twelve smokejumpers perished. They were taught to douse a fire, not to start one.

While that was sad, what was bizarre was that bodies of a few smokejumpers were found with their equipment still on them. A backpack, 25-pound chainsaw and other tools. While trying to outrun a fire, in an uphill climb, why would they not simply ditch the equipment? One firefighter later explained that discarding your tools doesn’t just require you to unlearn habits and disregard instincts, but it’s perceived as admitting failure and shedding part of your identity. You don’t fight a fire with bodies and bare hands; you fight it with tools, which become a part of your existence.

Adam insists that we don’t just hesitate to rethink our answers, we hesitate at the very idea of rethinking.  Seth Stephens-Davidowitz carries this concept further in his book Everybody lies. In 2013, a reddish-brown horse (no. 85) was among the 152 horses being auctioned in upstate New York. The horse’s current owner was an Egyptian beer magnate, Ahmed Zayat, who wanted to sell no. 85 and buy other horses. To help him, Ahmed had hired a team of experts – a small firm called EQB, headed by Jeff Seder.

After a few days of evaluating, Seder’s team told Ahmed that they were unable to recommend any horse to buy in this auction, but had a near-desperate plea–he cannot, ABSOLUTELY POSTIVELY cannot, sell horse no. 85! Thankfully, Ahmed paid heed and retained the horse (later renamed American Pharoah). American Pharoah went on to become the first horse in more than three decades to win the Triple Crown! What did Seder know that apparently no one did?

Historically, people had believed that the best way to predict horses’ success was to analyse their pedigree. Being a horse expert meant being able to rattle off about the horse’s father, mother, grandparents, siblings, etc.

However, Seder (a Harvard grad) found that pedigree wasn’t a consistent predictor of a successful race horse.  He was more interested in data and started collecting it, for years on. He measured the size of horses’ nostrils; he did EKGs to examine their hearts and cut the limbs off dead horses to measure the volume of their twitch muscle. He grabbed a shovel to determine if the size of a horse’s excrement had any correlation to its wins (had it lost a lot of weight before a race?). He then got his big first break when he decided to measure the size of their internal organs. Since technology didn’t exist back then, he created his own portable ultrasound. The results were remarkable. He found that the size of a horse’s heart, especially the left ventricle, was a massive predictor of a horse’s success – the single most important variable.

At the New York auction, of the horses on offer that day, No. 85 was 56th percentile on height, 61st percentile on weight, 70th percentile on pedigree, but a whopping 99.6th percentile on left ventricle. The data screamed that no. 85 was one in ten thousand or even one in a million horse.

Now let’s come back to the question I had asked at the start of this letter: can you think of that one winning formula that has always helped you generate a profitable investment? Earlier this month (1), I had argued that boiling down an investment framework to bite-sized rules has historically not worked. Today, let us look at a similar euphemism: “Buy businesses that generate strong return ratios, and they will continue to outperform the markets forever,” they say.

Whereas it is obvious that one would not want to invest in businesses that cannot earn their cost of capital. However, I humbly submit that historical return ratios are of little help as sole predictors of investment returns. The chart below is the frequency distribution of the stock returns of 674 companies (with market cap above INR5bn and those that have a 10-year share price history). We took the average of return on capital employed (ROCE) between 2007 and 2010 (so that one year does not have an outlier effect) and compared their stock returns over the next decade (2011 to 2021). As the chart indicates, returns aren’t materially different across ROCE buckets.

Data indicate that you cannot predict future returns based on historical return ratios of businesses. How then, you might wonder, could the high ROCE fallacy have started? I believe some expert would have looked at stocks that have done well over the last decade and studied common traits – say, all had great return ratios a decade back. He then would have concluded that buying businesses with great return ratios results in superior investment returns.

However, we miss the huge survivorship bias here. Humour me for a bit. One could look at all the successful companies, compare their traits and conclude that ‘all of them are successful because they took outsized risks.’ Fair observation. However, there are companies that took outsized risks and perished on account of an unfavourable outcome. Unfortunately, they are no longer part of the universe you are analysing (because they went bankrupt). If you think that no one does that, I can list two books that were written explicitly stating that, and they sold more than 4m copies!

Similarly, businesses that returned superior investment returns may have a common trait–they generate superior return ratios. However: (a) all businesses that generated strong returns ratios a decade ago did NOT result in superior stock returns; and (b) there is a subset of stocks that delivered superior investment returns, but were NOT generating high return ratios a decade ago.

We should be cautious in what we choose to believe in as it becomes an unshakeable part of our investment framework (like smokejumpers clinging to their equipment). Adam concludes that ‘once we accept the story as true, we rarely bother to question it.’ The more we rely on data, rather than narratives, the better off we are in the long run. Reducing an investment framework to bite-sized rules sounds interesting in meetings and webinars; their efficacy in long-term cross-cycle investment returns is sadly rather poor.

 

Notes:
(1) Heuristics help open doors, but are bad for investments – Buoyant Capital
This letter was originally published here: Higher return ratios lead to superior returns? Think again… – cnbctv18.com

Disclaimers:
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 Disclosure Document filed with SEBI. Any description involving investment examples, statistical analysis or investment strategies are provided for illustration purposes only – and will not apply in all situations and may be changed at the discretion of principal officer. Certain information has been provided and/or based on third-party sources and although believed to be reliable, has not been independently verified; the investment managers make no express warranty as to its completeness or accuracy, nor can it accept responsibility for errors appearing herein.

Arguments matter, but stories sell better

Letter # 42, 21 May 2021

Of the two bad outcomes, which one do you reckon is worse: (a) a virus that kills more people, but spreads slowly; or (b) the one that spreads faster and kills fewer people.

If that sounded like the “blinding glimpse of the obvious” and you answered it right away with option b, I’d say Kudos! The onset of covid wave two (a more virulent and less pathogenic strain) has proven in practice, what we can only theoretically calculate in an excel.

But, the mathematic around it can be a bit of a stretch to wrap our brains around. After 20 rounds of infections, (a) above with case fatality (CFR) of 2% and reproductive rate (R0) of 1.4 results in 800k deaths, whereas (b) with CFR of 1% and R0 of 1.5 results in 900k deaths. As I said, both are bad outcomes, but one that spreads mildly faster (1.5 vs 1.4), but has only half the CFR (1% vs. 2%) still produces 13% higher deaths at end of 20 rounds (and 70% higher deaths after 30 rounds).

Math aside, Michael Lews in his book Premonition writes George W. Bush, the 43rd President of the US, was aware that freakishly terrible events can and do happen. After all, he had presided over the deadliest attack on American soil and the most destructive American natural disaster in a century (Hurricane Katrina). Which is why he moved to action when he read John Barry’s book The Great Influenza in the summer of 2005. He put in place a three-part pandemic strategy, made sure US Congress allocated USD7bn to it and set up a team of experts to get cracking on it.

That team included a doctor named Carter Mecher. Carter had a unique way of looking at problems and finding a ‘logical’ solution to them. Whereas the accepted opinion was to lower the R0 below 1, Carter ran various scenarios—what happens when you isolate the ill or quarantine entire households, follow social distancing among adults or use antiviral drugs. Nothing seemed to work. And remember, this was 2006; they hadn’t heard of covid yet.

Then, Carter noted that a communicable disease fell off the cliff when you… ‘shut the schools!’ How can such a small change drive such a large fall, he wondered. But then he noticed that on an average day, school busses carried twice as many people as the entire US public transport system. And once in school, the kids don’t practice social distancing—they aren’t aware and the schools aren’t built in a way that social distance can be maintained.

Coming to this conclusion was one part, but convincing relevant authorities was another matter. They argued back, “it is not going to work; kids will start hanging out at malls, crime rate will skyrocket, poor kids will starve” etc. Carter argued back: (1) crime rates fell on weekends when kids were out of school and juvenile crime peaks at 3:30 pm on weekdays (when schools end); and
(2) kids won’t starve. 30mn kids attended school, but his survey showed that only one in seven parents would have a problem feeding their child without the school programme. That is not 30mn kids, that’s just 3mn—a problem that can be managed with food stamps. But the ‘logical argument’ wasn’t getting him anywhere.

At some point, Carter decided to stop appealing to reason and began appealing to emotions instead—he stopped making the argument and began to tell a story. He created a picture, a 2,600 square-foot home, but with same population density as an American school. A single-family home suddenly started looking like a refugee prison in the next slide. He had started getting their attention now.

He would put a heart-tugging photo of a nine-year old girl in 1918, smiling and dressed for church; and in the next slide describe how she and other children would end up as bodies, stacked like cordwood. As the last straw, he made the problem personal: If there is a pandemic anything like the one in 1918, how many of you would send your kids/grandkids to school? Now, they were invested in the outcome. Finally, he didn’t care who got the credit, and voila, the report finally saw the light of the day!

For Carter, his story got the work done when his arguments failed. Let me try and do the same with markets. The argument first—of the 3,000 odd stocks that got traded yesterday, nearly half quoted within 15% of their 52-week highs, and over 500 stocks were within 15% from their all-time high. Does that sound like the market is heating up too fast? How about I sweeten it up for you with this chart?

It contrasts rolling one-year returns of three indices – BSE Sensex, Mid cap and Small cap (when mid and small-cap indices outperform Sensex, it shows up on the positive axis, and vice-versa). On a one-year performance basis, as of yesterday, the small caps have outperformed Sensex by a whopping c60%—the highest in the past 10 years. Now that the argument is made, let me tell you a story.

Pabrai Funds invested in Rain Industries in mid-2015 when its market cap was USD175mn with revenue of USD1.9bn in 2014. Mohnish, who runs Pabrai Funds, thought that Rain could generate a post-tax profit of USD175mn in not too distant a future. He bought 10% of the company, but was happy to buy even 30% if regulations permitted it (1). Rain indeed earned USD165mn in FY18 and its market cap zoomed to over USD2.35bn—12x return in just three years. Did he sell there? No. What stopped him from selling was that he got to know the business and its amazing leader Jagan Reddy. “It would be very dumb to say good-bye to such a gifted leader and capital allocator,” wrote Pabrai.

Rain made a high of INR461 in Jan-2018 and by Jan 2019, it was down 75%. The stock kept falling further till it bottomed in Mar 2020 at INR54—down a whopping 88% from highs just two years back. Mohnish writes that in hindsight, it was likely a mistake not to lighten up when the stock went over INR400/share.

The idea of the story is not to deride Mohnish; if anything, I am a great fan of his books, his investment style and his way of life. The idea is to learn from mistakes—ours and those of others.

When I had argued in Sept2020 (2) that the market is too focused on ‘growth at any price’ companies and small caps have underperformed Sensex by 30%, there were hardly any small-cap stories that were getting pitched to us. The scenario is largely reversed now. Increasingly, all we get recommended these days are great small-cap stories that have tripled over the past year, but can double from here as well.

I wouldn’t say that just because small caps’ outperformance has historically reversed from current levels, the small-cap index has topped. I am also not arguing that just because Rain did not work out for Mohnish, any other story will not work for us. But, the battle is half won in knowing that it is in times like these (when just a week’s research is generating superlative stock returns, the entire market is focussed on the next multi-bagger opportunity, that buying the dip almost always makes sense) that we are at our most vulnerable to commit our largest mistakes. Markets may not be at their top, but it might behove us to be at the top of our vigil.

Notes:
(1) Mohnish Pabrai on Rain Industries – Alpha Ideas
(2) Ant colonies, self-organized criticality and small-caps – Buoyant Capital
The letter was originally published here: SmallCap Index hits all time high; how should investors approach it – cnbctv18.com

Disclaimers:
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 Disclosure Document filed with SEBI. Any description involving investment examples, statistical analysis or investment strategies are provided for illustration purposes only – and will not apply in all situations and may be changed at the discretion of principal officer. Certain information has been provided and/or based on third-party sources and although believed to be reliable, has not been independently verified; the investment managers make no express warranty as to its completeness or accuracy, nor can it accept responsibility for errors appearing herein.

Heuristics help open doors, but are bad for investments

Letter # 41, 14 May 2021

“He was unprecedented for a European business leader – a Scandinavian who combined old world manners and language skills with American pragmatism and an orientation for action,” writes Phil Rosenzweig in his book The Halo Effect. The press could not get enough of Percy Barnevik, the CEO of ABB, in the mid-1990s as its revenue almost doubled, profit tripled and market cap breached the USD40bn mark between 1988 and 1996.

It started with Sweden’s ASEA and Switzerland’s Brown Boveri merging in 1988; they integrated at break-neck speed, saving millions of dollars in costs. Plants were closed, jobs were cut and overheads slashed, while acquisitions rose. By 1994, ABB had consolidated in Western Europe & North America, and expanded in Emerging Markets, with Percy at the helm.

In early 1990s, magazines like Long Range Planning, Forbes and Business Week gushed over Percy’s management style; academics at management schools praised his persona and Korean Management Association named him ‘world’s best honoured top manager’ – he was getting an award for getting the most awards!

And then came the downfall, starting 1998. The spree of acquisitions, the unrelated expansion (into financing arm, etc.) and the litigations (asbestos) hurt ABB. The size of the problem grew so large that ABB had to sell its petrochem business, its finance division and take unprecedented loans. By 2003, the company was a mere shadow of its previous self, as Jurgen Dormann, ABB’s Chairman remembered, “we had a lack of focus as Percy went on an acquisition spree. The company wasn’t disciplined enough.” Then, managers recalled poor coordination among countries and dysfunctional competition. The board joined the chorus on how Percy had ‘monopolized the flow of information’. By now, the once superstar had to give up more than 60% of his pension pay and his legacy was in tatters.

It’s a nice story—leaders are important, but judging whether a leader is great from the fact that a company has been successful is breaking down a complex problem into bite-size theories. To me, that begs a larger question, given that we are aware that some relationships of cause and effect are complex in nature, why do we have the urge to break them down into heuristics?

And, it is not just about distant corporations and CEOs; our financial markets too are inundated with investment theories that sound simple, but with little effort, we know them to be totally wrong. Over the past few letters, I have written how frameworks that sound simple (buy growth companies with high RoE, don’t buy PSU, don’t buy commodity companies) do not actually work in real life. They are largely a hoax, meant to make the financial guru to sound intelligent and for marketing guys to be able to sell you a product.

Today, let us look at one more of such truisms, “Times are uncertain; stay invested with the leaders in each sector; your portfolio will emerge stronger from the crises.” Over the years, chances are high, that you might have come across someone making similar claim.

The table below summarizes the leading company by revenue (in fiscal 2011) in different sectors. Now imagine one created an equal weight portfolio, investing the same sum in all companies that were leaders a decade ago. This portfolio would have returned ~16% CAGR, a superior return compared to 10% CAGR in Nifty.

However, had one created a similar equal-weight portfolio of contenders, the returns would have been a staggering 22%. To put things in perspective, the ‘contender’ portfolio would have been up 6.6x over the previous decade versus the ‘leader’ portfolio, which would have been up 3.5x. The leader portfolio underperformed the contender portfolio by a staggering 47% in a decade.

We discussed last week (1) how reducing an investment framework to narratives (that sound intelligent) does not hold the test of numbers over time. The result above debunks a similar myth that has been doing the rounds in the world of investments for quite some time now.

As to the broader question of why the urge to break down a complex relationship into bite-size theories that aren’t true, Elliot Aronson, an American psychologist, has a beautiful answer in his book The Social Animal. He observed that “people are not rational begins so much as rationalizing beings. We want explanations. We want the world around us to make sense.”

Experts appearing on CNBC will sound a lot more intelligent if they explain half a point drop in a stock with something that sounds plausible (albeit inaccurate) rather than suggesting that on any given day, stock price fluctuations are more easily explained away with a Brownian motion. That need for the world around us to make sense compels us to form heuristics; it makes our lives easier. It gives us the confidence that we will be able to open a door to a room that we have not previously entered. In life, heuristics serve a useful purpose.

When it comes to investments, however, each situation is different from another. And, while broad rules do apply, boiling down a framework to these rules (buy the leaders, buy high growth high ROE companies, don’t buy PSU etc.) does not work. People who propagate them do a great disservice to the overall investment clan.

At the end, one might have a question—investing in the contender portfolio will help generate superior returns in the next decade, right? Sadly, if one did the same in the FMCG sector in the past decade (buying Nestle instead of the leader Hindustan Unilever), one would have underperformed by a whopping 45%. While trying to debunk the notion that formulas do not work, I am not about to introduce a formula that I think works. Investing is simple, but condensing it down to heuristics is a recipe for disaster.

 

Notes:
(1) Numbers matter, not the narrative – Buoyant Capital
This letter was originally published here: https://www.cnbctv18.com/market/heuristics-help-open-doors-but-are-bad-for-investments-9299131.htm

Disclaimers:
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 Disclosure Document filed with SEBI. Any description involving investment examples, statistical analysis or investment strategies are provided for illustration purposes only – and will not apply in all situations and may be changed at the discretion of principal officer. Certain information has been provided and/or based on third-party sources and although believed to be reliable, has not been independently verified; the investment managers make no express warranty as to its completeness or accuracy, nor can it accept responsibility for errors appearing herein.

Numbers matter, not the narrative

Letter # 40, 7 May 2021

Let’s start with a fun exercise. Based on the past 20-years’ stock returns, match the following companies to the following returns (without looking them up):

Companies: (a) Hindustan Unilever, (b) Nestle, (c) Colgate, (d) Infosys, (e) JSW Steel and (f) Vedanta.

Stock returns (CAGR): (a) 35%, (b) 25%, (c) 21%, (d) 19%, (e) 18% and (f) 15%.

Let me share a couple of interesting stories, before we come to the results.

Philip Tetlock, a professor of psychology, in his book Expert Political Judgment writes that he spent 15 years (1988 – 2003) studying the decision-making process of 284 experts. He defined experts as people who appeared on television, were quoted in newspaper & magazine articles, advised governments & businesses, or participated in punditry roundtables. All of them were asked about the state of the world; all gave their prediction of what would happen next. Collectively, they made over 27,450 forecasts. Tetlock kept a track of each one and calculated the results. How accurate were the forecasts? No better than dart-throwing chimpanzees!

You might think that people may not be great at making predictions, but when it comes to facts, they know their stuff, right?

Hans Rosling, a renowned medical doctor and public educator, in his book Factfulness asks 12 (multiple choice) fact questions about the world (how many girls finish primary education, how much population lives in low-income countries, etc.) to a variety of people (12,000 people in 14 countries in 2017). On average, they scored just two correct answers of 12. No one got a perfect score and a stunning 15% scored zero.

Respondents included medical students, teachers, scientists, investment bankers, journalists, senior political decision makers. The most appalling results came from Nobel laureates and medical researchers. These were not just wrong results, but they were systematically wrong. The test results were not random, they were worse than random. Chimpanzees (who have no knowledge at all) would have done a better job. He writes, “every group of people I ask thinks the world is more frightening, more violent and more hopeless–in short, more dramatic–than it really is.”

How is it that well-educated people with access to all the data would score worse than chimpanzees in their knowledge of facts or their forecasts? Rosling writes that only ‘actively wrong knowledge’ can make us score so badly. We build a narrative of the world view based on what we hear in the news, what we see on television and who we interact with; this makes us form a world view that is different from reality.

However, Daniel Kahneman, in his book Thinking fast and slow, has a more nuanced answer. He writes that our cognitive processes are divided in two modes of thinking: (a) thinking – traditionally referred to as intuition (system 1); and (b) reason – described as slow and rule governed (system 2). Whereas system 1 operates automatically, quickly, and effortlessly with no sense of voluntary control, operations of system 2 require concentration. And, although we like to think of ourselves as having sturdy system 2 ability, in fact much of our thinking occurs in system 1.

Now, answers to the quiz. Ranking from highest to lowest stock returns: (a) Vedanta – 35% CAGR, (b) JSW Steel – 25% CAGR, (c) Nestle – 21%, (d) Colgate 19%, (e) Infosys – 18% and (f) Hindustan Unilever – 15%.

You might think that 2002-08 was a super-cycle–a once in a century event, which skews returns. Here are the returns for the past five years–JSW Steel 42%, Vedanta 32%, Nestle 25%, Hindustan Unilever 24%, Infosys 20% and Colgate 14%.

These numbers may appear counter intuitive; after all, how can a capital-intensive commodity business outperform a consumer staples or an information technology business over a 20-years’ time frame? The people who Tetlock tracked and Rosling spoke to might appear distant, but haven’t we, over the past few years, been fed a certain narrative (companies with higher revenue growth with strong return ratios outperform in ALL market conditions or don’t buy commodity companies or don’t buy PSU stocks) that needs to be seriously questioned after these results?

Well narrative aside, numbers have always told a different story, i.e., if we were willing to listen. In the future, at some point of time the returns of commodity businesses will likely look sub-par, but therein lies the important lesson. I am reproducing the table (updated for latest data) that I had written about in the December 2020 letter (1). Over different market cycles, different sectors tend to drive (or lag) indices and the narrative that there could be ‘one investment strategy that can beat the markets at all times’ is largely a hoax.

However, if numbers spoke that loudly, why would a lot more investment managers not include cyclicals as part of their investment framework? Because we have the recency bias and until recently (a year back or so), commodities did not look like an investible asset class. The narrative of a framework that included cyclicals was very difficult to sell to people who would invest in funds.

Morgan Housel summarises it well when he writes, “few people make financial decisions purely with a spreadsheet. Most make them at the dinner table or in a company meeting. Places where personal history, your own unique view of the world, ego, pride, marketing and odd incentives are scrambled together into a narrative that works for you”. Marketing experts that sell financial products are aware that building a simple narrative has a stronger chance of generating a sale. Paraphrasing Kahneman – we might think we are deploying reason (system 2) while making a decision, but in fact, much of our thinking happens through intuition (system 1), which is gullible to narrative. For system 1, narrative matters more than numbers, which guarantees a sale; but for generating superior long-term investment returns, the numbers will always matter more!

Notes:
(1) Jailing short sellers, capital returns and long-run cycles – Buoyant Capital

Disclaimers:
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 Disclosure Document filed with SEBI. Any description involving investment examples, statistical analysis or investment strategies are provided for illustration purposes only – and will not apply in all situations and may be changed at the discretion of principal officer. Certain information has been provided and/or based on third-party sources and although believed to be reliable, has not been independently verified; the investment managers make no express warranty as to its completeness or accuracy, nor can it accept responsibility for errors appearing herein.

Give it time and you will see

Letter # 39, 30 April 2021

Have a look at the figure below. Given the times we currently live in, you might think it illustrates the rising Covid cases in India. It does not; but let us park that for a minute; I shall come back to it. First, let me tell you a story about two gentlemen.

The first one, let us say Mr. A, studied to be an investment banker and got a job at a decent bank. He globe-trotted his way till the age of 30, by when he got bored and decided to start investing full time. He had saved USD1mn, which became his seed capital. Over the course of the next 30 years, he did fantastically well, generating 20% CAGR till he turned 60. By then, his corpus ballooned to USD237mn and he decided to give up investing full time to rekindle with his childhood passion of playing golf. Mr. A did well (20% CAGR is not common and a quarter of a billion is a lot of money). But then, it would have been just another story, nothing that would inspire generations to come.

Now consider Mr. B. He started investing at the age of 11 and is still investing full time as he becomes a nonagenarian. He has compounded his wealth at the same rate as Mr. A (20% CAGR), but for a longer period. He holds annual shareholders’ meetings, which are attended by shareholders from across the globe–to gain from his wisdom, but more importantly, to pay homage to one of the best investors of our generation. He hosts a charity lunch once every year, for which someone paid USD4.6m last year. Compared to Mr. A’s USD237mn net worth, Mr. B is now worth a staggering USD84.5bn!

By now, you would have guessed that Mr. B is indeed Mr. Warren Buffett. But would it be surprising if I told you that Mr. A is also Warren Buffett with a slight nuance—he just decided to retire early at the age of 60. The chart above is the age wise graph of his wealth accumulation. Of the USD84.5bn in wealth, he generated a whopping 95.5% (or USD80.7bn) after he turned 60. One might think that the rate at which wealth compounded after he turned 60 has increased dramatically; it has NOT! (age 30 to 60: CAGR of 32%, age 60 to 90: CAGR of 11%). This might sound counter intuitive, but that is simply how compounding works.

Of the thousands of books and articles that deeply analyse Buffett’s investment style, hardly any book mentions what’s far more important is that he has done it for way longer than anyone else. And come to think of it, Buffett hasn’t had the highest returns track record; many of my fellow asset managers in the alternatives space report far superior returns. Jim Simons, who ran Ren Tech’s Medallion Fund returned more than 66% CAGR over a 30-year life span (1). And yet, Jim’s net worth in not even a third of Buffett’s! The latter’s skills are possibly many, but his secret is one… TIME*.

A lot of people on hearing this, come back with something like, “I agree! I want to get invested for the long term, but markets are at their peak right now. I will look for a more opportune time to get invested.” A lot of us think that ‘getting in at the bottom of the market and getting out at top’ is the key to successful investing. While that has its benefits for wealth creation, it is not an essential criterion (see data below).

We have analysed data of BSE Index since 1979 (close to 13,500 days). Had one chosen any random day to invest, there is a 92% probability that they would have generated a positive return over a 5-year period. Now, I am not suggesting that because it has happened in the past, it will always happen; but historical odds are staggeringly in favour of getting invested.

A corollary to this is true as well. If one had invested on January 1, 1990, their cumulative returns till date would have been 6242% (or 14.2% CAGR). However, if they had missed just the best 10 days in that time, the returns would have been only 2205% (lower by 65%). Miss 30 best days and returns fall to just 512% (lower by a whopping 92%).

The learnings are simple, but counter intuitive. As investors, we focus a lot more on generating maximum returns for any given period, and a lot less on how we can keep doing it for a long time without getting burnt out. The highest returns mindset forces our attention on the smallest of the news items that we can consume (from social media, Whatsapp, news channels, etc.); after all, we wish to be the quickest to execute the trade before the market gets the chance to digest the news.  In my opinion, that is as often noise as often as it is a signal; intelligently deciphering it to benefit consistently has proved futile. Second, we obsess endlessly about timing the market. We want to get in at the lowest possible price and get out at the highest possible price. Every now again, one gets it right, which creates a false sense of comfort that they can keep doing it. But since it is not humanly possible, it eventually leads to the feeling of either: (a) having missed out; or (b) having messed up. That is far worse than the few times one was right in timing the market.

Third, some take inordinate risks that can put them out of markets in the event of an adverse outcome. Last week, we discussed how things that haven’t happened before, happen all the time (no typos in that sentence). If you are that leveraged, where you potentially risk ruin in case of an adverse outcome, staying in the game long enough will prove highly challenging.

Lastly, we should be willing to learn and adapt. Strategies that have done well in the past five years are not the strategies that will continue to do well now or in the next five years. Strait-jacketing an investment thesis (2) (I will only buy high RoE and fast growth businesses, never buy PSU stocks, never buy commodity stocks etc.) does not take lessons from history and will likely result in resentment on several occasions.

Like nature, investment strategies should learn to adapt. There can be boundaries that we, as investors, will never cross, but willingness to learn and adapt will likely enhance our time horizons. In the end, that’s what matters more than anything else, right?

Notes:
(1) Renaissance Technologies – Wikipedia
(2) We have endlessly written about those; you will find them at blog – Buoyant Capital
* This story is adapted from Morgan Housel’s book, The Psychology of Money
The letter was originally published here: Give it time and you will see – cnbctv18.com

Disclaimers:
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 Disclosure Document filed with SEBI. Any description involving investment examples, statistical analysis or investment strategies are provided for illustration purposes only – and will not apply in all situations and may be changed at the discretion of principal officer. Certain information has been provided and/or based on third-party sources and although believed to be reliable, has not been independently verified; the investment managers make no express warranty as to its completeness or accuracy, nor can it accept responsibility for errors appearing herein.

Pessimism sells, but does it also pay?

Letter # 38, 23 April 2021

In late 2008, the Dow Jones Industrial Average was down close to 40% from its recent high as the global financial crisis engulfed the entire world. A crisis of this magnitude was unprecedented, and everyone was uncertain as to what would happen next. That’s when an article appeared, (1 ‘As if things weren’t bad enough…’

“Around the end of June 2010, the US will break into six pieces. California will form the nucleus of ‘The Californian Republic’ and will be part of China. Texas will be the heart of ‘The Texas Republic’, a cluster of states that will go to Mexico. Washington and New York will be part of ‘Atlantic America’ that may join the European Union. Canada will grab a group of Northern states and Hawaii will be a protectorate of Japan or China, and Alaska will be subsumed into Russia.”*

No, this is not some looney blogpost or a newsletter that no one reads; it is on the front page of the Wall Street Journal–widely considered one of the most prestigious financial newspapers around the world, with circulation of 2.8mn copies and 37 Pulitzer Prizes.

2008 appears to be a long time ago, but the feeling of pessimism surrounding the article seems as pervasive even today. A perusal of several social media or news articles indicates an impending doom of the second Covid wave in India. There is no denying that the on-ground situation in India is acute, but the news reports almost conclude that there is no end in sight. Consider this Bloomberg article (2) which lists everything problematic, without even mentioning how the situation is improving at the margin. Or this article (3) which lists how the absolute number of Covid cases in India is the highest now, disregarding the size of India’s population and density.

One often wonders, why the exaggerated pessimism? Morgan Housel deals with this subject beautifully in his book The Psychology of Money. He says that optimism is the best bet for most people because the world tends to get better most of the time, but pessimism holds a special place in our hearts. Pessimism sounds smarter, it is intellectually captivating, and it is paid more attention than optimism, which is often viewed as being oblivious to risk.

Historically, the odds that an outcome will be in our favour over time are greater despite there being setbacks along the way. Optimism is focusing on the higher odds; pessimism is focusing on those setbacks.

However, sounding pessimistic grabs attention faster. As Morgan puts is, “if a smart person tells me that a stock pick that’s going to rise 10-fold next year, I will immediately write him off as nonsense; but, if someone who is full of nonsense tells me that a stock that I own is about to collapse because of accounting fraud, I will clear my calendar and listen to his every word.”

Now imagine someone writing this in the late 1940s after Japan was gutted in World War II and the future appeared bleak. “Look today it looks bad, but it won’t be like this forever. Within our lifetime, our economy will grow 15x pre-war levels. Our life expectancy will double. Our stock markets will rock. Unemployment won’t cross 6% for decades. We will become world leaders in electronic innovation. We will become so rich that we will own a decent chunk of Manhattan, and yes, America will be among our closest allies.” Sound ludicrous, right? But that is exactly how it panned out*.

It is easier to create a pessimistic narrative when the panic is fresh in our memories. At the peak of the Covid crisis in India in March 2020, some prominent industrialists and politicians sounded intelligent by arguing how “India flattened the wrong curve” (4) by imposing the national lockdown and how “central leadership screwed up by not giving states the control to fight the pandemic (5).” In the second wave of covid, we find out how neither of those narratives was accurate.

In a 2008 letter to shareholders, this is what Warren Buffett wrote, (6) “amid this bad news, however, never forget that our country has faced far worse travails in the past. In the 20th century alone, we dealt with two great wars (one of which we initially appeared to be losing); a dozen or so panics and recessions; virulent inflation that led to a 21 1⁄2% prime rate in 1980; and the Great Depression of the 1930s, when unemployment ranged between 15% and 25% for many years. America has had no shortage of challenges. Without fail, however, we’ve overcome them. In the face of those obstacles – and many others – the real standard of living for Americans improved nearly seven-fold during the 1900s, while the Dow Jones Industrials rose from 66 to 11,497. Compare the record of this period with the dozens of centuries during which humans secured only tiny gains, if any, in how they lived. Though the path has not been smooth, our economic system has worked extraordinarily well over time. It has unleashed human potential as no other system has, and it will continue to do so. America’s best days lie ahead.”

When we are on the river of life, it is more than likely that we will hit a few rocks. That’s not being pessimistic, that is being accurate. From memory, I recall Ayrton Senna, the Formula one car racing champion, saying something like this in an interview, (7) “I attempt that my car never goes into a tailspin. But when it does, I can either look at the wall I might crash against or the road where I am supposed to drag my car back to. Focusing on the road improves the chance of my car not crashing by a factor of 10. And in my line of work, that is difference between life and death.”

Pessimism helps sell book and newspaper, and it may even make you sound intelligent; but over the long term, does it really pay to be pessimistic all the time? During the previous crisis, Warren Buffett was focusing on the road instead of the wall; all of us might do a lot better with our investments if we did the same, the current covid predicament notwithstanding.

Notes:
(1) As if Things Weren’t Bad Enough, Russian Professor Predicts End of U.S. – WSJ
(2) India’s Covid Tragedy as Seen on Twitter, Instagram and Facebook – Bloomberg
(3) Covid: India sees world’s highest daily cases amid oxygen shortage – BBC News
(4) Coronavirus Lockdown Flattened The Wrong Curve: Industrialist Rajiv Bajaj To Rahul Gandhi On Lockdown (ndtv.com)
(5) Modi’s Need for Control Impairs India’s Coronavirus Recovery – Bloomberg
(6) printmgr file (berkshirehathaway.com)
(7) I fail to find a reference of this anywhere on internet. There is a strong possibility I maybe wrongly attributing this to Ayrton Senna
* Story adapted from the book: The Psychology of Money by Morgan Housel
This letter was originally published here: Pessimism sells, but does it also pay? – cnbctv18.com

Disclaimers:
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 Disclosure Document filed with SEBI. Any description involving investment examples, statistical analysis or investment strategies are provided for illustration purposes only – and will not apply in all situations and may be changed at the discretion of principal officer. Certain information has been provided and/or based on third-party sources and although believed to be reliable, has not been independently verified; the investment managers make no express warranty as to its completeness or accuracy, nor can it accept responsibility for errors appearing herein.

Because it has never happened before – tail risks and convex portfolios

Letter # 37, 16 April 2021

In a series of interviews last week, Prashant Kishor—one of India’s finest political strategists (in my opinion)—reiterated, multiple times, a commitment which sounded bizarre. Prashant’s company, I-PAC (1) / (1b), is currently working with All India Trinamool Congress (AITC) for the ongoing assembly elections in West Bengal in a primary fight against the Bharatiya Janta Party (BJP). He claimed that BJP will struggle to cross 99 seats (in a 294-constituency assembly), and if it does cross, he will quit this space (2) (which he later clarified to mean that he would stop being a political aide to any other political party and shut down I-PAC (3)).

The claim is bizarre, predominantly on account of the disproportionate risk he seems to have taken; and not, at the very least, because he does not have the data or the on-ground reports or the absolute expertise to read the election. In the 2016 West Bengal assembly elections, AITC had won 211 seats and BJP had secured just three (with a vote share at 10%). By the 2019 Lok Sabha elections, BJP’s vote share in West Bengal had jumped to 41%. If BJP were to translate its 2019 parliamentary constituency win into the 2021 assembly constituency win, it would stand to win 127 seats. In addition, with a mere 3.5% vote swing, some 36 seats could swing from AITC to BJP.

Now, I-PAC has been years in the making and has already helped national (BJP and INC) as well as a few regional parties (JDU, YSRCP, AITC, DMK). In its field of operation, it is by far at pole position. Politicians making unsubstantiated claims may be par for the course, but for a professional, as astute as Prashant (who even chooses his words carefully), the upside from making this unsolicited bet is flummoxing. Until, in one of the interviews (3), he clarified the basis of his conclusion, “we have studied data for the last 30-40 years and have seen elections in most polarizing atmospheres. We have found that 50-55% is the limit beyond which it is not possible to polarize a community; it has never happened.” (3)

To simplify, Prashant is staking everything he has painstakingly built over the past decade, inter-alia, on the assumption that because it hasn’t happened before, it will not happen now. Whether he wins or not is not as much of consequence, as the realisation that even seasoned professionals can end up taking disproportionate risks based on erroneously calculated odds. And, if you think this hasn’t happened before, read on.

In 1991, John Meriwether, then the head of bond arbitrage desk of Solomon Brothers, resigned and founded Long-Term Capital Management (LTCM) in 1994. Members of LTCM’s board of directors included Myron Scholes and Robert Merton–who shared the Nobel Prize in Economic sciences for ‘a new method to determine the value of derivatives.’ John’s desk was responsible for 80-100% of Solomon’s total earnings between the late 1980s and early 1990s (4), and the other two gentlemen literally wrote the book on how to value derivatives. Clearly, LTCM was run by an exceptionally sharp bunch.

The idea behind the hedge fund was simple–exploit small pricing inefficiencies in bond markets and leverage the trade to generate a superior rate of return on equity. Among its core strategy was to purchase the old benchmark, say issued 3 months ago (which no longer had a premium attached to fresh issues), and to sell the newly issued benchmark, which traded at a premium. Over time, valuations of the two bonds would converge. Assuming this generates 50bps arbitrage, you leverage the position 25 to 1 and earn 12.5% return on equity (50bps * 25x leverage). LTCM generated annualised return of 21% (after fees) in its first year, 43% in second and 41% in its third year. The going, so far, was good.

By the end of 1997, LTCM broadened its strategies by including new approaches in markets outside of fixed income. Many of these strategies were not market neutral as they were dependent on directional movement in interest rates or stock prices (not traditional convergence trades). By 1998, LTCM had accumulated extremely large positions in merger arbitrage and S&P 500 options. The assumption was, because things have historically converged, they will in the future as well.

At the beginning of 1998, LTCM had equity of USD4.7bn and had borrowed over USD125bn, a debt-to-equity of over 25x. The markets, then, were just recovering from the 1997 Asian Financial Crisis when the Russian government had defaulted on its domestic local currency bonds. It hadn’t happened before; countries have access to the printing press, why would it default on local bonds instead of just printing more money. But it did, and in the ensuing flight to quality, prices that ‘should have’ converged went farther apart. By end of September 1998, LTCM had lost USD4.3bn, leaving it with debt-to-equity ratio of a staggering 250 to 1. Fourteen institutions had to bail it out under supervision of the Federal Reserve and the fund was dissolved in early 2000.

At the end, we must acknowledge that with investments, as with life itself, events that have not happened before, may happen. Prior to last year, markets had never fallen 25% in one month (and yet they did in March 2020). And, markets had never recovered to form new high in one straight line (which again they did by December 2020). These are tail risk events, ones that have an exceptionally low probability of occurrence, but when they do occur, they have a disproportionate impact.

As investors, all of us regularly draw conclusions from historical events. As the availability of data and the depth of our analysis increase, so does our confidence in decision making. And when rising confidence meets success, for every subsequent bet, we tend to increase the stakes. This can be a virtuous circle, only so long as we do not raise the stakes so high that when a tail risk event strikes, its impact delivers a devastating blow on our portfolios which we cannot recover from.

Nassim Taleb, in his book Antifragile, calls it making your portfolio convex–something that gains from disorder (including tail risks), whereas Mohnish Pabrai, in his book Dhandho Investor, elegantly puts his investment philosophy as, “heads, I win; tails, I don’t lose much.”

Even seasoned professionals can fall in this trap when the going is good. Being prepared that life will, intermittently, keep serving events that have never happened before, is the battle half won.

Notes:
(1) The un-politics of Prashant Kishor | India News,The Indian Express;
(1b) IPAC is widely reported as Prashant’s company, but it is difficult to find in what capacity he is related to it from its website.
(2) https://twitter.com/PrashantKishor/status/1340882902628749317?s=20
(3) Prashant Kishor Speaks To Rajdeep Sardesai Over His Explosive Chatroom Audio Leak On Bengal Polls – YouTube
(4) Long-Term Capital Management – Wikipedia

The letter was originally published here: Because it has never happened before—tail risks and convex portfolios – cnbctv18.com

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