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Small Circles: The Theory of Mastery in the Art of Learning and Investing

One of the best books on the art of learning I’ve read is, well, The Art of Learning by Josh Waitzkin.

Josh is a champion in two distinct sports – chess and martial arts. He is an eight-time US national chess champion, thirteen-time Tai Chi Chuan push hands national champion, and two-time Tai Chi Chuan push hands world champion.

In his book, Josh recounts his experiences and shares his insights and approaches on how you can learn and excel in your own life’s passion, using examples from his personal life. Through stories of martial arts wars and tense chess face-offs, Josh reveals the inner workings of his everyday methods, cultivating the most powerful techniques in any field, and mastering the psychology of peak performance.

One of my favourite chapters from Josh’s book is titled – Making Smaller Circles – which stresses on the fact that it’s rarely a mysterious technique that drives us to the top, but rather a profound mastery of what may well be a basic skillset.

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Latticework of Mental Models: Risk Aversion Vs Loss Aversion

On April 10, 2003, Pepsi announced a contest called “The Pepsi Billion Dollar Sweepstakes”. It was scheduled to run for 5 months starting from May in the same year.

For the contest, Pepsi printed one billion special codes which could be redeemed either on their website or via postal mail. According to Pepsi’s estimate, about 200-300 million of these codes were redeemed. Out of these, 100 codes were chosen in a random draw to appear in a two-hour live gameshow-style television special. Each of these 100 people were assigned a random 6-digit number, and a chimpanzee (to ensure a truly random number and of course to rule out any monkey business) backstage rolled dice to determine the grand prize number. This number was kept secret and the 10 players whose numbers were closest to it were chosen for the final elimination. On the evening of September 14, the final day of the contest, the event, titled Play for a Billion, was aired live. If a player’s number matched the grand prize number, he would win US$ 1 billion.
(Source: Wikipedia)

Given the scenario, it was highly unlikely that anyone would win a billion dollar. The chances were literally 1 in a billion. In spite of that, Pepsi was unwilling to bear the risk of the possible billion-dollar prize. So they arranged for an insurance company to insure the event. They paid US$ 10 million to Berkshire Hathaway to assume the risk. Yes, Warren Buffett’s Berkshire Hathaway. The same guy who is famous for his two iron rules –

1. Never lose money
2. Don’t forget rule number 1.

Then why would Buffett expose his company to such a big risk for a relatively paltry premium of US$ 10 million? Isn’t this akin to playing Russian roulette?

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Latticework of Mental Models: Decision Fatigue

In January 2016, after two months of paternity leave when Mark Zuckerberg returned to work he asked his followers, showing off a picture of his wardrobe, for a suggestion about what he should be wearing to office. This is how his wardrobe looked.

Pretty drab collection, isn’t it? Zuckerberg has been wearing the same outfit, a grey t-shirt, for many years. The reminds us of Steve Jobs and his favourite black turtleneck.

So why do these billionaires who could afford almost anything in this planet, choose to stick to a simple attire?

The answer is – it’s their hack to simplify life.

According to Zuckerberg, making clothing decisions each day was a “frivolous” waste of time. I really want to clear my life, says Zuck, “to make it so that I have to make as few decisions as possible about anything except how best to serve this community.”

According to one estimate, we normally make somewhere around 35,000 decisions every single day. Many of those decisions are unconscious like walking, blinking, breathing and don’t need any extra mental effort. But the sheer volume of even those decisions that require at least some brain power like what to wear, where to eat, how to get to work, who to call when you get there, is staggering.

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Latticework of Mental Models: Zeigarnik Effect

“What is not started today is never finished tomorrow.” ~ Johann Wolfgang von Goethe

The most interesting and exciting thing about psychology is that you don’t need expensive lab instruments to experimentally test the validity of theories. The world is your lab and its inhabitants i.e., people, including yourself, are the test subjects (read guinea pigs).

So here is a simple experiment that you can try during your next visit to any restaurant.

You’d often find waiters who don’t need to write down your order. They seem to have this remarkable ability to accurately remember the order for each table. Even if there are half a dozen orders with every order consisting of many different dishes (including special request like – less sugar, no mushrooms in the Pizza etc.) these waiters rarely goof up.

Well, it’s a part of their job and with years of practice, they develop a super-sharp memory. But do they really have a great memory?

Try this – After you are done with your meals and have paid the bills (and a good tip), wait for ten minutes after you have left your table and then go back to the waiter who was waiting on you. Ask him to repeat your order. You’d expect him to rattle off your order without any difficulty. But don’t be surprised if he gives you the look – “I am sorry, who are you?”

It would seem, not just your order but your whole existence has evaporated from waiter’s memory. What happened to his super memory?

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Latticework of Mental Models: Physics Envy

A group of tourists was visiting a dinosaur museum. A guide was entertaining them with interesting trivia about various dinosaur species. Just when they were passing by a huge skeleton of an ancient carnivore, an inquisitive member of the tourist group asked the guide, “How old is this skeleton?”

“Oh, that big T-rex skeleton? It’s about 100 million and 5 years old.” quipped the guide.

“That’s quite an odd figure. I understand the 100 million part but how are you so sure about the last 5 years?”

With all earnestness, the guide replied, “Well, that’s the most accurate part of the figure because exactly 5 years ago a world famous expert on dinosaurs told me that the skeleton is 100 million years old.”

The guide was honest in his attempt to provide an accurate information but he confused accuracy with precision. His answer was precise but was it really accurate? In fact, a better question to ask would be – did the guide make expert’s answer anymore useful by making it more precise? I think no.

Sir John Maynard Keynes said, “Better roughly right than precisely wrong.”

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Latticework Of Mental Models: Hedgehog Vs Fox

On June 16, 2015, Donald Trump announced his candidacy for President of the United States. Most political forecasters and pundits brushed this news as Trump’s another gimmick for seeking attention and creating sensational news.

Sixteen months later, as November 2016 approached, it became frighteningly clear that Trump was very close to winning the elections.

However, when the experts were shaking their heads in disbelief and talking about all the things that were wrong with Trump, there was a cartoonist in San Francisco who had been writing blogs all through 2015 and 2016, claiming that Trump will win the elections in landslide. He received a lot of flak (even threats) but on November 8, 2016, Scott Adams, the creator of Dilbert was proved right.

Not entirely right because Trump’s victory wasn’t exactly a landslide but he did win the elections. But Adams was way ahead than the experts who were sweating over predicting precise numbers by which Trump will lose.

Charlie Munger likes to say, “It’s better to be approximately right than precisely wrong.”

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The Most Powerful Mental Model for Identifying Stocks

For starters, we had our Value Investing Workshop in Chennai yesterday, and here are some moments from the same…

Safal Niveshak's Value Investing Workshop in Chennai - Feb. 2017

The next workshops are in Mumbai (19th Feb), Delhi (25th Feb), and Hyderabad (5th March). In case you wish to join any of these, please click here to register.

Anyways, let’s start with today’s post.



“It’s a funny thing about life; if you refuse to accept anything but the best, you very often get it.” ~ W. Somerset Maugham – English dramatist & novelist (1874-1965)

As I’ve seen in the past 14+ years of investing in the stock market, Maugham’s thought holds a great relevance when it comes to picking up businesses for investment.

Pick up a business with good economics and with good margin of safety, and the probability of making money in the long run is high. Pick up a business with poor economics with any margin of safety, and the probability of losing your shirt, and entire wardrobe, in the long run is very high.

Understanding a business also adds significantly to your margin of safety, which is a great tool to protect yourself against losing a lot of money.

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Latticework Of Mental Models: Planning Fallacy


When I planned my first road trip from Bangalore to Goa, I calculated that the distance (about 560 km) should take little more than 9 hours. Factoring in stopovers and few unexpected events like a flat tyre or traffic, I assumed that 12-15 hours should be sufficient for the road trip. It took 15 hours.

“Good job, Anshul!” I patted myself on the back. Not a bad estimate.

Now based on this, if I had to forecast the time it would take to cover a distance of say 5,000 km, a road trip to cover major cities in India, I might be tempted to extrapolate the Bangalore-Goa trip time. I’ll probably calculate that 560 km took one day so 5,000 km should take 10 days plus 2-3 more days.

Am I being reasonable in my estimation?

What I am forgetting here is that the second road trip is not only longer but more complex and subject to many more unforeseen and unexpected events. My estimation is fraught with over-optimism bias. And I am not alone in making this kind of mistake.

There are many ways a plan can fail and most of those things are too improbable to be anticipated. The likelihood that something will go wrong especially in a big project is high. Overly optimistic forecasts of the outcome of projects are found everywhere.

In fact, how often are you able to complete everything on your to-do list at the end of the day? This shows how absurdly ambitious we’re in planning.

This bias, a phenomenon in which predictions about how much time will be needed to complete a future task display an optimism bias (underestimate the time needed), is called Planning Fallacy. The term was coined by Nobel Laureate Daniel Kahneman and his colleague Amos Tversky.

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