Why is continuous learning important?

I came across a great quote on the subject from a Coursera course on Model Thinking by Scott E. Page. The subject under discussion was Solow Growth Model to understand growth of countries. I have edited it a little to set the context: “We can sort of work hard, but if we don’t invest in new technologies, in new innovation, if we don’t become sort of better at what we do, by possibly learning new models, learning new techniques, by developing new skills, we’re probably gonna level out. In fact, if you look at the data on what makes for really successful people, people who are very successful in their careers, one thing you find is they continue to learn. So, it’s almost like their own personal technology parameter (similar to investments in innovation and technology by countries). They keep upping and upping and upping. So continued growth depends on innovation and getting better. You can’t just sort of do more. At some point, the rate at which things fall off and the rate at which things increase are just gonna even out. Sustained growth requires innovation, becoming better at what you do. So just like countries have to invest in innovation, so should a person and that’s where personal growth and sort of personal success can come from.

Arisaig’s Investment Philosophy

It is important to have a good investment process and I am constantly checking how other investors approach this. Arisaig is a consumer focused fund and I admire the in-depth work they do in understanding their companies. Below is how they summarize their investment process in their letters. I don’t agree with every point but most of what they say is very sensible.

What we look for in our stocks:   
– Market leadership – dominant companies tend to do better; 
– Scalability – large target markets; 
– Strong “moats” – brands, distribution, innovation; 
– Low capital intensity – high ROCE; 
– Predictability – compounding growth; 
– Access – management who welcome our involvement.

What our investors can expect from us:   
– Alignment of interests – capped funds, no segregated portfolios, co‐investment; 
– Transparency – holdings booklets, monthly portfolio summaries, examples of research reports; 
– Coverage – 22 analysts; five research offices; 150 target stocks; 
– Minimal trading – active management destroys value;  
– Focus – consumer companies tend to out‐perform, so we won’t be doing anything else.

Vito Maida on choosing an investment manager

From Vito Maida, Founder and President, Patient Capital: You don’t want an investment manager doing something different with his money than he is doing with his client’s money. When you’ve got your money on the line and you’ve got your entire family’s money on the line, the approach is a lot different than if you’re doing it just for the clients.

DCF is dangerous

From Stephen Penman: “I am not a fan of DCF valuation. It discounts free cash flow with that elusive discount rate, but the problem is worse. Free cash flow is not a measure of value added; it is not appropriate accounting for value. That’s easily seen. Free cash flow is cash from operations minus cash investment, so investment reduces free cash flow and liquidation increases free cash flow. That’s perverse. I can show you a number of very profitable firms that have negative free cash flows because they invest a lot to take advantage of their profitable opportunities. DCF works for long forecasting horizons, but that leaves you speculating about the long-term, or guessing at the “long-term growth rate.” Plugging in an assumed growth rate into a DCF model is dangerous; it results in a speculative valuation that rides on a (speculative) growth rate.

The way to success

From Mohnish Pabrai quoting Swami Vivekananda:
“Take up one idea.
Make that idea your life.
Think of it, dream of it,
live on that idea.
Let the brain, muscles, nerves,
every part of your body,
be full of that idea, and
just leave every other idea alone.
This is the way to success.”

Addendum to Rules no. 1 & 2

As mentioned in a prior post, Warren Buffett’s first two rules of investing are “Rule No.1: Never lose money. Rule No.2: Never forget rule No.1”.

These rules are so important, I thought they deserved a bit more discussion. The following two quotes and my comments, sort of, follow from the first two rules. They are from an interview conducted with Charles de Vaulx and Charles de Lardemelle of International Value Advisers:

One of the most effective ways to compound wealth is to minimize drawdowns” -> Large drawdowns really hamper the long term compounding rate. For instance, if your portfolio falls by 20% in value, it requires a 25% return just to get back to breakeven. If the drawdown is 33%, you need a 50% return to get back to breakeven. If the drawdown is 50%, your portfolio needs to go up 100% just to get to breakeven. So avoiding large drawdowns is important.

For each stock we arrive at an estimate of intrinsic value, but equally important is defining the worst-case value” -> If you can buy a stock below its intrinsic value, you automatically get a margin of safety. Even if the stock price is higher than the worst-case value (but below the intrinsic value), the worst-case value gives an estimate of the drawdown you might face on that stock. Remember that Mr. Market can get fairly irrational at times. Some of the best investment opportunities are created when a stock goes below the worst-case estimate (provided the analysis is sound).

The full interview is here.

Rule No.1: Never lose money

Warren Buffett: “Rule No.1: Never lose money. Rule No.2: Never forget rule No.1

This is probably the most important rule in investing. But I think it is also misunderstood. The two words that cause confusion are ‘lose‘ and ‘money‘. Here is what I think Buffett really meant with these two words.

Money‘ is not the absolute dollar amount. It is the value of your dollars adjusted for their purchasing power over the investment horizon. Buffett explains it beautifully in another place when he says “Unfortunately, earnings reported in corporate financial statements are no longer the dominant variable that determines whether there are any real earnings for you, the owner. For only gains in purchasing power represent real earnings on investment. If you (a) forego ten hamburgers to purchase an investment; (b) receive dividends which, after tax, buy two hamburgers; and (c) receive, upon sale of your holdings, after-tax proceeds that will buy eight hamburgers, then (d) you have had no real income from your investment, no matter how much it appreciated in dollars. You may feel richer, but you won’t eat richer“. It is easy to say that this is simply the inflation-adjusted real return but this statement brings about two new problems. First, each person’s inflation rate is different depending on their individual basket of consumption…and this basket can also vary over time. The official rate of inflation (and it doesn’t matter which official authority one uses) may be benchmarked to a different basket of goods. Secondly, as most governments are incentivized to show lower inflation, I will not be surprised at subtle changes in the way official inflation is measured that understates real inflation. I use two heuristics to come up with an acceptable baseline rate of inflation to measure my personal investment performance. First, I use the official US CPI but adjust it up by 4% as some studies have shown that the adjustments to CPI methodologies over time understate the true inflation by 3-4%. Second, I take a minimum rate of 5% as I believe that my expenses are going up by atleast that much every year. So to actually become richer through investing, I need to beat 5% every year at a minimum. This gives me a heuristic of myCPI = min (5%, official US CPI + 4%). At the end of each year, I can use this to benchmark my investment performance. Note that I am better off overestimating my inflation rate than underestimating it. By overestimating it, I will be richer than I think which is not the worst mistake in the world.

Lose‘, I think, is also a misunderstood word. If I bought a stock for $100 today and it went down to $95 tomorrow, did I lose $5 on that investment? The correct answer is – not necessarily. The stock price is only relevant if I choose to act on it. If the fundamental value of the company is unchanged, the fluctuation in its stock price is irrelevant. If you have good reason to believe that the stock price is worth much more than $100, then either ignore Mr. Market’s mood swings or use it to your advantage by buying more. However, this is not a justification to naively double down on a losing investment. If you don’t have a good estimation of the company valuation, doubling down on a losing investment is a great way to throw good money after bad. The valuation estimate need not be a point value. If I think a company’s stock is worth somewhere between $120 and $200 and Mr.Market is giving me an opportunity to buy it for $100, even that wide range of estimates is good enough. You also need to have the capability of holding the stock through Mr.Market’s volatile mood swings. If not, you may end up selling up at an inopportune time and crystallizing your losses. Thus ‘lose‘ should be interpreted as a permanent impairment of capital.

So, to sum up, the first and the most important rule of investing can be awkwardly rephrased as ‘don’t impair your purchasing power permanently’. I have to admit that the original phrase sounds much more elegant as long as it is understood correctly.

The role of incentives in investing

Incentives are a powerful and often under-appreciated force. This is a great quote on the role of incentives in investing taken from an interview with James Rosenwald of Dalton Investments: “We feel that there is so much room for monkey business in running companies, but that management teams who own more shares than we do tend to focus on the success of the business rather than stealing from the company!

The complete interview here is also a good read. 

Betting on tennis with a quantitative model

Bloomberg has an article today on Elihu Feustel who built a quantitative model to bet on tennis. According to the article, Feustel does not watch a lot of tennis matches but built his model using quantitative inputs to come up with “fair” odds for a match. If his odds are significantly different from what the market is pricing in, he places a bet. I thought there were a few interesting takeaways from his approach.

First, frequently it is possible to build a predictive quantitative model using a few key inputs that does significantly better than the prediction of experts. We have seen this in many different domains. See here for more examples.

Second, before getting carried away and applying this approach into a new domain (investing, for instance), it is important to understand the bounds of this approach. The set of outcomes of a tennis match or a political election is small and bounded. Many investing situations have large possible outcomes. This makes the modeling much more difficult.

Lastly, there may be multiple ways to trade a situation (using options for instance) so the problem is not just one of building a good model but also of figuring out the best trade that maximizes the expected return.

Despite some of the modeling problems, this is an approach worth thinking about more deeply in the context of investing. I have some thoughts on this and I plan to develop this approach in future.

Excerpt from the article:

Tennis is an “attractive” sport to create an algorithm for because there are only two players in a singles match and statistics are freely available, according to William Knottenbelt, an associate professor of computing at London’s Imperial College. He co-wrote a tennis algorithm that he says would have made a 3.8 percent return on bets on 2,173 ATP matches in 2011.

Feustel, who says he puts in a 60-hour week checking and improving his model, works with a computer programmer and trader. The programmer trawls the Internet for data such as serve speed and break-point conversions. That’s plugged into the model which comes up with “fair” betting prices for scheduled games.

If those odds diverge from market prices, Feustel says, his trader — who lives outside the U.S. — will gamble as much as the market will allow at bookmakers including Pinnacle Sports, based on the Caribbean island of Curacao. That can be about $30,000 on a match result in later tournament rounds.

Here is a link to the full article.

An example of fragility exposed through a crisis

An example of hidden sources of fragility in the context of the Mexican Tequila Crisis. Key learning: “there is often an unknown vulnerability that only comes to light when a crisis erupts

From Bamboo Innovator:

Tequila crisis: The dangers that only come to light in a disaster
Mexico’s “tequila crisis” is the quintessential example of the dangers of original sin. It also holds some cautionary lessons for those who believe the floating exchange rates and foreign borrowing abstinence of emerging markets will now inoculate countries from crises.
Money gushed into Mexico in the early 1990s but when Alan Greenspan, the Federal Reserve chairman, raised interest rates in 1994 the boom came to an abrupt end – and the dollar put pressure on the peso’s peg. By December the government tried to depreciate the peso but the currency crashed by more than 50 per cent.
The government was then brought low by its Tesebonos – peso bonds indexed to the dollar to reassure investors worried about a devaluation. When the peso collapsed the state was unable to pay the Tesebonos and had to be rescued by the US and the International Monetary Fund.
Today Mexico’s finances are transformed. About 80 per cent of its debts are in pesos, the currency floats and the central bank’s reserves are close to $180bn. Original sin is almost eliminated and the country is a firm investor favourite.
But the tequila crisis holds another vital lesson for policy makers and investors that draw comfort from the striking reduction in original sin: that there is often an unknown vulnerability that only comes to light when a crisis erupts.
Mexico’s crash in 1994 was exacerbated by the fact that the recently privatised local banks had themselves quietly accumulated huge exposures to Tesebonos. The currency devaluation therefore hammered the entire domestic banking sector instead of just hurting US banks, causing a ripple throughout Latin America.
Nor did Mexico look particularly vulnerable before the crisis struck. Although the current account deficit was wide and inflation elevated, the budget was not in terrible shape and growth was the fastest in four years in 1994. “Mexico was the poster child of Latin America,” says Prof Calvo. “But when liquidity bubbles burst it reveals weaknesses we cannot see now.”