From an investing point of view, “high quality” is subjective. Subjective to your risk appetite, time horizon and your own biases. But it would be fair to say that, a company that can assure a certain amount of return over a period of time can be considered as high quality. The quality coming from the certainty to which we can look into the future.
That said, there are countless ways in which the future can unravel. Hence, we need to have a margin of safety in our thesis about a company and it’s future.
The analysis can be divided into a qualitative and quantitative parts.
The 5 main qualitative perspective are
- How does the business make money? What is it’s business model? What are the core features of the business that customers are paying continually paying for?
- Does it have a competitive advantage? Will that advantage strengthen or weaken as the business expands?
- Are they innovating with changing times? This shouldn’t be read as, are they jumping on the hype wagon every couple of years to prop up investor sentiment. Rather, is the business having a good balance of exploring new avenues and maintaining it’s core business.
- What are the major risks for the business? Are there any other businesses that can take its place easily?
- How are the people running the business? This is hard to judge without having any kind of contact with the management. Have they been on the news lately? And was it for a good or a bad reason?
The 5 main quantitative aspects to figure out are
- How has the returns been historically? What drove them over the years?
- What are the costs for running the business? Are the costs growing or dropping and why? How will the costs change as the business expands?
- How much debt does the company have? Is it good debt or bad debt? Will it be able to payoff most of it’s debt if an adversity occurs?
- What are the margins in the business? How much pricing power do they have?
- These metrics alone are not that helpful in itself. The key step here is to compare it with that of it’s competitors and against the backdrop of the industry the business is in.
Coffee Can investing was first popularized by Robert G. Kirby in an article he published in the fall of 1984.
Coffee Can investing riffs off of an old-fashioned saving method where you physically earmark some money, put it in a coffee can, and basically forget about it. And only consider opening it either after a long time or when you desperately need the money.
Converting that concept into an investing strategy, this is how it would look like.
You would begin by allocating money to a number of high-quality companies and forget them for a period of 10 years. No buying or selling during this period. “Just” hold on to dear life.
Then you might ask, why not invest an index fund and hold that for 10 years. Well, for most people, the index fund is still a very good option. But the upside of how much an index can run in a span of 10 years is capped. This cap is typically due to the fact that the growth and return of an index fund in averaged among all of it’s constituents. Despite a few high performing companies, the index would still move slower.
However, the coffee can strategy does have an elegant logic behind it. Consider that you have $100 Million dollars to invest. If you split that into 50 investments in high quality companies worth $2 Million each. The maximum you could lose in one holding is only 2% of the total portfolio while the upside is uncapped. Chances are that at least a couple of the holdings turn out to be a multi-bagger and provide a net profit at the end of 10 years.
An advantage of this kind of investing is that the amount compounds over time and fetching every dividend along the way. Compounding works well when it is not disturbed.
A detriment to an investment strategy are it’s transaction costs. A great strategy with too many transactions would then begin to eat up the gains anyway. Coffee can investing solves that buy reducing transactions to the absolute minimum.
A downside is that it requires you to invest a lump sum amount up front. In addition to that it does take time and effort to figure out which companies are “high quality”. But it is doable.
Greenfield and Brownfield investments are ways in which a company can expand into other countries. They are 2 different types of foreign direct investment.
Greenfield investment is when the company builds necessary resources from scratch in the new country. This could include building new plants, distribution centres etc. Greenfield option makes more sense if the business operations are unique and custom made for the company. It is more risky as it is the more expensive option of the two. If the operations are near one-of-a-kind, it would be cheaper to build it from scratch and operate it like existing parts of the business. A good example of this is the Gigafactory tesla is building in Germany.
Brownfield investment is when the company relies on acquiring existing companies and facilities. This makes sense when business operations are rather existing. In some cases, facilities are leased instead of purchasing. This could be an interim solution before companies can take the leap to build their own facilities in a new market.
This way of thinking can be applied to personal projects as well. Would it be easier to update your personal website by making tweaks or to rewrite it from scratch.
A term I came across from Mental Models Vol. 1. But this is something that I have found myself doing and has been useful in helping me make decisions.
When presented with a decision that is a) affected by a lot of uncertainty the future holds b) a large set of possible outcomes can be guessed, then having a theoretical world generator helps.
Having a checklist of aspects to consider is a good idea. A set of checklists covering different dimensions. Maybe they can be classified as internal or intrinsic aspects and external ones. Or can be classified in terms of time.
Thinking about the possibilities in a form of a tree can also help.
After mapping out most of the outcomes and possibilities. The next step is to individually think about the probability of each outcome from happening.
Now here is the kicker. What makes this a really neat is that we have to start thinking about the different outcomes and work our way backwards to the event&decision. Thinking forward and backward through a possibility tree.
This exercise can easily backfire too. So figuring out on what problems this approach works and doesn’t is key. This takes a lot of trial and error, increasing domain knowledge and in general being able to ingest a large amount of information before running the TWG.
TWG is a good way to evaluate your past decisions. Given the information that you had at the time and if you run a TWG now for this decision, how would your decision change.
“I rather be roughly right than be precisely wrong”. Avoid the craving to go into details of outcomes of trigger that should happen. Keep it as broad as possible. When it comes to figures and statistics, look at ranges and trends not at actual figures down to decimal
Every successful business has done at least a few things right if not many. They have to find a product or service that they are good at. Possess some characteristic that differentiates them from their competitors. Find a market to sell to. And be profitable at the same time.
Businesses in itself are a beast of an animal.
Then there is this special breed of businesses. That can not only do all of the above, but can spawn off other businesses at the same time. By spawning off, I don’t mean extending an existing product line or expanding into nearby verticals. But building entities that are not in their primary field of expertise and building them into independent businesses.
Amazon is a good example of this. Starting from selling books online and expanding that to other verticals is quite logical. But the spawning off of businesses like Amazon Web Services, Amazon Prime, Kindle, not quite. But that did not come for free.
There were 2 major factors that enabled them to do this. Access to capital and ideas for businesses that have the possibility to return high ROI. Internet based businesses have a very high ROI, given the low investment required.
Having both access to capital and serially trying one idea after an other is a deliberate effort for sure. And the more tries you get, higher the chances of success.
Comparative advantage describes how trading parties will choose to produce more of a good that they have a comparative advantage of, and use that to trade for other goods that they don’t have a comparative advantage in. Comparative advantage forms a foundation for international trade.
Comparative advantage is why there are call centers in India, manufacturing in China and highly specialized capital intensive labor in the US. It makes sense for China to do all manufacturing electronic goods and trade it to other countries that are specialized in producing other goods.
Conversely, an oil producing country will have a cheaper access to raw material for chemical products. They have a lower opportunity cost of producing more chemical products compared to countries that do not have access to cheap raw materials. This drives more chemical production in oil producing countries.
However, there are cases where countries, governments and business lobby together to protect niche interests. This can effectively keep foreign, cheaper goods out of the market to protect domestic businesses. However, in the long term, this might not good solution as neighbouring countries will be better off as they have to spend less to get the same goods.
Pricing power allows businesses to price their product or services higher than the rate of inflation and that of the competitors without reduced sales. Pricing power can come from a few ways. A very high quality product. A patented efficiency or feature of convenience that competitors cannot match. Or when a business is operating as a monopoly and barrier for entry is quite high.
A key indicator of the strength of a business is its pricing power That said, it does not mean that if a business does not have good pricing power it is a bad business. However, the opposite has a much higher probability to hold true.
In some businesses untapped pricing power is a good indicator that it is mispriced by the market. To reach such a conclusion one must have an idea on the costs and margins of that particular business against the backdrop of it’s competitors.
High pricing power can materialize as high ROIC over the years. But keep in mind that, high ROIC can be a result of many other factors. Operating and gross margins also provide an indication of the pricing power a company has.
A layman idea that has permeated the investing world is that if you are using a product or service then and you enjoy it, then you should own the stock of the company behind it. This is a good example of why Albert Einstein said “Everything should be made as simple as possible, but no simpler“”. By making a concept simpler than it should be, it has omitted some important aspects of it.
There are a few shortcomings to this idea. The fact that you like it does not mean everyone else likes it. And is also not any indication of what the business might expand into later. It does not give an idea of what it’s competitors are. Maybe the competitors don’t sell or market to where you live.
The business behind it can tell a totally different story. They can be debt ridden. Found malpractice. Or fighting a patent lawsuit. Anything is possible.
Households names are a good starting point. There is something in you that made you purchase the product or service. That in itself is a pre-requisite for a good product. But analysis shouldn’t end there. Looking into the financials and the story of a business is key to investing as much as having a mouth feel of the latest flavour of coke.
Market capitalization is the total cash-value of a business. AKA market cap. The market cap is calculated by multiplying the current number of shares outstanding by the price of one share. For example, a company having 1000 shares of 10$ value would have a market cap of 10,000$.
Companies are usually classified based on their market as small-cap, large-cap etc. Microcap refers to a companies that have much smaller capitalizations. In the U.S. it refers to companies having a market cap of roughly 50-300M$.
Microcap companies are not that popular. And not that well.covered by mainstream media. Hence the volumes traded on these stocks are quite low. This can be risky as it might be hard to offload or buy into large positions.
Since the companies are not that well-covered, the data on these companies are generally good. Less noise overall. And these companies are usually easier to analyse as they have simpler businesses and product lines compared to larger companies.
One of the key ideas for investing well, over a long period of time is to handle as much of thinking using structured methods. Leaving things open and to be decided by chance is an easy way for it to get affected by emotions, biases and the chatter in your head. A downside to using systems to invest is it is very easy to fool yourself that you have found a silver bullet.
“To a man with only a hammer, every problem looks like a nail” – Charlie Munger.
Systematic thought processes can be achieved in many ways. A well-known approach is having a toolbox of mental models. Another popular way is to use algorithms.
An algorithm is a well-defined set of instructions that can be executed to achieve a solution. Algorithms help make the thinking process more deterministic. These algorithms can be based on different heuristics. Screening is a common practice to filter out companies that satisfy different conditions. Usually conditions on various financial ratios. Filters in itself is an algorithm.
Checklists are probably the most simplest version of an algorithm. They are a very “analog”, pen-and-paper way of putting a system in place.
In the context of investing, systems like checklists and algorithms work better when they are not defined down to the last decimal point. There needs to be a variable part to the system that can change depending on the context and company in question. This is where investing turns into something of an art. Knowing when to use what thought process to value a company.
In some cases, the system in place won’t have a variable part in it. And the complete process can be boiled down to a well-defined algorithm. Once the system reaches that state of maturity, computers can take over and do a much better job then us. Algorithmic trading and investing allows to push the boundaries from 2 perspectives. Trades can happen in a whole new time domain. Instead of timing in terms of time of day, trades can be orchestrated with a resolution of milliseconds. Secondly, the limit of quantitative analysis can be pushed considerably if we let computers take care of the complete process.