The following is from my annual letter to subscribers. I will be posting the letter soon on the blog
There are a few irrefutable statistics of the India stock market. Over the last 10-year period around 50% of small caps (and roughly the same for midcap), lost money for their investors. Only 10% of the companies in this space accounted for most of the returns of the index.
In such a scenario, rejecting stocks is an equally important task in building a portfolio.
We have been focused on this aspect from the beginning of the model portfolio but have not discussed it in depth. The last two years has brought this factor into the spotlight and I want to share the process we use to filter ‘out’ stocks.
The first step in filtering out stocks is quite simple. I look at an idea and reject it if any of the following conditions are met
- Management has past record of illegal actions or are known for bad governance practices. This is a subjective criterion, but one can filter out the obvious cases
- Debt equity (other than financials) is greater than 1.5
- PE is greater than 60
- Company operates in an industry with poor economics (return on capital over a business cycle has been below 5%)
- IPOs
Some of you may look at this and point out that ‘so and so’ company has been a value creator in spite of meeting some of these conditions.
To this my response is this – An elimination process works on probabilities. If you pick 100 companies which have a very high PE or very high debt, 80% or more will lose money for their shareholders. There will always be some which buck the trend.
I am not trying to win an intellectual contest of picking a winner with odds stacked against it. If you play this game long enough, the probabilities eventually catch up with you.
If the idea survives this step, I move on to the next series of checks. These checks are detailed out in the spreadsheet I upload for every company. I have extracted the specific sections used to reject an idea and uploaded here for reference.
Please keep in mind these checks are not quantitative and there is no mathematical formulae which will throw up an answer. Think of these points as checklist/questions to dig deeper into the company
- Fragility – I added this section recently and use it to check whether the business would collapse if some of these risks materialize. For example – Does the company have a major concentration with a single customer or supplier. What will happen if this partner pulls out?
- Management checklist – I have had this section for a long time and have added to it over the years. There are sub-sections to check if the management actions have been ‘suspect’ in the past and point to unethical behavior
- Accounting – This has an exhaustive list of possible accounting games companies play. I have created this from multiple books on financial fraud and accounting malpractices. 2018/19 had a few repeats and some new ways of fudging accounts
- Risk analysis – I added this section a few years back and it is for a deeper analysis of risks and their probabilities.
As you can see from the file, this is a checklist to ensure that I don’t miss something obvious. At the same time, this will not prevent mistakes from happening. A management may be able to hide some of its behavior for a long time and it may come to light after we make an investment.
These points are not black and white and involve a judgement call on where to draw the line. In the past, I have been more tolerant of management behavior, but have realized that even if a particular idea works out, the long term average of such decisions will be disappointing ( I have called this riding a tiger in the past)
As you will note, this process works on evidence or past history of a company and its management. If that is missing, we are flying in the dark. This is another reason for me to avoid IPOs. In most IPOs, the business has been dressed up for sale and all the skeletons tumble out after the listing.
The aggregate performance of all the IPOs in the last 2 years bears this point. Pointing out a few successes, only proves that they are the exceptions and not the rule.
The downside of this process is that I may end up rejecting a company which turns out to be a success. I am comfortable with that problem as long as I can avoid failures. A portfolio of 20 companies out of a universe of 3000+ stocks means that will we miss a lot of winners.
The more important criteria is to avoid the losers.