Value Investing: Identifying Quality CompaniesVW Staff
Identifying Quality Companies via SG Investor
As covered previously (link), I discussed on how ROC worked as a form of proxy for ‘quality’ when sourcing for companies to invest in. However, given the backtests, one would notice that other than Japan, ROC does not really add much value compared to using the Enterprise Multiple as a standalone. However, what if there is a more rigorous method in conducting quality checks on companies? In this article, I would be giving an overview of an article: How to Identify Quality Companies that I have been reading and the research results I conducted on the Singapore market.
If you got the right kind of product, you may be paying for taste, you may be paying for a mental association that you have, or service availability. That’s franchise value, then the question is how durable and big is it? I’d say that franchise is basically like a moat around your economic castle.
In the nutshell, a franchise is one that can price its products aggressively and yet still earn high rates of return on capital. More importantly, such franchises have to be idiot-proof in the sense that it is able to handle mis-management. It may seem like a relatively simple strategy of finding companies that are earning high returns. In reality that is far from the truth. Just investing in any company that is earning high returns based on ROA/ROE/ROC would probably end up with a negative performance in the long run. With many of these companies, they may earn one period of high returns, but due to economics, such high returns never last. One of the most basic laws in microeconomics would be that businesses that are doing really well, earning excess returns would attraction competition. Such competition would ultimately result in the erosion of such excess returns. Hence, the key would not only be identifying companies earning high returns, but to find one that is able to sustain it over a long period of time.
Summary of article: How to Identify Quality Companies
- High Returns. As mentioned above, we want companies that not only exhibits high returns but one that is able to sustain it over the long term – 8 years of financial data as used in the article. The author used a geometric mean over an arithmetic mean as a geometric mean would penalise for volatility. Furthermore, Return on Capital was used alongside Return on Assets for robustness.
- Pricing Power and Stable Margins. As with companies with large economic moats, some of the key traits they have would be pricing power and stable margins. For example, the hospital decides to increase the consultation fees charged to patients by 10%. As patients would be say no to that? Given the fact that we actually need medical help, we would be willing to pay the increased consultation fee no matter what. Ultimately, given that the good the company is selling has certain key traits, it results in the demand for the good to be price inelastic. This translates to companies possessing pricing power and more stable margins.
Applying to Singapore market
Over the last couple of days, I have been compiling the 10 year financial data of companies required and double checking the formulas to replicate this screening process to identify companies that trades within the top 20 percentile of the market that exhibits all the above-mentioned qualities.
Upon looking at the results, many would be skeptical about it. Blue Chips (e.g. Keppel Corporation, UOB, DBS, OCBC etc.) do not seem to be there. Most of these companies are penny stocks, are some of the thoughts crossing the minds of most currently. However, what I like to point out would be that with this screening process, certain industries are not applicable such as those REITs, Utilities and Financial Services. Furthermore, a large company does not necessarily mean a great company. If one were to track the share performance of these stocks, one would notice the huge performance one would actually be raking up if invested.
Disclaimer: The authors have vested interest in E5P.SI & 573.SI