Fundamental quality is a powerful return driver for stocks. However, the concept of quality can be difficult to define. Business quality clearly includes many soft variables such as the company's competitive advantages and the capabilities of its management team, among many other variables that are hard to measure and quantify.

That notwithstanding, quality can also be analyzed in numerical ways, and business profitability is one of the most important indicators of underlying quality. There is a clear and direct relationship between business profitability and shareholder returns. If all other variables are the same, the more profitable the business, the higher its ability to create wealth for investors over time.

Besides, consistent profitability says a lot about a business. In a free market economy success attracts the competition, and competition erodes profitability levels over time. If a company is consistently making above-average profitability, this generally indicates that it has superior fundamental qualities such as differentiated competitive advantages or a visionary management team.

Quality Stocks by the Numbers

The following quantitative system is based on a ranking algorithm; this is materially different from a screener. A screening system will invest only in companies that meet a specific parameter - for example, the return on equity ratio is over 20% and the operating margin level is above 15%.

A ranking system, on the other hand, will rank companies in a particular universe based on return on equity and operating margin, and will invest in the companies with the higher ranking based on a weighted average of those indicators.

There are basically two ways to measure business profitability. Profitability on capital measures how much money the company makes on its assets, shareholder equity, or investments. On the other hand, profit margins on sales measure how much money the company makes as a percentage of revenue at different levels, considering ratios such as gross profit margin, operating margin, and free cash flow margin.

The ranking algorithm includes both kinds of profitability indicators. In particular, it covers return on investment (ROI), return on assets (ROA), return on equity (ROE), gross profit margin, operating margin, and free cash flow margin.

These factors are not only ranked in absolute terms, but also in comparison with the industry average for each company. Profitability varies substantially across different industries and sectors, companies in the software industry obviously make much higher margins on sales than those in discount retail, for example. This is because pricing power, the cost structure, and industry dynamics are completely dissimilar.

If the system is looking for top quality companies, it makes sense to overweight the sectors and industries that typically allow for superior profitability, so we need to consider profitability levels in absolute terms. In addition to that, if a company is producing profitability levels substantially above the industry average, this is arguably a strong reflection about the company's underlying quality, even if profitability is not particularly high in comparison with the broad market.

In a nutshell, we want to invest in the most profitable companies in the market, and we also want to consider companies with superior profitability in comparison with the industry average. That's the main reason this particular ranking system uses both profitability in absolute terms and profitability levels in comparison with the industry average.

Backtested Performance and Recommended Portfolio

The following backtest picks the 50 companies with highest quality ranking in the S&P 500 index. Since the universe is limited to stocks in such index, all the companies considered are relatively big and liquid, which makes the system easy to implement for investors with different risk tolerance levels. Besides, the portfolio is rebalanced every year, so trading expenses shouldn't be a big problem when it comes to implementation.

The equal weighted portfolio with the 50 stocks selected by the system produced an average annual return of 9.39% since 1999 versus 6.2% per year for the SPDR S&P 500 ETF (SPY). In cumulative terms, the system gained 457.90% versus 216.21% for the market tracking ETF.

In plain English, this means that a $100,000 investment in the SPDR S&P 500 ETF in January of 1999 would currently be worth around $316,200, and the same amount of capital allocated to the portfolio recommended by the system would have a much larger value of $557,900.

Source: Data and charts are from Portfolio123.

Backtested performance should always be taken with a grain of salt, since past performance is no guarantee of future returns. However, there is plenty of statistical data showing that companies with above-average profitability tend to outperform the market in the long term, and this particular system seems to do a sound job at capitalizing on profitability as a return driver.

The following table shows the 50 stocks currently selected by the system, ordered by market capitalization. The table also includes forward price to earnings ratio and return on assets to provide a quick reference about valuation and profitability levels. As you can see, the list includes many of the most powerful and influential corporations in the world.

My preferred approach to implementing quantitative systems is using them as valuable sources for potential ideas to do further research. The numbers are remarkably important, and they provide an objective framework to making sound investment decisions based on time-proven factors as opposed to subjective considerations and opinions.

However, the numbers alone don't tell the whole story, you need to understand the business behind the numbers in order to build a complete investment thesis for a company.