risk

“Without mastering the power is nothing”

Wealth Monaco met the team of GEFIP – an independent portfolio management company where fundamental analysis is reinforced by an in-depth research into the risk / return ratio. In this first article, GEFIP explains its risk quantification and illustrates it through 2 companies: Caterpillar and Air Liquide.

The all-out irruption of technology

From the 90s, at GEFIP we were handling large-scale data with the first quantitative funds and « program trades ».

Throughout the 2000s, we improved our straight market model by including a third dimension: liquidity.

2020 marks a triple achievement: artificial intelligence is interfering in our asset allocation process; our market plan model extends to the American and Japanese zones; and finally, our risk analysis is enriched.

The profitability / risk issue is to management what the engine is to the automobile: its reason to be. The expected gain on a security depends on the future cash flows that the business concerned will be able to generate. The more our expectations differ from those of the market, the more significant the upside / downside potential may be.

Then the risk comes into play… The stronger the risk seems to us, the higher the rate at which we update our future projections will be, thus putting a strain on the value of the company. These are therefore a couple of variables essential to the valuation process.

Quantify the risk

We quantify the risk through three dimensions:

• An operational dimension: we measure the volatility of a company’s results. We consider a “low risk” business to be more likely to deliver less volatile and more “predictable” future results than a risky business.

• A financial dimension: we analyze the quality of the company’s balance sheet. A business without debt is less likely to go bankrupt than a business with debt.

• A stock market dimension: the beta, which measures the sensitivity of a security to market variations.

These three pillars allow us then to determine a risk rating for each of the securities in our investment universes. We maintain a database listing more than 500 stocks in the United States, 320 in Europe and 500 in Japan.

The rating assigned to each of these values allows us to classify our investment universes into 5 risk categories / quintiles. Category 1 corresponds to companies with the best visibility on their future results as well as the healthiest balance sheets.

In contrast, category 5 brings together companies with more impacted profits (economic cycles, restructuring, accidents, etc.) and more fragile balance sheets. The dynamics of earnings growth (and therefore stock market profiles) vary greatly from one category to another (see graph below).

We can see that these two stocks, although belonging to the same industrial sector, have different stock market paths.

CATERPILLAR sells mining equipment and construction tools. Its profits depend on the investment budgets of its clients, themselves dependent on the evolution of mineral prices.

Conversely, AIR LIQUIDE supplies industrial gases for various sectors of activity (health, environment, chemicals, etc.). It operates in an almost oligopolistic environment and benefits from long-term contracts that are relatively independent of the economic situation.

Even if over the period represented (2000-2020), CATERPILLAR achieves a better performance than AIR LIQUIDE, we observe that its profits are much more volatile.

Thus, the point of entry on CATERPILLAR is decisive for achieving significant performance. In other words, it is a stock of category 5 and we will only position ourselves if there is significant upside potential.

This is less true on AIR LIQUIDE, where the value is category 1, so the entry point will be less determining and, as a result, the expected upside potential will be less.

Our classification therefore pursues a double objective in our stock selection work.

First, it tells us, by means of a linear regression1, the discount rate to use for the valuation of the company.

Then, it allows us to calibrate the expected upside potential on a stock: we will indeed be more “greedy” on profiles 4 or 5.

Our methodology finally allows us to define a construction framework for our portfolios.

The table on the following page highlights the structure by risk class of our different investment universes. It should be noted that regardless of the geographic area in which we are located (Europe, Japan, USA), around 30% (40% for the USA) of the universe’s market capitalization is characterized by stocks of category 1.

Conversely, categories 4 and 5 weigh between 20 and 30% of the market capitalization of our universes.

When we look at the last two columns we see that the stocks offering the most visibility and the healthiest balance sheets recorded the best performances in 2020. This seems logical given the high uncertainty characterizing that year. However, the penultimate column reminds us of the value of having riskier stocks whose variations can be rapid and significant. In November and December, the latter largely outperformed the market.

The construction of our portfolios is based on this approach. We ensure that the different categories of securities are well represented, thus favoring a diversified risk management strategy.

In addition to offering a different view from traditional classification codes (sector, geography, market capitalization, etc.), our methodology also allows us to free ourselves from style considerations (growth, value, etc.).

Our risk-taking is thus quantified and we take a critical look at the potential for market revaluation.

Article: GEFIP

Title: Advertising Pirelli

1 Linear regression: statistical model for establishing a linear relationship between two variables. At GEFIP, our model establishes a relationship between 3 variables: the internal rate of return (IRR) of a company, its risk and its liquidity. Our market plan allows us to define, for a given level of risk and liquidity, the remuneration that we are entitled to expect on a security: its discount rate.

Post Author: Wealth Monaco