Analyze as a spy, calculate as an engineer

Financial markets are a whole universe. They offer everything and for everyone, from complex derivatives to mutual funds.

Analytical approaches also vary - from a lack of analysis through fundamental and macro approaches to esoteric quant calculus. The common thing among all working approaches is that they follow a three-step process: analysis, valuation, and risk management.

High-frequency software analyzes the market structure for a fraction of a second, determines the risk, and takes an instant position. At the other end, we have the same steps - the deep value investor analyzes the company, calculates its value, and determines the risk parameters of the trade.

Today, we will examine the first stage of the investment process—analysis—through the prism of the fundamentals.

One of the best ways to understand something is to compare it with its peers. There are three popular analytical approaches, and each of them answers different questions:

When - Technical analysis - analyzes price movement and uses charts for this purpose. It is best for timing the buying and selling. It does not provide information about the reasons behind the movements, nor can it analyze and evaluate a company.

Why - Macroeconomic analysis - analyzes the three gears that drive the global economy - credit markets, goods and services markets, and currency markets. It uses GDP, inflation, unemployment, interest rates, etc., as input data. It provides reasons for long-term trends lasting more than six months. It is not suitable for market timing or analyzing and evaluating a company.

How much—Fundamental analysis evaluates how much a business is worth and why it is worth investing in. Its indicators measure the company's health, its leaders' quality, and growth potential. However, fundamental analysis is unsuitable for market timing and does not explain why markets and the economy will move in a particular direction.

Each analysis corresponds to one of the following questions: When, Why, or How much? Fundamental Analysis (FA) works in two directions: to describe the business and to evaluate it—qualitatively and quantitatively.

Today’s article will not chew on metrics like the price to book (PB) and price to earnings (PE). They have almost zero analytical value because the majority mainly looks at them. Whenever I think of them, the following thought comes to mind:

When everyone knows something, its informational value tends toward zero.

PB and PE ratios are used for all sectors and industries without considering their peculiarities. They are instruments whose application should follow basic principles. Neglecting them leads to blindly using them.

In today's publication, instead of (useless) ratios, we will examine practical mental models. Most of the principles apply to other fields dealing with complex systems beyond the world of investments. They are helpful when working with variable types and amounts of information.

Mental Models for Analysts and Beyond

Most of the principles described come from seemingly incompatible fields—engineering, intelligence, and psychology—which makes them so powerful. As investors, we need to excel in calculations like engineers, effectively handle information like CIA analysts, and, last but not least, master ourselves.

Stock and flow

The financial statement of a company has the following structure:

Balance sheet - shows the company's assets and liabilities as of the reporting date (end of quarter or year).

Income and expenses - shows the structure of the company's revenues and costs and the resulting net profit for the period (for the past quarter or year).

Cash flow - shows the outgoing and incoming cash flows for the past period (for the past quarter or year).

The balance sheet shows a snapshot of the company's condition at a selected date, i.e., stock variable. It helps us determine solvency, net assets, or other characteristics fixed in time.

The other two statements—the income statement and the Cash Flow statement—report the movement of capital per unit of time, i.e., flow variable. They measure efficiency, return, and liquidity per unit of time.

Correlation or causality

An increase in the price of gold at a constant AISC leads to increasing profit margins for the mining company. This is causality.

An increase in the price of gold and an increase in the price of oil are correlations. Even if there is a cause-and-effect relationship somewhere, it is too abstract to be evaluated.

Graphs showing correlation are too often cited without any actual causality. However, the opposite is claimed - that the change in parameter A leads to a change in parameter B.

The conclusion is that there is an interdependence between the two variables. Unfortunately, this is far from the truth. Deceptive certainty is more dangerous than uncertainty.

We should look for causality relationships when analyzing a company, as in the gold mining company's example. Their strength lies in reducing noise and focusing on the signal. The presence of causality between two variables has a high value of information for our analysis and the final investment hypothesis. They are the signal.

The Five Forces - Michael Porter and Fundamental Analysis

The Five Forces define a business's strengths and weaknesses. They can be used to analyze an individual company or an industry/sector.

The impact of the Five Forces depends on the industry in which the analyzed company operates. It will significantly differ for Apple, Agnico Eagle, and Met Life.

The Five Forces are as follows:

·?????? Barriers to entry - legal, technical, and economic barriers that limit the entry of new competitors.

·?????? Potential substitutes: can the product be replaced with a suitable alternative?

·?????? Bargaining power of customers - to what extent can customers negotiate the product's price?

·?????? Bargaining power of suppliers - to what extent can the suppliers determine the prices of goods and services necessary for production?

·?????? Intensity of competition is the number and strength of competitive companies.

Every company depends on these five forces. How it copes with them predestines the business's development. Our fundamental analysis must necessarily analyze the Five Forces. They will show us the business's advantages and disadvantages.

Know your people

Often, we focus only on financial statements and forget that companies are managed and owned by people.

The analysis of people has two aspects:

·?????? Who manages the company – managers and directors?

·?????? Who owns the company – major shareholders?

Assessing people cannot be done using business analysis formulas. It is a qualitative exercise, which makes it difficult. However, this does not detract from its importance.

The criteria are simple: managers should have skin in the game, industry experience, and history with the company. All three are essential, and their presence or absence says a lot.

High Order Specialization

We must build our circle of competence to make us as adaptive and operational as possible in the financial markets. By accumulating knowledge and skills, we seek a balance between the two extremes—hedgehog and fox.

The hedgehog specializes narrowly in one area and remains blind to everything else. The fox knows many places, but it is superficial.

The balance between these extremes will define our circle of competence. We aim to be high-order specialists, which means we need to know a little but enough in enough areas.

High-order specialization applies to analytical approaches, financial assets, industries, and regions. There are several main analytical approaches, and each has many branches. Fundamental analysis is no exception.

In the financial markets, there are many instruments to express our hypothesis - funds, indices, debt securities, stocks, currencies, and derivatives.

In the USA alone, there are over 4,000 publicly traded companies. They operate in all sectors, including dozens of industries. We cannot be familiar with banking, supermarkets, telecoms, uranium mining, shipping companies, and pharmaceuticals in detail.

We chose a few industries that we understand very well. At the same time, we are always ready to take advantage of opportunities in sectors and regions we do not know as long as they meet our strict criteria for business quality and carry asymmetric risk in our favor.

High-order specialization makes us operational and adaptive - we take maximum advantage of circumstances instead of complaining about them. Returning to the metaphor of the hedgehog and the fox, we must be hedgehogs possessing the cunning of a fox as high-order specialists.

The Paradox of Choice

The more choices we have, the more indecisive we become. This principle applies to any situation with multiple options.

In financial markets, this manifests as so many seemingly great companies that we cannot filter out the perfect ones and buy everything that catches our eye. We have a too-diversified portfolio of companies with average quality at best.

Fundamental analysis helps us filter the abundance of opportunities. The most effective way is to set high criteria for each variable we analyze. Thus, a large portion of "incredible" companies will quickly fall away.

Survivorship Bias

People love success stories and ignore failures. Yet, the most significant lessons are often hidden in stories about misadventures. Behind every Barrick Gold, there are hundreds of failed junior miners; behind every successful business, there are many bankrupted businesses.

In fundamental analysis, we focus on the best companies in the sector and neglect those at the tail end. The latter is important not as an investment case but as a lesson on why a company can fail. Analyzing failed companies yields much information on what NOT to do, which is often more important than knowing what to do.

Information Asymmetry

Information is not evenly distributed among shareholders, directors, and managers. Equity owners have access to the least amount of information, which disadvantages them. Therefore, we analyze not only quantitative parameters but also qualitative ones. The latter refers to people.

This will not eliminate information asymmetry but tell us how much we can trust these people. Complete trust cannot be achieved, but it can be good enough to compensate for information asymmetry.

At the same time, information asymmetry harms us in another way - by allowing managers to manipulate a company's financial statements. Using alternative valuation methods does not nullify this fact but reduces its impact.

An example of an alternative approach is using the cash flow statement to analyze a company's efficiency, as it is much harder to manipulate than the income statement.

When working with quantitative parameters, using less popular valuation methods is helpful. Popular metrics are used by everyone, which reduces their informational and predictive value. This strengthens the adverse effects of information asymmetry.

The Checklist – the analytical process described step by step

Knowing what to do is not enough. We need to understand the sequence and essence of the actions.

This is precisely the role of checklists. They remove the burden of constantly thinking about the process and its steps. Thus, it protects us from biased and hasty decisions – we follow each step until the end of the list.

Checklists are exceptional tools that are not used by chance in industries where one wrong action can lead to a cascade of disasters.

The tricky part is creating a checklist because it must include everything necessary but without excess. The goal is to collect sufficient information that leads to an analysis with high predictive value.

It should contain at least the following elements:

·?????? Business description – activity, competitors, specifics of the business/industry/region

·?????? Liquidity is the company's ability to cover its expenses.

·?????? Solvency – the company's net worth

·?????? Efficiency is the company's ability to generate profit and return on investment.

·?????? People – managers and partners

The data extracted from each step is the foundation for creating an investment hypothesis.

These mental models are inspired by diverse fields. However, they have one thing in common: they help us handle a large amount of data in an environment of constant uncertainty. Their primary strength is protecting us from our worst enemy, the man in the mirror.

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