How Was Fundamental Analysis Born?

By definition, Fundamental Analysis is the analysis of a company’s condition, or health. It also covers the market potential, considering the evolution of the market and the activity of its competitors.

In the classic formulation by Benjamin Graham, the father of value investing, fundamental analysis was based on the in-depth analysis of the company’s assets. It also considered the ratio between recent profits and the overall company’s market valuation.

Until this day, “The Intelligent Investor” by Graham (1949, re-edited until the fourth edition in 1973) remains the bible for all value investors out there.

Fundamental analysis assumes that the market price of an asset reflects its true intrinsic value. As a result, fundamental analysts are looking for stocks that are under-valued or overvalued and to make a decision if to sell or to buy a particular stock or asset.

Fundamental analysis differs from technical analysis, searching for statistical trends in the stock’s price and volume. However, both methods are applied to forecast future trends in stock prices. As a result, that to minimize the financial risk of buying or selling stocks.

Value investors still look into the company’s books and analyze the overall situation in the market. This includes the political situation, interest rates, employment, the housing situation, and income per capita, all considered while making investment decisions.

However, is this formulation optimal when it comes to evaluating businesses in times of Digital Transformation? Especially, online businesses based on software rather than manufacturing and protected Intellectual Property such as patents? Let’s take a closer look.

Do New Ventures Borrow Value From the Future?

But what about new companies operating in the field of new technologies, such as quantum computing, blockchains, or tele-health? These are exactly the sectors where business intelligence for market analysis has to work differently. 

Investing in this area is often referred to as “speculative” to the fact that the prices of assets and companies operating in these markets are explosive. Stanford research by Gornall and Strebulaev found just how distorted this can get: studied unicorn startups’ headline valuations were, on average, 48% higher than their actual fair value, with nearly half not really worth the $1 billion mark they claimed. 

They don’t follow the same dynamics as more “traditional” companies based on manufacturing, construction, or engineering. This also applies to trade or services involving human factors, such as consulting, education, or job market management.

Indeed, the valuation of these new ventures varies a lot which is mainly because they are hard to value. This is because, in times of digital transformation, the fundamental analysis following traditional measures such as the price-to-earnings ratio (also known as “P/E ratio“) is simply impossible.

These new businesses are often community-driven, running on the enthusiasm of their developers. Additionally, designed to grow for a long time before they will eventually generate any earnings. Or, before the service they provide will get adopted by businesses and individuals.

To be real, in most cases the price-to-earnings ratio of these companies is flat at zero. That’s why the valuation of these businesses is based on the prediction of future potential rather than on the current state of affairs. 

Since these predictions follow the current sentiment in the market. Additionally, the crowd’s group fearful or greedy reactions potentiate the price fluctuations on top of that, the prices jump up and down like crazy. 

But does it mean that the new businesses created in the times of digital transformation have no intrinsic value at all? Of course not. It just means that the approach to the Fundamental Analysis should get adjusted to this new reality.

How To Do Fundamental Analysis in Times of Digital Transformation?

As mentioned before, new projects often have no physical assets and no patents, since they are based on software. Their value is also conditioned on the future, so the rules of classic fundamental analysis don’t apply.

According to Ocean Tomo’s Intangible Asset Market Value Study, intangible assets now account for roughly 92% of the market value of S&P 500 companies, up from only 17% in 1975, a shift every business intelligence trends for 2027 forecast has to reckon with. A Federal Reserve Bank of Chicago analysis traces a parallel shift in investment itself: intangibles (software, R&D, business processes) have grown from about 7% of total U.S. investment in the 1950s to roughly 27% today.

In this situation, the following three factors become the grounds for the fundamental analysis, and they are just as relevant to how to use business intelligence for decision making today.

1. The Assessment of the Potential of the Whole Market Sector.

The first fundament is the potential of the whole sector. History knows examples of heavily overvalued markets, the most famous being the tulip mania in the Dutch Golden Age. During this frenzy, the bulbs of rare and fashionable tulips could cost as much as a house or even a ship. 

As it soon turned out when the bubble popped, the value of the whole tulip industry was flat at zero. When the crowd stepped away from tulips as a store of value, their price rapidly dropped toward zero. A study in Financial History Review found the crash was even more extreme than once thought: prices fell by roughly 99.999% within about a week once the market could finally see how many bulbs had actually been planted.

Hence, the first question should be: does the whole market have potential? What is the scope of the possible applications? Is this another revolution such as the Internet thirty years ago, or is it yet another bunch of tulips?

2. The Relative Novelty of the Project.

The second aspect is the value of the project compared to other projects in the same space. Is the difference quantitative or qualitative?

As Peter Thiel likes to say, successful companies don’t compete; they innovate and become leaders of their niche, and they realize their specific business development plan.

Therefore, the question is: what is the added value of the project? What new functionalities does it offer? Are these functionalities easy to copy or reproduce?

This sounds trivial, but in practice, there are lots of similar projects that go forward head to head. Clearly, though, there is only space for one player who wants to realize this specific business development strategy in the market.

3. People.

The last important aspect is the credentials of the people involved, a factor that resists easy data-driven business decision making more than the others. This one is tricky too! Even the best idea will remain an idea without the proper execution, something no business intelligence dashboards for executives can fully capture on its own.

Yet, people who become authorities in a certain area even if they work on their professional development as well, often enjoy the aureola effect and proceed to launch new ventures and sign them with their name despite the lack of proper credentials. As a result, projects with a few famous people on board can still fail. A study in Entrepreneurship Theory and Practice confirms founder and board prestige acts as a real credibility signal to investors, reducing IPO underpricing — but a signal is not a guarantee, which is exactly why it can still mislead.