Perceptions Are Fundamental. Investing Is A Sociological Game.

In my previous post, Investing from a First Principles Perspective, I built the case for deconstructing investment assumptions to find the irreducible, axiomatic truths of investing success. Today, we build upon that foundation to identify and analyze the single most important driver of all asset prices—a concept that, once accepted, will fundamentally change how you view every chart, every headline, and every position you hold.

After two decades of operating in and analyzing financial markets, I have concluded that all price fluctuations, from the short term fluctuations to the secular trend, are under the direct influence of one powerful concept: EXPECTED GROWTH.

This is not a new term. However, the conventional understanding of it is deeply, structurally flawed. The old model, the one taught in every textbook, assumes that "fundamentals"—earnings, cash flow, margins, and other "objective" metrics—are the concrete reality. In that paradigm, "perceptions," "sentiment," and "psychology" are treated as "noise," a temporary, irrational fog that obscures the "true value" until it inevitably re-asserts itself.

In my view, this is incorrect. The hierarchy is inverted.

Perceptions are the fundamental driver that sets the price.

The "fundamentals" that most investors obsess over are not the final "reality". They are merely one variable type, an important one but not necessarily the most important in any context, that feeds into the much larger, more powerful, and all-encompassing engine of human perception.

This is not a paradox. It is the operational image of a market composed of human beings, not calculating machines. The work of a sophisticated investor, then, is not to calculate a "true value" that exists in a vacuum, but to analyze the inputs of perception. This is a paradigm shift from being a "fundamental analyst" to being a "probabilistic aggregator of perceptual inputs."

Deconstructing the Real Driver: "Expected Growth"

To build this new model, we must first dissect its core driver, "Expected Growth," into its two components:

1. "Expected": The Realm of Subjective Reality

The first word, "Expected", places us squarely and immovably in the realm of human psychology. We are not pricing a static, objective, mathematical reality. We are pricing a subjective belief about the future.

Every single market participant, from the high-frequency trading algorithm (programmed by a human) to the retail trader to the Ph.D. quant, understands "reality" through a unique analytical lens. This lens is colored by their own experiences, cognitive biases, mood, and available information.

When a company releases an earnings report—a "fundamental fact"—two investors can look at the exact same data and reach opposite conclusions.

• Investor A sees revenue growth of 20% and declares it a sign of strength.
• Investor B sees the same 20% growth, compares it to last quarter's 30%, and declares it a sign of critical deceleration.

Which "fact" is right? Neither. Both are interpretations. Both are perceptions. The "fact" itself (the 20% growth) is meaningless until it is processed and integrated into a human-generated narrative. The price will move based on which narrative (which perception) wins the aggregate battle. We are not pricing facts; we are pricing the reaction to facts.

2. "Growth": The Focus on Future Flow

The second word, "Growth", confirms that the market is a forward-looking discounting mechanism. The past is irrelevant, and the present is merely a starting line.

The market is attempting to price the future modification of a business's current status. A static business, one that is expected to be identical in five years, is of little interest beyond its stable dividend yield (which is itself a form of predictable, low growth). The high-multiple, high-return opportunities that define modern markets are priced exclusively on the possibility of a meaningful improvement in their business.

In short, people are attempting to measure the business flow, not its static state. Given this subjective, future-oriented driver, we can easily explain the multitude of opinions colliding in the market. Not only is it very hard to accurately measure the possible evolution of a business, but doing so under the immense pressure of subjective biases makes it a truly daunting task.

The Psychological Engine: Why Subjectivity Creates Trends

If all perceptions are subjective, why isn't the market just a chaotic, random walk? Why do powerful, multi-year trends form?

This is the crucial intersection of finance and psychology. A market built on millions of subjective, competing opinions creates a condition of profound uncertainty. This is not "risk" in the casino sense, where probabilities are known. This is Knightian uncertainty, where the probabilities themselves are unknown and often unknowable.

This profound uncertainty generates anxiety.

Anxiety is an intolerable human state. It demands a coping mechanism.

In financial markets, the most powerful and readily available coping mechanism is herd behavior. Following the consensus, whether that consensus is bullish (FOMO) or bearish (panic), provides immense psychological safety. It relieves the cognitive distress of being alone in your conviction and the anxiety of managing the unknown.

This is why subjective beliefs can lock into powerful, self-reinforcing trends. A "bull market" is not an objective fact; it is a sociological construct, a period where the dominant coping mechanism is to buy, and this collective action reinforces the positive perception. A trend "feels" objective and inevitable, but it is, at its core, a mass psychological consensus.

The New Hierarchy: A Framework for Analyzing Perception

If "Expected Growth" is the driver, how do we measure it?

At any point in time, these perceptions act on prices in an aggregated form via two primary vectors:

1. Exp_Gwth_MKT: The aggregated expectations and perceptions for the macro-economic growth of the entire system.
2. Exp_Gwth_CO: The aggregated expectations and perceptions for an individual company's growth.

These vectors can be aligned (a bull market lifting all boats) or conflicting (a great company fighting a bear market).

The Exp_Gwth_MKT vector is the most important. It is the tide. It sets the overall sociological level of tolerance for price multiples and valuations across the entire market. Anticipating this vector gives you index-level entries. The Exp_Gwth_CO vector is secondary. A strong company vector cannot, in the long run, fight a strongly negative macro vector.

But what forms these two vectors? They are compounded based on several types of variables:

1. Sociological Variables

This is the dominant category. It is perception itself. It is the subjective understanding and participation of the herd. Its components include:

• Popularity and Participation: How many people are connected to the phenomenon (actively or passively)? A narrative known by 1,000 people has less force than one known by 10 million. This is Metcalfe's Law applied to financial narratives.
• Purchasing Power: It's not enough to believe (perceive) a stock will go up. Participants must have the capital to act on that belief. Low interest rates, stimulus, and high savings rates are rocket fuel for positive perception.
• Existent Risk Exposure: How much capital is already deployed? If the herd is fully invested, leveraged, and holding no cash, who is left to buy? At this point, even overwhelmingly positive perception has no potential energy to move prices higher.
• Cognitive Biases: These are the subconscious patterns that shape perception. Recency bias (projecting the recent past into the future), confirmation bias (seeking data that supports a prior belief), and availability heuristic (overweighting recent, dramatic news) are the mechanics of the perceptual engine.
• Mood: This is the emotional overlay on all data. It cycles from optimism > euphoria > anxiety > pessimism > fear >panic. The same earnings report will be interpreted as "bullish" in a euphoric mood and "disappointing" in a fearful mood.
• Investment Knowledge & Information Speed: The sophistication of the participants and the speed at which narratives (information) are distributed. In the modern era (e.g., Twitter/X, Reddit), narratives form and disseminate in hours or even minutes, dramatically accelerating the formation of herd consensus.

2. Fundamental Variables

This is what most consider "investing"—the objective, real growth prospects of a business or economy. In our model, this is not the primary driver. It is only a contributing variable that influences the dominant Sociological vector.

• Real_Gwth_MKT: The real, measurable growth of the entire economy (e.g., GDP, CPI, unemployment data). These "facts" are not drivers. They are data points that the herd interprets to form the Exp_Gwth_MKT narrative ("soft landing," "hard landing," "stagflation").
• Real_Gwth_CO: The real, fundamental growth of the individual company (e.g., financial results, user growth, product releases). This is perhaps the most significant input into the Exp_Gwth_CO vector, but it is still just an input. The reaction to the earnings, not the earnings themselves, is what matters.

3. Structural Variables

These are the artificially imposed rules and market infrastructure that shape how perceptions are expressed. They are the plumbing of the market.

• Derivatives and Automation: The availability of options, futures, and their automated trading can create self-reinforcing phenomena (like a "gamma squeeze") where the structure forces a price outcome based on a perceptual bet.
• Leverage and Short-Selling: These are amplifiers. They do not create perception, but they multiply its force. A small shift in perception can cause a massive, cascading price change via margin calls or a short squeeze.

Redefining the Investor's Goal: Probabilistic Compounding

This new hierarchy changes the investor's job entirely. Entry points are moments when the aggregate direction of the expected growth vectors (Exp_Gwth_MKT and Exp_Gwth_CO) can be anticipated.

This redefines our approach in contrast to the two classic schools:

1. The Classic Investor does not try to anticipate perception. They start from the premise that perception will eventually follow the fundamental variable (Real_Gwth_CO). They try to anticipate the fundamental variable and wait, requiring both excellent understanding and sufficient time.
2. The Classic Trader does not care about the fundamental variable at all. They try to measure the perception vectors (Exp_Gwth_CO and Exp_Gwth_MKT) indirectly and almost exclusively from price reaction (technical analysis / tape reading).

We are not interested in aligning with either theoretical concept. Our goal is to significantly increase the success of anticipation. This implies a probabilistic compounding of all available variables—sociological, fundamental, and structural.

Let's use a practical example:

Imagine a tech company.

• Fundamental Input (Real_Gwth_CO): The company posts 25% revenue growth. (Objectively strong).
• Structural Input: A large tranche of employee options is expiring, creating a large, temporary supply of shares. (Negative).
• Sociological Input (Company): The narrative on social media is focused on a new competitor, and analyst mood is "cautious." (Exp_Gwth_CO is weak).
• Sociological Input (Macro): The Fed has just signaled higher rates, and the macro mood is "risk-off." (Exp_Gwth_MKT is strongly negative).

The Classic Investor buys, citing the 25% growth, and is frustrated as the stock falls 30%. Our model, however, performs a probabilistic aggregation: The strongly negative macro vector, combined with a weak company-level perception and a negative structural headwind, will overwhelm the positive fundamental input. The probability is high that the stock will fall, despite its "good fundamentals". The same Classic Investor will be tempted to label such an approach as "trading" or "speculating". At the same time, the Classic Trader will follow only price action on a chart to identify "support", "resistance", "trend line". The Classic Trader will be tempted to label a strategy which disregards such concepts as "investing". The hard truth is that the ultimate goals is to make a profit, no matter the theoretical label. As long as the probabilities increase, the "label" is irrelevant.

A Practical Framework: The Perceptual Margin of Safety

This paradigm shift demands a new definition of "cheap."

• The Old Method: Look for companies "cheap" relative to their fundamental potential (e.g., a low P/E ratio).
• The New Method: Look for companies "cheap" relative to their perceptual potential. That is, companies with a high probability of increasing aggregated positive perception.

We are no longer hunting for a fundamental margin of safety. We are hunting for a perceptual margin of safety.

This is the gap between an objectively strong fundamental input (Real_Gwth_CO) and an overly pessimistic, and likely temporary, perceptual vector (Exp_Gwth_CO).

Identifying opportunities in individual stocks is genuinely difficult. It requires the cumulative alignment of three distinct conditions:

1. You Must Understand the Fundamental Trend (Real_Gwth_CO)

This is your anchor. You cannot identify a "perceptual gap" if you have no baseline to measure it against. You must have an objective, well-founded understanding of the real business and its products. Without this, you are just gambling on crowd psychology.

2. You Must Wait for the Perceptual Margin of Safety

This is the dislocation. This is the moment when the Exp_Gwth_CO vector becomes detached from the Real_Gwth_CO anchor. This is not just "buying a dip." This is identifying a decline caused by an exaggerated perceptual reaction (e.g., panic) or an exogenous event (e.g., a macro-driven market crash that sells off good and bad companies alike).

Example: A high-quality, fortress-balance-sheet bank (strong Real_Gwth_CO) is sold off 30% during a systemic panic about other, weaker banks. The fundamental reality of the strong bank did not change. Its perception (Exp_Gwth_CO) was exogenously dragged down by the herd. That gap is the perceptual margin of safety.

3. The Entry Must Not Contradict the Macro Vector (Exp_Gwth_MKT)

This is the timing component. It is not enough to find a company with a perceptual margin of safety (Points 1 & 2). If you buy it while the entire macro vector is in a "fear" or "panic" state, you will likely lose more money as the tide continues to fall. The highest-probability entry occurs when the Exp_Gwth_MKT has at least stabilized or, ideally, has just begun to turn positive.

Ultimately, the success of anticipation is directly proportional to the level of probabilistic aggregation. Opportunities are not just stocks; they are combinations of targets, moments, stakes, and time frames, all determined exclusively by this aggregated probabilistic level.

This framework requires a total shift. We should not analyze fundamentals in a vacuum and instead treat them as one critical input into the far more powerful, and ultimately decisive, engine of human perception.

PS: A value investor reading the thoughts above might say: "Yeah ... you're right on the short term, but the longer term is something different". To that I would respond: "Well ... long term is nothing but a sum of short terms" 😄