Part 4: The Two Engines Behind Every Stock Price
Essential Market Knowledge Before Trading Options
Before moving forward with the construction of the model for pricing options and understanding its practical implications for trading, it is necessary to have a clear understanding of what the price of the underlying asset represents and how and why it moves (in our particular case, we are talking about stocks and stock indices).
At any given moment, a stock's price reflects the market's collective assessment of five fundamental components. These factors work together to establish an equilibrium value—the price at which buyers and sellers agree to trade.
Expected Profitability & Growth determines the size and trajectory of future cash flows. Companies with stronger earnings power, higher profit margins, and better growth prospects generate more value for shareholders, commanding higher prices.
Payout Policy affects how shareholders receive value. Whether through dividends, share buybacks, or retained earnings reinvested for growth, this policy determines the timing and form of returns, influencing what investors are willing to pay today.
Macro & Industry Trends provide the broader context. Economic cycles, sector rotation, and regulatory changes can enhance or diminish entire industries regardless of individual company fundamentals.
Interest Rates & Opportunity Cost set the baseline for required returns. When risk-free alternatives offer higher yields, investors demand lower stock prices to achieve competitive expected returns.
Risk & Uncertainty determine the additional return required above the risk-free rate. Business risks (competition, cyclicality), financial risks (leverage, liquidity), and management uncertainties force investors to demand a lower price as compensation for these risks. So the discount factor used considers not only the simple time value of money embedded in the risk-free rate, but also a risk premium.
In equilibrium, these five factors combine to produce a single price where supply meets demand.
If we consider the market as a whole, for example the S&P 500, thereby eliminating idiosyncratic risk, i.e. risk linked to the fortunes of individual companies, then it may be plausible that in the short term the market may have digested the information linked to the five factors examined in depth and returned to a more or less stable price.
In reality, even if nobody learns anything new about the market’s five fundamentals, the price continues to move on.
That’s driven by order‑flow imbalances, liquidity provision, tiny bits of new data (a trader’s opinion, a macro headline), and pure microstructure noise.
This is called continuous diffusion and captures small, frequent random moves, creating an unpredictable path.
These random movements follow a probability distribution that is called log‑normal1 (more on this in the next parts).
This is the “high‑frequency” engine of the price movements.
On a different frequency, the market gets new information on growth, profitability, payout policy, macro trends, and rates.
Those news events can be small (an earnings beat) or large (a surprise acquisition, a regulation shock, a credit crisis, a pandemic).
These shocks change the underlying expected cash flows and/or discount rate, moving the “equilibrium” fair value with sudden jumps.
This is the “low‑frequency” engine of the price movements.
We have:
Engine 1 (High-frequency), which is market microstructure-driven dynamic around a kind of stable fair value2.
Engine 2 (Low-frequency): Actual news about the above five pillars creating discrete jumps to new equilibrium levels.
So, for example:
Ceteris paribus, if expected earnings increase, the price suddenly rises to maintain the required return unchanged.
Conversely, if expected earnings decrease, the price falls to reflect lower expected earnings and maintain the same yield as before.
If risk aversion increases, the price falls to adjust to the required risk premium (always bearing in mind the benchmark represented by the risk-free bond); if, on the other hand, it decreases, then the price rises to give a lower yield.
Not every piece of news leads to a single “clean” jump; sometimes markets digest information gradually, and sometimes changes in risk appetite come gradually too.
But more importantly, news is often poorly digested, and the market returns values that are clearly out of line with fair value.
Fair value gaps may close slowly or abruptly, but are often glaring.
Here is a link to an interesting piece by
on this subject:
And here is the Morningstar fair value page:
https://www.morningstar.com/markets/fair-value
Below is the updated chart.
It confirms what Klement states in his article.
Next time, there will be a brief recap, and we will continue to shed light on the subject.
A probability distribution explains how probabilities are spread across the possible values of a random variable. It indicates the likelihood of each outcome occurring and is governed by a probability law that defines the randomness.
It means there is an underlying mathematical rule (a probability distribution) that tells us how likely each outcome is, even if we cannot predict the exact result.
Black-Scholes assumes pure log-normal (Engine 1 only), but reality includes jumps from the fundamental factors. The market compensates by using different implied volatilities across strikes (more on this in the next parts).