The Three Forces That Shape Every Return: Deconstructing Market, Skill, and Noise

The Morning That Looked Simple

Three colleagues were supposed to attend a conference across the city. All three lived in the same neighbourhood. Same starting point. Same destination. Same city traffic waiting for them.

But each chose differently.

Amit, the youngest among them, looked at his bike and decided instantly. “Bike is best. I can weave through traffic. Fast and flexible.”

Vidita, practical and calm, paused for a moment. “I’ll take an auto to the metro station and then the metro. It’s predictable. I can even revise my notes.”

Dr. Rao, the senior professor, simply waited for his car. “Comfort matters,” he smiled. “It’s going to be a long day. No need to start it stressed.”

Three people. Same place. Same goal. Three different choices.

Nothing unusual so far.

What the City Threw at Them

As they started, the city did what cities always do.

Traffic built up near the main junction. One road was blocked for emergency repairs. A political rally slowed an entire stretch. The sky darkened, and a light rain began. At one signal, an accident created a long jam.

Nobody planned these events. Nobody chose them. Yet all three faced them.

Amit slipped through side lanes on his bike, constantly alert and adjusting. Vidita’s auto crawled in traffic, but once she entered the metro, movement became smooth and steady. Dr. Rao’s car moved slowly, but the comfort inside insulated him from the chaos outside.

Same city. Same obstacles. Different experiences.

Something else happened too — things specific to each person’s choice.

Amit’s bike developed a minor chain issue midway. Not a city problem. Just his bike. He fixed it quickly and moved on. Vidita’s auto driver took a longer route because that was the route he knew best. Not a metro issue. Just that driver’s choice. Dr. Rao’s car had excellent suspension, so bad roads felt gentler to him than to others. Not a road issue. Just his car’s feature.

City-level events affected everyone. Vehicle-specific events affected only that person.

By late morning, all three reached the conference venue. Not at the same time. Not with the same comfort. Not with the same stress. But they reached.

Return = Market-driven return + Skill-based return + Random noise

What This Simple Journey Reveals

If we pause and reflect, this ordinary morning reveals something important.

Every outcome — including investment outcomes — is shaped by three forces. First, the choices and skill we bring. Second, the environment in which everyone operates. Third, random events that nobody controls.

You influence the first. Everyone experiences the second. The third simply happens.

This is not just a story. This is structure.

And investing works exactly the same way.

Return and Risk Are Not the Same

Before going further, one distinction is essential.

Return and risk are not the same.

Return answers a simple question: What happened to my money?

Risk answers a different one: How uncertain was that outcome?

Many investors mix these two, which creates confusion. Finance treats them separately — and for good reason.

Let us first understand how returns are created.

How Returns Are Created: Three Sources

Whenever you earn or lose money in the market, that return comes from three sources:

your skill, the market you are in, and randomness.

This can be expressed simply as:

Return = Market-driven return + Skill-based return + Noise

This mirrors our journey perfectly.

The city and traffic represent the market.

The vehicle represents your choices and skill.

The unexpected events represent randomness.

Sharpe’s Way of Explaining Return

Academic finance captures this idea through the Sharpe Single Index Model, which represents return as:

$$R_i={\alpha }_i+{\beta }_i{R}_m+{ϵ}_{\mathrm{i<span\; style="text-align:\; justify;"></span>}}$$

Behind these symbols is a very intuitive idea.

The term βRₘ represents the part of return driven by the market. When markets rise or fall, most investments move with them to some degree.

The term α (alpha) represents stock-specific or skill-based return — the value added by selection, judgment, discipline, and structure.

The term ε (epsilon) represents noise — random variation in returns that cannot be explained by either market movement or skill.

In simple words:

Your return = what the market gave + what your skill added + what randomness created.

Nothing mysterious. Just structure.

Now Let’s Talk About Risk

Return tells you what happened.

Risk tells you how uncertain that journey was.

Risk also has structure.

Finance breaks total risk into two components:

systematic risk and unsystematic risk.

Systematic risk belongs to the market itself. Economic cycles, inflation, interest rates, global events — these affect everyone. Just like traffic and weather affect all commuters, systematic risk cannot be diversified away. It is the cost of being in the market.

Unsystematic risk belongs to specific choices. Company-level issues, sector problems, management failures — these are risks tied to individual assets. Unlike market risk, this risk can be reduced through diversification.

In our story, traffic and weather were systematic. Amit’s bike chain, Vidita’s auto driver’s route choice, and Dr. Rao’s car features were unsystematic — specific to each vehicle.

How Risk Is Measured Academically

Finance measures this uncertainty formally as:

$${\sigma }_i^2={\beta }_i^2{\sigma }_m^2+{\sigma }_{{ϵ}_i}^{\mathrm{2<span\; style="text-align:\; justify;"></span>}}$$

This simply means:

Total Risk = Market Risk + Asset-Specific Risk

The formula separates how much of your return variability comes from the market and how much comes from your specific choices.

Clearing the Common Confusion

One important clarification is necessary.

Alpha is not unsystematic risk.

Alpha is about earning more through skill.

Noise is not the same as unsystematic risk.

Noise is about randomness in outcomes.

Unsystematic risk contributes to variability in returns and shows up partly as noise, but noise is broader. It includes timing effects, sentiment, shocks, and chance events.

In short:

Alpha is about ability.

Unsystematic risk is about vulnerability.

Noise is about randomness.

Different concepts. Different roles.

That morning, Amit, Vidita, and Dr. Rao all reached the conference.

Not in the same way.

Not with the same comfort.

Not with the same experience.

But they reached.

Investing works the same way.

Same market. Same economy. Same global uncertainty. Different choices. Different structures. Different outcomes.

You cannot control the city.

You cannot stop random events.

But you can choose your vehicle wisely and design your journey thoughtfully.

When Skill Meets Its Limits

Each of the three colleagues began the journey believing they had made the smartest choice.

Amit trusted his riding skill and agility. Vidita trusted planning and predictability. Dr. Rao trusted comfort and experience. None of them were wrong — and yet, none of them were fully right.

The rain reduced the advantage of speed. Traffic diluted the value of planning. Roadblocks slowed even the most comfortable ride. The city did not reward intelligence consistently. It simply imposed its conditions.

Markets behave the same way.

There are periods when skill shines and selection is rewarded. And there are long phases when the environment overwhelms individual decisions. Random events, regime changes, and broad market forces often neutralise even well-thought-out strategies.

This does not mean skill has no value.

It means skill has limits.

Over time, this is where many investors begin to understand why market-aligned approaches, such as index investing, tend to work so well. Not because they are clever, but because they are humble. They do not assume the ability to outthink the market every year. They accept that the market itself is the dominant force, that randomness cannot be eliminated, and that participation matters more than precision.

Index investing does not rely on being right about specific stocks or sectors. It works by staying aligned with the market, absorbing its long-term growth, and quietly sidestepping the fragile task of consistently proving skill in an uncertain world.

When investors forget the limits of skill, they start believing that outcomes are proof of intelligence.

When they remember those limits, they stop trying to challenge uncertainty and start designing portfolios that respect it.

And that shift — from proving skill to respecting structure — is often where investing truly becomes calmer.

Final Thought

Investing is not about predicting every turn in the road.

It is about understanding the structure of the journey.

Returns come from your skill, the market environment, and random events.

Risk comes from market uncertainty and asset-specific uncertainty — one you must accept, one you can manage.

Once this is clear, money stops feeling mysterious.

It starts making sense.

And that is the real Money Vichara.

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Academic Note (for interested readers)

The return decomposition used in this article is based on the Sharpe Single Index Model, where asset returns are expressed as the sum of a market-driven component (βRₘ), a stock-specific excess return (α), and a random error term (ε). Risk decomposition follows standard portfolio theory, where total variance is divided into systematic (market) risk and unsystematic (asset-specific) risk. While unsystematic risk contributes to return variability and appears in the error term, it is conceptually distinct from alpha, which represents skill-based return.

Return Decomposition (Sharpe Model)

Component	What It Means	Journey Analogy	Control
Alpha (α)	Skill-based excess return	Choosing the right vehicle and using it well	Yes
Beta × Market (βRₘ)	Market-driven return	City traffic, roads, weather	No
Epsilon (ε)	Random noise	Accidents, rallies, sudden rain	No

Risk Decomposition

Risk Type	What It Represents	Journey Analogy	Can It Be Reduced?
Systematic Risk	Market-wide uncertainty	Traffic, weather, city conditions	No
Unsystematic Risk	Asset-specific uncertainty	Bike issues, auto driver choices	Yes (through diversification)

Money Vichara

Understanding money beyond numbers