Why Coding Taught Me the Secret of Long-Term Investing
Why I Chose Computer Science
In 2022, I spent almost all my time studying — reading dozens of investing books, learning valuation, accounting, and statistics.
Yet despite all that effort, I lost 52%.
That contrast shocked me.
I realized I was optimizing for information, not intelligence.
Charlie Munger once said that you need to build a latticework of mental models — a way of thinking that connects knowledge across disciplines.
So I decided to study computer science, the subject of thinking itself.
To my surprise, after I started learning it, my returns changed completely.
Over the next three years, I averaged around 50% annual growth — not because I found better stocks, but because I learned to think differently.
In this post, I’ll share why learning computer science helped me become a better investor — and how understanding systems, logic, and feedback loops improved not just my portfolio, but my mind.
Abstraction — The Logic of Investing
Abstraction means rising above the details until you can see the underlying logic.
There are thousands of books about investing, each with its own claim.
But at its core, investing is simple:
It’s buying a piece of a business today to share in the cash it will create tomorrow.
That’s why long-term holding is essential — a company needs time to generate real free cash flow.
In the end, every investment comes down to one timeless question:
Is it worth it?
To think clearly about value, imagine a small coffee shop.
How much would you pay to own it?
How much cash could it earn each year?
Would the return justify the price?
It’s the same logic behind every investment — just with bigger numbers.
That’s what computer science taught me:
to rise above the noise, see the core logic, and design decisions from first principles.
Algorithms — Turning Wisdom into Process
In computer science, an algorithm is a repeatable process that solves a problem.
It takes an input, follows a defined sequence of steps, and produces a predictable output.
But the deeper beauty of algorithms isn’t in the code — it’s in the clarity of logic.
They train you to think in systems instead of emotions — to break big goals into precise, testable steps.
Every algorithm is a repeatable path from chaos to order.
These are my algorithms in investing:
Hold long term → Companies need time to create free cash flow.
I bought UMH; its price went down a lot, and the company struggled — but I gave the CEO time to adjust and operate more efficiently.Stay within your circle of competence AND focus→
Focus on fewer holdings i understand and avoid averaging away excellence.
As Charlie Munger taught, true outperformance comes from a few great ideas held with conviction — not from owning everything.Maintain 20–30% bond allocation →
Stability under any condition builds the right temperament.
When the market drops, you can buy.
When it rises, your holdings rise too.
True steadiness is built on being always prepared.
Debugging — Metacognition in Investing
Investing is a constant debugging process — not of code, but of judgment, perception, and emotion.
Every act of debugging — whether in code, investing, or life — is a feedback loop in motion.
That’s how wisdom accumulates: through observation, adjustment, and refinement.
Debugging is the art of catching your own thinking errors.
It trains patience, precision, and non-reactive awareness — the same skills practiced in meditation and self-reflection.
When you debug code or emotion, you’re doing the same thing:
noticing what doesn’t serve, tracing it to the cause, adjusting, and trying again.
When I lost 50%, I debugged the root cause:
I was too greedy, too arrogant, and constantly comparing myself with others.
So I learned the lesson and adjusted my thinking system.
Over time, this process rewires not just programs — but perception itself.
Each loop refines clarity. Each correction expands consciousness.
Investing algorithms are the architecture of clarity.
Debugging is the process that keeps that architecture alive.
Together, they form a self-correcting loop — a living intelligence that compounds truth over time.
Systems Thinking — Seeing the Whole System Behind Every Decision
Computer science teaches you to think in networks, dependencies, and flow.
When you invest, it’s not only your mind making the decision — it’s your whole system.
Returns don’t come from intellect alone, but from alignment between mind, body, spirit, and energy.
Every layer of life connects:
body → thoughts → emotions → energy → actions → results —
just like a system of inputs → processes → outputs.
In the long run, what determines your return is not just skill or timing —
it’s the efficiency of your entire system.
When my energy is low, my decisions weaken.
When I feel enough, my choices expand.
My clarity in writing trains my clarity in stock-picking.
My physical discipline shapes my mental discipline in the market.
My surrender in relationships strengthens the same muscle that helps me surrender to uncertainty in investing.
Life itself is a system.
How I invest is how I live —
and how I live is how I invest.
End
Most people stay within the walls of each discipline — math in math, finance in finance.
“To the man with only a hammer, every problem looks like a nail.”
Investing is a human activity — an enlarged one.
It’s not only about numbers and charts.
If you focus only on accounting, valuation, and strategies — as I once did — and overlook thinking and temperament,
the market will eventually teach you a lesson.
You might get lucky for a while,
but what you gain by luck will be taken away if you don’t build clarity and character.
That is the law of wealth: before you build fortune, you must build the container that can hold it.
And that container — is you.
The work I am doing — seeing the essence, refining my algorithms through feedback loops, and upgrading my whole being — is how I build my container.
That’s why inner wealth creates outer wealth.
“Go to bed smarter than when you woke up.” — Warren Buffett