Start Here
Not the black box version. Not the Silicon Valley version. The real version — the one that's been sitting in math textbooks since before anyone called it an algorithm.
The Plain Truth
That's it. No mystery. An algorithm is just a defined process — you put something in, you get something out. The math determines how reliable the output is.
As far as the math goes, any algorithm can be created where the outcome is an absolute certainty — but only if the inputs are certain. That's the catch. And that's the whole game.
When you create your own algorithm, the outcome will only be as certain as the inputs you choose. Which means the better you know your inputs, the more powerful your algorithm becomes.
y = mx + b
// The simplest algorithm there is
Plot a straight line on a chart. That's mx+b. That's a stock price rising at a steady rate. That's an algorithm. Everything else is just a more sophisticated version of this same idea.
Three Things To Understand
01
The output is only as reliable as the inputs. A perfectly constructed algorithm with bad inputs gives you a perfectly wrong answer. Your inputs are everything.
02
The more data points you use, the more accurate and smooth your prediction line becomes. Fewer points means more uncertainty — and a less predictable result.
03
If you can arrange variables based on your own expertise, you can build an algorithm that verifies facts you already know. That's not cheating — that's the whole point.
Start Building
Before any math, any code, any tool — you need to know what you're trying to predict and what you believe influences it. Fill this in and you've already built the skeleton of your first algorithm.
// This is your starting framework. The more you refine your variables and test against historical data, the more reliable your output becomes. Save this, run it repeatedly across different time points, and look for the pattern that emerges.