Technical analysis (predicting price through patterns)
Technical analysis is the purest form of price prediction.
It doesn't ask what a business does, how much cash it generates, or what it's worth. Instead, it looks only at one thing:
"Based on how this stock has traded before, where is the price likely to go next?"
The idea is that all available information is already reflected in the stock price, and that human behavior—fear, greed, momentum—tends to repeat. If behavior repeats, then price patterns should repeat too.
What this looks like in practice
In the real world, technical analysis looks like charts.
Investors study price movements over time and try to identify patterns or signals that suggest where the price might go next. Some of the most common tools include:
- Trendlines: Drawing lines to show whether a stock is moving up, down, or sideways
- Support and resistance: Price levels where a stock tends to stop falling (support) or stop rising (resistance)
- Moving averages: Smoothing out price data to identify trends
- Chart patterns: Shapes like "head and shoulders," "double tops," or "triangles" that are believed to signal reversals or continuations
- Indicators: Mathematical signals (like RSI or MACD) that suggest whether a stock is overbought or oversold
Simple example: a trader might notice that a stock repeatedly bounces off $50. They label this as "support" and decide to buy near $50, expecting the pattern to repeat. If the stock breaks below $50, they may quickly sell, assuming the pattern has failed.
At first glance, this feels structured—even scientific. There are rules, signals, and repeatable setups.
Where technical analysis gets it right
To be fair, there is a reason technical analysis exists.
In very short time frames, markets are often driven by emotion, positioning, and psychology—not fundamentals. Fear and greed can create momentum. Crowds can chase trends. Prices can overshoot in both directions.
Because of this, some patterns do appear to work, especially over short periods. Traders reacting to the same signals can even reinforce those patterns, at least temporarily.
So there is a kernel of truth here: markets are not perfectly rational in the short run.
The logical problem
Now the key question:
If these patterns are real, repeatable, and mechanical… why haven't they been competed away?
If a simple rule like "buy at support, sell at resistance" reliably made money, large hedge funds and algorithmic traders would deploy it at massive scale. As soon as the pattern appeared, they would act on it instantly—eliminating the opportunity.
Markets are highly competitive. Any edge that is obvious and repeatable tends to disappear quickly.
There's a second issue: interpretation.
The same chart can lead to completely different conclusions:
- One trader sees a breakout and buys
- Another sees a false breakout and sells
- A third sees a longer-term downtrend and avoids it entirely
If a method can give conflicting signals from the same data, it becomes difficult to argue that it's objective or reliable.
The evidence problem
Beyond logic, the results are mixed at best.
While some traders do succeed with technical strategies, broad evidence shows that consistently beating the market using mechanical trading rules is extremely difficult—especially after accounting for:
- Transaction costs
- Competition from faster, better-capitalized players
- The tendency for patterns to break down over time
What often looks like a "working strategy" in hindsight can simply be randomness, luck, or patterns that existed briefly and then disappeared once discovered.
The deeper issue
Technical analysis is entirely disconnected from the business itself.
A stock could represent a company growing rapidly, generating enormous cash, and strengthening its competitive position—and technical analysis might still tell you to sell because of a pattern on a chart.
Or the opposite: a deteriorating business might look like a "buy" because of a short-term price signal.
You are making decisions based on price movements alone, without asking what is actually driving the value of the asset.
Bottom line
Technical analysis is appealing because it feels structured, visual, and actionable. It offers the promise of a repeatable system for predicting price.
And in very short time frames, where psychology dominates, it can sometimes appear to work.
But it rests on a fragile foundation:
- If the rules were truly reliable, they would likely be arbitraged away
- The same data can produce conflicting signals
- Long-term success is difficult to demonstrate consistently
- It ignores the underlying economics of the business entirely
At its core, technical analysis is a bet on patterns in human behavior.
Sometimes those patterns show up.
But building an investment philosophy on them is a very different question.