You will be able to state the claims of technical analysis and separate those with evidence from those without.
Scroll through any investing forum and you'll find a chart with lines drawn on it. A stock "bouncing off support", a "golden cross" on an index, a "cup and handle" forming on a chip stock. Marcus's group chat has one most weeks, usually with a confident caption and a rocket. After eight modules on reading accounts and valuing businesses, he wanted to know whether any of it was worth his time, and what the honest answer was.
The honest answer is mixed. One part of technical analysis has serious research behind it, a large part has very little, and none of it promises returns. This module teaches what each part claims and how to test a claim yourself. It doesn't give trading signals, and nothing in it is a recommendation to trade.
Technical analysis studies past prices and trading volume to judge where prices might go next. It ignores the business entirely. A technical analyst looking at Larkspur doesn't care about its customers or margins, only about the pattern its share price and volume have traced.
The fair way to describe it is as a record of how other people have traded. A chart shows where buyers and sellers met, how eagerly, and in what quantity. That's real information about the market. Whether it tells you anything about the future is a separate question, and that's where the evidence comes in.
The starting point for the sceptics is the efficient market idea that Eugene Fama set out in a 1970 review: if past prices held a reliable, exploitable pattern, traders would use it until it disappeared. Its weakest form says exactly that about price history. The research since has found that this is mostly right, with one notable exception.
In 1993 Narasimhan Jegadeesh and Sheridan Titman published a study in the Journal of Finance on US shares. They found that stocks which had done best over the previous three to twelve months tended to keep beating those that had done worst over the following months. The effect is called momentum, the tendency of recent winners to keep winning for a while.
Momentum has since been found in many stock markets and in other asset classes, and in 2012 Tobias Moskowitz, Yao Hua Ooi and Lasse Pedersen documented a related pattern across futures markets, in which an asset's own past twelve-month return tended to predict its return over the following month. It's the one part of technical analysis that has made it into mainstream academic finance and into the factor models that fund managers use. It also has serious weaknesses, sharp crashes and high trading costs among them, which lesson 10.5, Momentum and relative strength: the part with academic backing, covers in detail.
Other claims have weaker records. In 1992 William Brock, Josef Lakonishok and Blake LeBaron tested simple moving average rules on almost a century of the Dow Jones Industrial Average and found that the rules had predictive power in their data. In 1999 Ryan Sullivan, Allan Timmermann and Halbert White revisited the question. They allowed for the fact that thousands of rules had been tried on the same data, which makes some look good by chance, and found that the results looked much weaker and that the best rules didn't hold up in the years that followed.
That pattern, a rule that looked strong on the data used to find it and then faded, recurs throughout this field. Chart patterns such as head and shoulders or triangles have been studied with mixed results, and the ones that look profitable tend to shrink once trading costs and the number of patterns tried are counted. Lesson 10.6, Data mining, overfitting and transaction costs, explains why that happens and how to guard against it.
Here's a claim from Marcus's group chat: "When a stock closes above its 200-day moving average, it keeps rising. Buy the cross." Before believing it, he wrote down what evidence he'd need.
The rule stated precisely in advance, then tested on years of data that weren't used to design it, with every trading cost deducted, and compared with simply buying and holding over the same period, including the worst drawdown each suffered
The chat post had none of these. It showed one chart, of one stock, over the months when the rule happened to work. That's an example, which proves the rule worked once and says nothing about whether it works.
That standard doesn't only apply to charts. It's the same one module 1 applied to fund returns, in lesson 1.5, Annualise, compare periods and spot cherry-picked start dates, and the same one lesson 2.3, Sharpe and Sortino ratios, and when each misleads, applied to smooth track records. A chart claim deserves no more and no less scepticism than a fund manager's brochure.
None of this means you should never look at a chart. Price and volume describe the market you're about to trade in. They can show you whether a stock is in a calm or a violent phase, where many orders sat in the recent past, and whether a move came on heavy or light trading. Lesson 10.7, Use a chart to time entry within a decision made on fundamentals, shows how to use that information to place an order you've already decided on for other reasons. Used that way, a chart is a description of conditions, which is all the evidence supports.
Think of a chart claim you've seen online recently, in a forum, a video or a chat, and get ready to write out the evidence that would make you believe it.
Write down one chart claim you have seen online and the evidence you would need to believe it.
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