What we see when we look at price charts.

Every investor looks at price charts for stocks, bonds, indices, etc. but what exactly are we looking at? How do we perceive these charts and how does that influence our expectation for future returns? Using eye-tracking analysis Huseyin Gulen and Chan Lim provide fascinating insights that can help explain why chart analysis can work.

Chart analysis is often derided (notably more by academics than practitioners) as tea leaf reading. After all, the weak form of the efficient market hypothesis says that prices contain all known information at a given time and hence past prices have no predictive power for the future. But what do I always say about theories vs. the real world?

Using modern eye-tracking technology, the two researchers invited 175 students from Purdue University to look at 40 price charts of stocks in random order. Each price chart was anonymised and comprised 18 months of data. After each round, the students were asked to make predictions about the future return of the stock.

The chart below shows examples of heat maps and scope maps. The top row shows two heatmaps where hotter colours indicate a longer focus of the eye on the data points. These heat maps provide information about the focus of attention. The bottom row shows scope maps (the inverse of heatmaps) where data becomes clearer the more a subject looks at a data point. This is a visual representation of the actual data that enters our brains and helps us make decisions.

Example salience maps.

Source: Gulen and Lim (2023)

Of course, what people focus on in the charts does predict their actual forecasts for future returns and the experiment found that both the levels of the share price as well as the change in share price play an important role in the subjects’ forecasts. Surprisingly, though, the level of share price has a more robust influence on forecasts than the returns (or past movement). This may explain why there are often significant volume spikes around round numbers and why share prices sometimes struggle to break through such round numbers.

But the examples shown above also indicate two other things. First, note that some people focus more on the most recent data points while others take in the whole price history. It turns out that people who focus more on the most recent data points tend to make more trend-following, momentum-driven forecasts, while people who take in the whole price history tend to be more contrarian in their forecasts.

Second, note that typically a lot of attention is paid to turning points and local highs and lows. Meanwhile, points in the middle or periods of sideways movement get less attention. People do use recent highs and lows as their anchors and these anchors influence their forecasts. This of course explains why concepts such as 52-week highs and lows and resistance and support levels make a lot of sense in practice. Because that is what most investors in a market focus on and hence where volume in markets is concentrated. And once such attention-grabbing levels are broken, shares often move rapidly to the next salient price level.

But of course, none of that happens in real life because markets are efficient and chart analysis does not work…