Hips don’t lie but charts can

As buy-side professionals, we spend a lot of time looking at charts. Every results season, any diligent investor ends up browsing through presentations of at least a hundred companies. Assume, 10 charts per presentation, and we get to 4,000 charts a year — and that’s just quarterly results season. Add to that annual reports, sell-side research, business press, and social media. If looking at charts is equated with facing deliveries in a Test match, most investors are in the Rahul Dravid league.

Charts are a useful tool for presenting information, and most of us in the finance world would rather look at a well-presented chart than read hundreds of words describing it. Yet charts can be potent tools for misrepresentations. They are just a visual representation of data and if numbers can lie, so can charts. On this, Darrell Huff’s ‘How to lie with statistics’ is a good read.

Over the years, we have come across some terrible ones which seem to be created for the sole purpose of misleading the viewer. This article is an attempt to highlight some such charting shenanigans.

Exhibit 1: The New Origin

    

The one thing that we remember from our co-ordinate geometry class in high school is the concept of Origin i.e. the point at which X and Y axes intersect. Origin is represented by (0,0) which means that the point at which the axes intersect is assumed to have zero co-ordinate for both axes. But it seems lot of people have chosen to forget their high-school geometry, as the most common charting shenanigan we see is playing around with the Y axis by starting with a number other than 0. In case of Exhibit 1 (above), with 94. What this achieves is an optical illusion of large growth. While revenues have grown by only 10 percent, the size of the second bar is more than twice that of the first bar giving a false impression of larger than actual growth. A more accurate presentation of the data would be;

Exhibit 1A: The Old Origin

Exhibit 2: The Third Axis

Want to show correlation where none exists? Easy. Insert a third axis with different scaling. In Exhibit 2, the NAV for Fund A (Blue line) went from 14 to 125 in 4 years, a 73% annualized return. At the same time the NAV for Fund B (Orange line) went from 1829 to 3702, a 19% annualized return. That’s more than a 50% annual difference but if we look at the chart, it may seem that both have generated similar return. When looking at charts with two axes, one needs to take into account the varying scales. Better still, ask for underlying data on the variables.

 

Exhibit 3: Gulliver and Lilliputians

In Exhibit 3, it may seem that Stock B (Orange line) has grown its sales much faster than Stock A (Blue Line). Unfortunately, this is a problem which occurs when two variables with a huge difference in values are plotted on the same chart. Stock A has in fact grown its sales over 3000%. On the other hand, Stock B grew its sales by just 135%.

Most of us have seen a similar scale-challenged chart through the COVID pandemic. In that chart, Stock B was new COVID cases and Stock A was COVID deaths.

 

Exhibit 4: Can you read backwards?

Exhibit 4 shows the performance for an unnamed fund. Reasonably good right? That is until we look at the order of the dates. The performance is terrible, but switching the order of dates provides you with a line that trends up. This shenanigan comes from the finance world’s fetish for anything that is upward-sloping.

 

 

Exhibit 5: Creative Liberty

It is somehow assumed that if you are using pictures instead of lines and bars, that gives you the liberty to dispense with scale considerations. In Exhibit 5, a 12% return is a significantly fatter wad of money than a 10% return. A mere 20% difference is being represented by a picture twice the size of the previous one.

When a daily barrage of charts is being thrown at us, we need to be able to filter the good from the bad, and being aware of some of these shenanigans, can ensure that we aren’t being lied to! On this subject, we would recommend reading the book “How to lie with statistics” by Darrell Huff.  

 

This article was initially published on MoneyControl. It is co-authored by Anup Maheshwari, Swanand Kelkar and Dhruv Maniyar.

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