Understanding the difference between M/M and Y/Y data
Learn how to familiarize yourself with the time periods in data reports
Economic reports are given in a number of different formats. Many economic data releases are reported in a month on month format (m/m) and also in a year on year format as well (y/y). A y/y reading might be represented by the characters, YoY.
Similarly, a m/m reading may also be represented by the format MoM. Regardless of the format of the report, they both mean the same thing. In many instances, both m/m and y/y readings are reported as percentages which allows for easy reporting and comparisons.
At first, these conventions can be confusing, so this article is designed to help explain them and point out the key differences between the readings and, most importantly, how they help investors get a handle on the key data.
m/m or MoM data
The m/m readings are changes in data with respect to the previous month. So, for example, on Friday March, 9 German January factory orders showed a m/m reading of -2.6% vs. a prior reading of +0.9% m/m. This meant that the factory orders for January were down -2.6% on December's figures. As such, this indicated a m/m contraction. For simplicity, the chart below illustrates this trend:
m/m data and a few things to be aware of
One of the most important things to mention is that m/m readings are vulnerable to a number of variables. Is there a major holiday in a month? Take Christmas, Thanksgiving, and lunar New Years for example.
When these events occur, they can impact m/m readings. Similarly, one-off events can impact m/m readings. In the last football World Cup, UK retail sales were positively impacted as England made it through to the Semi-finals of the World Cup.
Many new televisions were bought, more food and drink and, as a result, retail sales enjoyed a spike in the report. In a similar way, m/m readings can also be impacted by natural disasters and other one-of disasters.
Other less dramatic variables can be things such as days in the month and months when people typically take holidays. All of these types of factors mean that m/m readings can vary considerably from month to month. This is why m/m figures are often reported with the more stable y/y figures.
y/y or YoY data
The y/y readings are changes in data over the course of one year in comparison with the previous year. So, as an example, in June 2018 Japanese preliminary machine tool orders reported +11.4% y/y reading vs +14.9% prior y/y reading.
This means that the data, at this point in time, shows only a +11.4% y/y increase as opposed to the previous year's increase of 14.9%. See the chart below.
Calculating y/y data with a working example
To calculate year on year growth you perform the following calculation. Let's simplify this with a fictional example by comparing the sales of a watch company. Say a company sells 200 watches in one year and 220 watches in the following year. How do we calculate the growth rate? You can calculate this as follows:
1. Take away last year's sales from the most recent number e.g.
220 - 200 = +20
The company sold 20 more watches in the present year
2. Then divide that number of 20 by the previous sales and multiple by 100 to get a percentage.
20/200 x 100 = 10%
So, in the listed example we can see that there is a year on year growth rate of +10%.
y/y data and a few things to be aware of
If a company experiences a period of negative growth over one year then the next period that reports strong growth may be more an emphasis on the period of weakness than a particular period of strength.
The worse the prior year, the better the present year will seem. Therefore, it is always prudent to be aware that if a y/y reading is reported that appears very strong, just check what has happened in the previous year.
However, y/y analysis does generally help to smooth out the inherent volatility that you get through reporting m/m data. This is probably the biggest advantage of y/y data; all the ups and downs of m/m reporting (one-of events, seasonality, holidays etc.) are balanced out allowing for simpler comparisons.
A final word on Q/Q data
While covering m/m and y/y data it is also worth covering q/q data. This stands for quarter-over-quarter and these figures compare the previous financial quarter. Each year is broken down into four quarters and the first quarter of the year is referred to as Q1.
There are a number of reports that are broken down into m/m and y/y readings. However, some very important indicators, like Gross Domestic Product (GDP) are broken down into quarters. In terms of volatility q/q data will be more volatile than y/y figures, yet less volatile than m/m readings.
So, there you have it, a quick rundown on understanding the difference between m/m readings and y/y readings.
This article was submitted by the ADSS Research Team.