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

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:

German factory orders

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.

Japanese machine tool orders

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

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.

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