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Aim for the stars! #inspiration 🀩

Nooooooooooooo. Not like that!

I've been thinking about averages and how/why we use them to decipher economies, markets and pretty much everything else.

Averages can be useful, but they're also open to abuse and risk feeding our bias.

Recent CPI data is an excellent example.


The Consumer Price Index (CPI) is the most widely-used measure & tracks the value of a basket of goods that 'most people' would consume.
There are plenty of flaws with the index and how it is calculated, so it's best to think of this the same way as we think of the BMI to measure obesity: Broadly accurate, yet imperfect.

The whole point of CPI is to measure the AVERAGE cost of living.

Due to the semiconductor shortage, new car production hasn't been able to keep pace with demand, so people have increasingly turned to the used car market.

As a result, prices have increased drastically...



That's had an out-sized impact on the overall CPI readings and energy has joined the party now too. πŸ‘‡



Now, food and energy can be more volatile, with prices spiking in one direction & then the other so they are typically separated from core measures which are usually seen as more stable (such as vehicle and shelter costs).

Why does this matter?

CPI is a measure of the average cost of living.

In the case of the US, it's the average cost of living for around 333 million people...

Over the past decade, roughly 15 to 20% of the US population bought a new or used car in any given year πŸ‘‡


Statista

Which means that in any one year, the majority of the population won't buy a car...

Research by R.L. Polk says that the average age of a modern vehicle is 11.4 years, while the average length of time drivers keep a new vehicle is 71.4 months β€” around 6 years...

Fair to say that on average people change vehicles every five to six years?

So, this part of the average cost of living metric we're using only applies to a minority of the population once every five or six years...

Under 'normal' conditions averages can be a decent barometer.

Between 2016 and the start of the pandemic used car prices fluctuated a percentage or two either side of 0.

Some months they'd go up a bit, others they'd go down a bit. πŸ‘‡



That all changed with Covid but the calculation of the average cost of living (CPI) didn't.

This isn't to say that inflation isn't impacting the everyday person in the states. It certainly is to varying degrees.

Although everyone experiences it differently, and the variance in those experiences is likely wider than usual.

Let's take two extremes to illustrate.

Person 1: Owns their own home, remote worker, bought a new car in Jan 2019, runs an off-grid renewable system.

Person 2: Rents, drives to work, just had to buy a used car because theirs packed up, lives in a draughty old house somewhere in the depths of North America.

Person 1: "What inflation?"

Person 2: "Inflation is KILLING me, and I have no idea how I'll afford to heat this house through winter"

Entirely different experiences that the average metric is supposed to normalise for.

The variance between these extremes is wider than usual, so the average isn't as reliable as it normally would be...


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And variance is a really important factor when looking at averages.


Variance is a measure of dispersion: how far a set of numbers is spread out from their average value

I'll let you into a secret.

I'm an excellent trader and I want you to back me with an investment of €100,000.

I've taken my trading metrics and put them into a simulator.

On average, I'll be able to return €257,373 after 100 trades. Β 

You in?

Come on.... it's a no brainer! Β 

"Show me the simulation FIRST"


equitycurvesimulator.com/

Not for the faint-hearted. There's a yuuuuuge amount of variance around that black line, even though on average the strategy has a positive expectancy.

(and that's based on the assumption it's executed perfectly) Β 

Let's try a different, more conservative strategy πŸ‘‡



A much narrower dispersion around the average.

Looking at it in this way also adds a degree of certainty to the only question that really matters....

If I invest am I more likely to lose money or make money?

In the first strategy quite a few of those lines end up below the initial investment amount, even after 100 trades. Β 

In the second strategy, ALL of those lines are positive after ~60 trades.

Both strategies have a similar average performance, but which would you prefer to back...?


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Whats the takeaway?

This passage sums it up perfectly Β πŸ‘‡


And that is the basic problem with averages: they can hide what you need to know.
Averages hide variation. Averages are simple to calculate and are sometimes a lazy way of determining past performance.
One of our clients once told us that the key to understanding what drives performance is not to exclude outliers, but to study them. By looking at the best and worst months over the last year, he learned what most impacted his results.
Averages can be helpful for many things, but with problem solving you need to be very careful about understanding what the numbers are actually telling you, or aren’t telling you.

Don't know what financial news stories are important and what is complete bullsh*t? Hop onto our filtered news channel.

It's completely free πŸ‘‡πŸ‘‡πŸ‘‡


Macrodesiac News Channel
You can view and join @MacrodesiacNews right away.

And if you really want to get to grips with how global markets and economics work, with trade ideas to give you actionable context, then come and join us as a premium member where you're likely going to get a nice Market IQ boost. πŸ‘‡


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