Regression to the Mean For BTC and ETH Using the MA 1000 - May 2023 Update

In todays TA I'm going to be continuing a series of analyses. I'll recap some important terms here but for a full recap please see this post going over why the MA 1000 is a useful indicator for baselines. I'd like to emphasize that the MA 1000 is not "the" baseline but rather a baseline.

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• The Moving Average (MA): The MA is a stock indicator commonly used in technical analysis, used to help smooth out price data by creating a constantly updated average price. The number that follows "MA" denotes how many data points are being used. So when applied to the daily chart, 1000 days of data are being used.

• Regression to the Mean: In statistics, regression to the mean is when extreme events often regress back to the average. In trading, this is often called a correction (deviating too far from the average and returning to it)

• Why use the MA 1000?: This is where regression to the mean comes in. The more data points you have to inform a mean/average, the more reliable you can consider it. You may then ask why not the MA 2000? The reason is because you have to stop at a certain point. Eventually, you get to a point where you have enough data to inform you where the mean likely is. There is also the central limit theorem which you can test here. Basically, at a certain point things will revolve around the mean and rarely deviate too far from it for too long. For our purposes, we can think of the MA 1000 as an approximate of the mean.

  • MA 1000 = blue
  • MA 200 = yellow
  • MA 50 = red

Ok so on with the show!

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BTC's MA 1000 on the daily chart

https://preview.redd.it/wm5fovcp0oxa1.png?2082&format=png&auto=webp&s=e1cd8fe456170a0056986fb0bfaa4422cbbbd5ba

ETH's MA 1000 on the daily chart

https://preview.redd.it/jq5dti1q0oxa1.png?2062&format=png&auto=webp&s=c57aae24860e33f254eefbb467a4e8dc72191b41

What we're seeing is that BTC is climbing back up to its MA 1000, whereas ETH surpassed it and corrected down below it. We're also seeing other MAs play out as local bottoms. For BTC, we see that both the MA 200 and 50 each acted as a local bottom indicator. For ETH, we see that the MA 200 acted as a local bottom indicator, and that when ETH prices crossed over the MA 1000 they quickly corrected back below.

This post will *not\* be making any predictions about where prices will go. Instead, this post is emphasizing that prices in crypto seem to follow statistical concepts such as regression to the mean. From what we can see, prices do not like to deviate too far from their mean for too long, and that any drastic deviations from the mean are eventually met with correcting back towards it.

I hope you enjoyed!