MaliceM13

Bitcoin Historical Volatility new low

Education
BITMEX:BVOL24H   Bitcoin Historical Volatility Index
Here we have the BTC historical Volatility Index in blue. Orange is the price of BTC. The teal line is the 50sma for volatility. At the bottom, I have the correlation coefficient (CC) for the volatility index with BTC. I have marked in green when the CC reaches above 0.50, and red when it crosses below -0.50. The fibonacci retracement is fairly arbitrary, but fits nicely between 0.25 and 1.00. In this article, I would like to discuss a little bit about volatility. It is often associated as going up when price goes down, but is a bit more specific in what it is telling us than simply being an inverse price indicator. Next, I’ll talk about the correlation coefficient. It is an excellent tool that every trader, and investor, should learn to use. Finally, I would like to examine some of the similarities between our recent all time low in this index, breaking the low 2018, which proceeded the infamous 2018 capitulation event.

Volatility is always an interesting indicator, and is often used to indicate position risk for the asset it is being calculated for. Simply stated, it is a measure of how much the price of an asset moves in a particular period of time. However, it can be calculated a number of different ways. The most common is standard deviation, or how far price is from an average of the price over a recent period of time. The amount of time the data is taken from can also change how the volatility measure acts and how useful it is. More so, because it measures movement, and not so much direction, it can be difficult to use it in an accurate way, as correlation appears to be inconstant at face value. Historical volatility is calculated a little differently. And honestly, before reading a few papers on it for this essay, I had not realized that ‘historical’ referenced the calculation method as opposed to it being the history of the volatility. Historical, or realized, volatility is an estimation of the standard deviation of the price of returns over a particular period of time, in this case, 24 hours. It can also be calculated with a weighting for the trading volume over the calculation period. I have placed a 50ma (150 day moving average) to show a general range for average volatility, and we can see that MA tends to oscillate between 2.5 and 5.0.

The correlation coefficient is an excellent indicator that allows you to see, and quantify, the correlation of your current chart with any other chart ticker. Here I have it set to the BLX all time price index for BTC. The higher it goes, the more correlated the movement of the 2 charts are, and below zero indicates an inverse correlation. When CC is near zero, the movements of the two charts are NOT correlated. One of the issues with volatility indexes is their accuracy can vary, and is sometime disputed. My goal in using the correlation coefficient with this index is to parse out when volatility is most useful to pay attention to, and in which direction. On this chart, we can see that when volatility spikes above 10, it is often correlated with big, sudden moves to the downside. However, not all of them are. By using the correlation coefficient, we can parse out the direction of volatility. When CC is in the green, and volatility increases, we see the price of bitcoin moving up, usually in an explosive manner. Likewise, inverse correlation is often showing us downwards movements. I find this a useful way to pull a little bit of the noise out of the volatility index.

The previous all time low in volatility of 0.35 occurred on October 28th of 2018, and about sixteen days before the 2018 capitulation event began. About a week ago on Christmas day, we broke that low, going down to 0.34. Very low volatility tells us that price isn’t just moving sideways, but is pretty flat for the most part. And if you have been following bitcoin lately (bless your soul) you know flat and boring is kind of an understatement. The good news is that it’s likely going to get exciting soon. Volatility doesn’t seem to stay at or below 1.0 for very long, and seems to be either correlated, or inversely correlated with price within a few weeks to a month after reaching 1.0. An exception would be from August of 2019 to the pandemic crash in 2020. We can see some similarities in both volatility and the correlation coefficient between the time leading up to the 2018 capitulation event and our recent data in 2022. Price action is also fairly similar (flat and boring) with the exception that in 2018, the line chart had a small move down and back up during the flatness, while we had a small move up and then down earlier in December. Although, I doubt this really means anything. In 2018, we saw a 50% drop after price had already fallen around 70%. From top to bottom, the draw-down was just under 85%. Another 50% draw-down from where we are at the time of writing would take the price of bitcoin to just over $8,000.

So what does this mean? Well, I can tell you, for sure, 100%, that I can not tell the future. I will be, however, watching my new chart very closely. But I would say it is likely we’ll be seeing something exciting, and it will probably be in January. Unfortunately, it looks like CC moves down just as fast as price, and as fast as volatility moves up during sudden, capitulation like events. However, Bitcoin always has a way of surprising everyone. If CC moves down to 0, and then puts in another local high in the next week, I would be a little spooked. If it keeps moving up to 0.50, it may be an interesting and unexpected move to the upside. Regardless of what happens, I would encourage everyone to try to understand volatility a little better than you already do, and use the correlation coefficient indicator. It is a simple, yet versatile tool that can be used to quantify data in a way that makes a trading strategy precise. Here’s to 2023, I wish you well, and thanks for reading.



Disclaimer

The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations supplied or endorsed by TradingView. Read more in the Terms of Use.