Better Technical Analysis with Blockchain Indicators: Bollinger Bands

Technical analysis (TA) represents one of the most popular mechanisms used by traders in capital markets and crypto is not the exception. One great thing about TA is that you can find as many fans as detractors in any asset class. In the case of a nascent and immature capital market such as crypto-assets, TA has established itself as one of the few viable mechanisms for extracting short term signals from the behavior of crypto assets. I’ve never been a fan of TA but I also don’t neglect its value and passionate community. Lately, we have been spending some time at IntoTheBlock, thinking about how some popular TA indicators can be improved with blockchain-native signals.

The idea of combining TA and blockchain signals is conceptually trivial. Crypto assets have the unique characteristic of recording a relevant portion of the investor activity in public ledger. Those ledgers represent a gold mine to understand insights about the behavior of groups of investors and, let’s face it, TA is mostly based on identifying short-term behavioral patterns reflected in asset prices. From that perspective, blockchain indicators can serve as a natural complement to enrich the results of basic TA methods.

The combination of TA and blockchain indicators can take different forms. In some cases, blockchain signals can act as an information enrichment vector of a TA sign. In other scenarios, TA methods can reinforce patterns signaled by blockchain indicators. I am planning to expand in this thesis in tomorrow’s webinar and in future blog posts. For today, let’s try to illustrate this concept using one of the most popular TA indicators in the space.

Bollinger Bands

Bollinger Bands are a popular TA indicator to measure mean reversion patterns in price time series. Developed in 1980 by financial analyst John Bollinger, the indicator defines a set of lines plotted two standard deviations (positively and negatively) away from a simple moving average (SMA). Conceptually, the bands act as a measure of how far price can travel from a central tendency pivot, indicated by the SMA, before triggering a reversionary impulse move back to the mean. The bands expand and contract in reaction to price and volatility fluctuations.

From the actionability standpoint, Bollinger Bands are believed to act as signs of buying and selling deviations in the market. From that perspective, traders interpret prices moving to the upper band as a sign that the market is overbought. Similarly, the closer the prices move to the lower band, the more oversold the market is.

The following chart illustrates the use of Bollinger Bands with Bitcoin.

Complementing Bollinger Bands with Blockchain Indicators

The most popular use of Bollinger Bands is to detect mean reversion patterns by analyzing potential overbought and oversold trends. The analysis of blockchain activity can provide very unique perspectives of these patterns that expand beyond simple price trends. There are many blockchain analysis methods that can be used to detect overbought and oversold activity, I would like to illustrate two included in the current version of the IntoTheBlock platform.

The In-Out Money Around the Current Price provides an analysis of profitability of active investors that are in close proximity to the current price (+-15% distance). The bubbles in green represent clusters of investors realizing gains while the read bubbles are clusters of investors whose positions are at a loss compared to the current price. Drastic variations in the difference between those two groups over time can represent indicators of overbought and oversold activity.

Another signals that is an interesting indicator of overbought or oversold positions can be extrapolated by analyzing the traffic in and out of exchanges. IntoTheBlock’s netflow analysis monitors the funds in the different type of addresses belonging to an exchange such as deposit addresses, withdrawal addresses, cold wallets and hot wallets. Large inflows into exchanges typically precede liquidations and large outflows can be associated with holding patterns. From that perspective, variations in exchange flows can be seen as signals of overbought or oversold positions.

How to combine these blockchain signals with the Bollinger Bands analysis. A very simple interpretation might be that the blockchain signals provide an stationary of oversold and overbought activity while the Bollinger Bands can reinforce that analysis by looking at short term conditions.

A more ambitious method might be to create a new version of the Bollinger Bands factoring in some of the key blockchain profitability metrics. More about that in a future post.

Some of those findings will be discussed at a webinar we are hosting tomorrow at 12pm US EST. Shameless plug 😊