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How do Cryptocurrency Price Rallies Look on the Blockchain?

Price rallies are the highlight of any asset class and cryptocurrencies are not the exception. Bitcoin has made more news based on its unpredictable price rallies than for any other of its recent developments. During and after a price rally we would hear all sorts of speculative arguments about its causes and expected behaviors but sometimes we ignore the most obvious data points. Like many other events in a cryptocurrency network, price rallies leave fingerprints in the underlying blockchains. Today, I would like to highlight some non-trivial examples of indicators and analyses that can help us understand price rallies based on its on-chain behaviors.

Analyzing the behavior of price rallies on-chain can be relevant for several reasons. For starters, on-chain signals can demystify some of the subjective, speculative analyses that are formulated after a price rally. More importantly, understanding patterns within on-chain indicators can help identify relevant conditions that can serve as predictors of a new price rally. With some exceptions, most price rallies are unexpected events and, therefore, trigger the best of our imagination in order to come up with plausible explanations about its causes.
The Three Stages of a Price Rally
Price rallies are important events to frame the investor behavior and psychology of any crypto-asset. While the structured processes of public markets and the control mechanisms of equities exchanges provide clear mechanisms to explain and even-constraint the effects of a price rally, those dynamics are completely different in crypto. Borrowing some ideas from behavioral psychology, we can describe price rallies in crypto assets in three different stages:
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  • Surprise: Most price rallies are triggered unexpectedly catching most investors by surprise.

  • Trend Following: Contrary to most principles in technical trading that state to never follow a price rally, many retail investors do precisely that. If the price rally is triggered by a major cryptocurrency like Bitcoin, a normal pattern is to look for what AltCoins are impacted by it.

  • Subjective Explanations: Cryptocurrency rallies are a perfect case study of the narrative fallacy pattern of behavioral finance. In the absence of rigorous information, pseudo-experts try to come up with the most unbelievable explanations about what fueled the price rally and use that as a predictor for future price movements.
Differently from other asset classes, crypto-assets record many events of their lifecycle in publicly available blockchains. When comes to price rallies, studying on-chain data can be one of the most effective ways to understand the effects and behavior of price rallies.
On-Chain Indicators: Leading, Lagging or Coincident
In financial markets, there are three fundamental types of indicators that are used to understand a given asset class:
  • Leading Indicators: Indicators that are considered to point toward future events

  • Lagging Indicators: Indicators that are seen as confirming a pattern that is in progress

  • Coincident Indicators: Indicators that occur in real-time and clarify the state of the economy.
Understanding the on-chain behavior of crypto-assets cannot only help to clearly understand how price rallies are reflected on blockchains but also identify clear conditions that will signal a new price rally.
What Blockchains Tell Us About Price Rallies?
Blockchains provide a universe of data that helps us understand the mechanics of price rallies. Using data science as an enabler, we can provide some unique indicators that are relevant to large price fluctuations in crypto-assets.
Token Holders Profits: In/Out Money Distribution Analysis
One of the clear signs of a price rally is the number of token holders that materialize gains. The In-Out Money Analysis reveals the distribution of token holders making money versus those loosing money. After a price rally, we should see the number and size of the clusters in green increase. If we compare the results of the indicator for Bitcoin (that has seen some relevant price rallies recently) and Ethereum, we can see some drastic contrasts.
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The thing about In-Out of the Money indicators is that they can be both lagging but also leading as the sign a position for the next price rally.
The Number of New Investors Increases: Traders Indicator Analysis
New investors is often one of the omnipresent elements of any price rally. Measuring the number of new and active addresses on a given crypto-network can help to understand the impact of new investors in a previous price rally as well as the conditions for new price movements. The Traders Analysis reveals an increasing number of new addresses created by recent price rallies in Litecoin.
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Whales Trade More Actively: Concentration Indicator Analysis
Large investors(whales) are typically associated with price rallies. In some tokens, whales act mostly as passive investors while, in others, they trade actively causing fluctuations in the price. The Whales Activity Analysis shows the trading activity of large investors. That analysis in Bitcoin Cash looks like the following:
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The Number of Active Addresses Increases: Address Activity Indicator Analysis
One of the clear signs of a price rally is the increase in number of active addresses. In any price rally, we should see a growing number of active addresses as well as new addresses coming into the network. The Address analysis shows the number of active, new and zero-balance address and you can see how it look very healthy for Ethereum.
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The Number of Large Transactions Increases: Large Transaction Activity Indicator
Large on-chain transactions are typically signs of large transfers that can be used to take a sizable position in an asset or also the aggregation of a large number of smaller transactions. During price rallies both indicators tend to increase distinctively.
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The analysis of on-chain data is not very obvious and is difficult to achieve at scale. However, when comes to price rallies, on-chain datasets provide some of the richest and more accurate data points to help us understand the behavior and predict conditions for future rallies.