Understanding Crypto-Assets Requires Looking Beyond Price Charts

What moves the price of cryptocurrencies? That question puzzles crypto investors and traders on a regular basis. In an such as crypto, there is no lack of absurd theories without any financial or technological rigor that constantly try to explain the price movement in different cryptocurrencies and tokens.
Despite the data-rich nature of crypto-assets that produces immutable records of every transaction in public ledgers, most financial analyses today are constrained to traditional price and volume indicators. Understanding crypto-assets requires a more that expands beyond price charts and considers some of the unique characteristics of this new asset class. After all, if crypto is a new asset class with new fundamentals, shouldn’t we be considering those unique elements in its analysis?

A Different Asset Class

The first step to enable more complete analyses of cryptocurrencies and is to recognize them as a new asset class with a new set of fundamentals. Every asset class in the history of financial markets has introduced new factors relevant to its analysis. Commodities rely on supply-demand dynamics, and some of their behaviors are highly seasonal – currencies trade 24×7 while options and futures are time-sensitive. Ignoring those key elements of the DNA of an asset class only results in overly simplistic models that fail to adapt to different market conditions.
In the case of crypto-assets, there are some unique characteristics that we haven’t seen in previous asset classes and that highly influence the behavior of this new asset class. Here are some of the most prominent ones:

The Ledger Factor: The behavior of individual crypto-asset investors is recorded in public, decentralized ledgers, which can be analyzed by anyone. This means that crypto-assets enable analyses at a more granular level that other asset classes.

The Network Factor: Crypto-assets operate in networks that enable the transfer of ownership and transactionality across its different parties. This means that the composition of the underlying network is incredibly relevant in the behavior of a crypto-asset.

The DApp Factor: Some crypto-assets enable (DApps). This means that the behavior of a crypto-asset can be influenced by the DApps that are using it.

The Fork Factor: Crypto-networks can be forked. This means that a group can decide to clone a specific crypto-network causing a big impact for its investors.

These unique factors are highly relevant when it comes to analyzing the behavior of crypto-assets. While many analysis techniques from other asset classes are applicable in crypto, most of them should be tailored to this new asset class and its unique characteristics.
Why Price and Volume are not Enough?
If crypto-assets are so different, why do we mostly rely on price and to analyze their behaviors? One explanation is that the crypto space is fairly new and that the analysis methodologies are just emerging. Another school of thought will argue that price and volume are the only relevant factors to understand any asset class, including crypto.
Techniques based on price and volume have proven to be effective in other asset classes, and some of them can be adapted to the crypto space. However, the context is drastically different. In most asset classes, price and volume are the only indicators of activity in a given asset. In the context of crypto assets, provide a universe of data points that describe the activity of individual or groups of investors. Let’s take the example of two scenarios in which the price of a crypto-asset increases five percent recording 100,000 transactions.
So technically, price variation and volume is the same in both scenarios. However, in one case the transactions come from existing addresses in the network while in the other the number of addresses increases by 30 percent. The second scenario indicates that new investors are coming into the network, who are likely to increase the buying activity in the near future.
The previous example illustrates how blockchain datasets provide additional data signals that are relevant to analyze the behavior of crypto-assets. Ignoring those data signals effectively ignores the elements that make crypto-assets different from any other asset classes.
Crypto-Assets Require a New Form of Analysis
Understanding and predicting the behavior of crypto-assets requires indicators that are tailored to the unique characteristics of this new asset class. From that perspective, crypto-assets require a new financial analysis methodology based on crypto-specific factors such as blockchain datasets as a first-class citizen. While exchange data fees capture the relevant trading lifecycle of a crypto-asset, blockchain datasets capture individual investor trends.
Blockchain data is certainly a unique differentiator of crypto as an asset class. The fine granularity and richness of blockchain datasets make crypto the richest financial asset class in history and one that is rapidly growing. Furthermore, the combination of blockchain, pricing, and off-chain datasets, provides a complete perspective of a crypto-asset across dimensions that are different from other asset classes. For instance, ownership indicators can provide signals about counterparty analysis, while network indicators can surface intelligence about the composition of the crypto-network supporting the asset.
Understanding the financial will be one of the existential challenges of the next decade of the cryptocurrency market. While the specific factors and methodologies for analyzing crypto-assets are still in a very nascent stage, one thing is for certain: crypto is a new asset class, with different fundamentals that require a new form of financial analysis.
Jesus Rodriguez is the Co-Founder and CTO of IntoTheBlock, a technology expert, executive investor, and startup advisor.