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On-Chain Analytics: A Cryptocurrency Investment Strategy

One of the greatest roadblocks to widespread cryptocurrency adoption is the lack of fundamental analysis found in traditional markets such as the stock market. It’s difficult to do any type of cryptocurrency analysis without a solid understanding of the value of what they are investing in and technical analysis.

The majority of retail bitcoin investors have little to no understanding of the market’s value of what they’re investing their money into. They only invest in cryptocurrency after receiving suggestions from people like myself.

The following are three frequently asked questions:

“Can you tell me which coin I can buy today?”

“Do you think now is the right time to get into the market?”

“How can I analyze cryptocurrencies?” you might wonder.

Technical analysis, or the study of price action, has been the most popular type of analysis in cryptocurrency trading/investing thus far. However, by leveraging the quantity of data supplied by public blockchains like Bitcoin and Ethereum, we can gain a unique perspective that has never been seen before in traditional assets and that can be used to supplement other analyses.

Although there is no one-size-fits-all approach to cryptocurrency analysis, I believe that because blockchain functions as a public digital ledger of transactions that is duplicated and distributed across the entire network of computer systems on the blockchain, it has spawned a new type of analysis that has never existed before, even in traditional markets. These new types of analysis are known as “On-Chain Analyses.”

On-chain analysis (also known as blockchain analysis) is a new field that looks into the fundamentals of cryptocurrencies to help investors and traders make better decisions.

You might wonder how this is feasible; well, cryptocurrencies are the first asset class to be able to record and extract investor behavior from enormous data sets via each cryptocurrency asset’s public ledger, which records every on-chain transaction.

A quick look back

On-chain analysis may be traced back to 2011, when the term “coin days destroyed” was coined as a metric for valuing Bitcoin, and it was the first indicator to use the age of Bitcoin addresses.

The Network Value to Transaction (NVT) ratio was developed by CoinMetrics’ Chris Burniske and Jack Tatar in the summer of 2017, and it was used to measure a cryptocurrency’s utility value.

The most important on-chain indicators to consider before investing

Before trading/investing, there are two crucial on-chain parameters to consider:

The total number of addresses in use

The total amount of transactions

These on-chain metrics are indicators of a blockchain network’s demand and usage. When the number of active addresses and transactions, for example, increases dramatically, investors can anticipate a price increase.

Restrictions

Despite the promise of on-chain analysis, it is still in its early stages of development, and given the small amount of data available, the metrics’ use may alter over time, or new trends may emerge that lead to the introduction of new metrics as the sector evolves.

The fact that not all blockchains are created equal is a key constraint of on-chain analysis.

Bitcoin, for example, is primarily utilized as digital gold, but Ethereum’s blockchain is used for a broader range of purposes, including the backing of smart contracts. Because of the differences between blockchains, alternative interpretations of the same statistic might be determined when analyzing both cryptocurrencies, making the procedure a little complex.

Another disadvantage is that, when comparing Bitcoin to other newer altcoins, Bitcoin has more than a decade of data to support historical research, whereas the newer altcoins have fewer data. Because newer altcoins have relatively limited data, some measures may become less reliable or their interpretation may shift.

Finally, short-term traders should avoid using on-chain research because these indicators typically offer actionable recommendations for longer-term market cycles.

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