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Home Crypto News & Analysis On-Chain Data & Metrics

On-Chain Analytics: An Investment Approach to Cryptocurrencies

by Dr. Jane Chen
May 25, 2024
in On-Chain Data & Metrics
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On-Chain Analytics: An Investment Approach to Cryptocurrencies
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One of the major issues hindering the mass adoption of cryptocurrencies is the lack of fundamental analysis that exists in traditional markets such as the stock market. It is difficult to do any kind of analysis on cryptocurrencies without having significant knowledge of blockchain and technical analysis. The majority of retail investors in the cryptocurrency market have little to no knowledge of the value of what they are investing in. They only invest in cryptocurrencies based on recommendations from individuals like me.

Three questions I am often asked are:

“Which coin can I buy today?” “Is it the right time to enter the market?” “How can I analyze cryptocurrencies?”

So far, the most dominant form of analysis in cryptocurrency trading/investing is the study of price action called technical analysis. However, by using the wealth of information provided by public blockchains such as Bitcoin and Ethereum, we gain a unique perspective never seen before in traditional assets and one that can complement other analyses.

READ: DeFi leads charge as total cryptocurrency market cap hits $400 billion

Although there is no straight path to doing cryptocurrency analysis, I would say that because blockchain functions as a public digital ledger of transactions that are duplicated and distributed across the entire network of computer systems on the blockchain, it has a created new form of analysis that never existed before, even in traditional markets. These new forms of analysis are called “On-Chain Analysis”.

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On-chain analytics (or blockchain analytics) is an emerging field that examines the fundamental factors of cryptocurrencies to improve investment and trading decisions.

How is this possible, you may ask; well, cryptocurrencies are the first asset class that can record and extract investor activity from massive datasets through each cryptocurrency asset’s public ledger, capturing every chain action that has taken place.

READ: Daymak to produce electric car that mines cryptocurrencies

As blockchains are prized for a treasure trove of open, uncorruptible financial data, we can establish metrics of economic activity in these networks. This allows for the collection and study of this data that we can use to measure sentiment and investor behavior.

On-chain analysis is a fundamentals-driven approach rather than one based on hype, sentiment, technical analysis or word of mouth from others. This type of analysis can focus exclusively on one crypto asset by looking at historical trends or it can be used to compare different crypto assets to identify undervalued/overvalued coins.

Brief history

On-chain analysis can trace its history back to 2011 when “coin days destroyed” was created as a valuation metric for Bitcoin and was the first indicator to use the age of Bitcoin addresses.

In the summer of 2017, CoinMetrics’ Chris Burniske and Jack Tatar created the Network Value to Transaction (NVT) ratio, which was used to determine the utility value of a cryptocurrency, specifically how much the market was willing to pay for the transactional utility of the blockchain.

READ: Is It The Right Time To Invest In Bitcoin?

Another on-chain metric soon emerged from the dissatisfaction with simplistic metrics from technical analysis (such as price/volume) and other concepts borrowed from traditional markets, such as market capitalization. Due to the weakness with market capitalization and the pitfalls of applying traditional metrics directly to cryptocurrencies, a new set of tools has been developed that can help traders determine the value of cryptocurrencies more accurately and precisely. This led to the creation of on-chain statistics, such as realized capitalization, HODL waves and percentage of supply in profit/loss.

Top on-chain stats to consider before investing

Two important on-chain statistics to consider before trading/investing are:

The number of active addresses The number of transactions

These on-chain statistics are indicators of the demand and usage of a blockchain network. For example, when the number of active addresses and transactions increases sharply, investors can predict that a price increase is expected.

Apart from these two, we have several other metrics which are:

Realized capitalization

It helps to know the participation of long term investors. This helps indicate an overheated market and one that relies heavily on short-term speculation. When used in conjunction with the market cap metric, it helps traders find optimal zones to buy and sell.

Time of time an address has not moved Bitcoins

It uses a UTXO set by aggregating these sets to see how many investors hold Bitcoin. An increase in the number of investors holding will mean that the circulating supply is lower, which should eventually increase the price if demand is constant. It also indicates confidence in the asset’s future performance.

Where to find on-chain analysis

Many websites offer on-chain analytics, Nairametrics recommends Glassnode. You can access basic on-chain statistics for free, but some indicators have a time lag under the free membership. You have to pay for advanced indicators and high frequency time series data.

Other sites include IntoTheBlock, Look Into Bitcoin, CoinMetrics, Santiment/Sanbase and CQ.Live.

Restrictions

Despite the promise that on-chain analytics brings, it is still in its development stage, and given the limited back-history of data, the use of the metrics may evolve over time, or new trends may be highlighted leading to the creation of new metrics as the industry matures.

The main limitation of on-chain analysis is the fact that not all blockchains are created equal. For example, Bitcoin is focused on being a digital gold, while Ethereum’s blockchain is used for a wider range of activities, including supporting applications called smart contracts. Due to the disparity in blockchains, different interpretations can be derived from a particular metric when performing analysis on both cryptocurrencies, making the process of analysis a bit confusing.

Another limitation is that when comparing Bitcoin to other newer altcoins, Bitcoin has more than a decade of data to support historical analysis, while the newer altcoins have less data. This means that some metrics may become less reliable or change their interpretation because newer altcoins have very limited data.

Finally, on-chain analysis may not be an advisable tool for short-term traders because these metrics usually produce actionable signals for long-term market cycles.

Disclaimer for Uncirculars, with a Touch of Personality:

While we love diving into the exciting world of crypto here at Uncirculars, remember that this post, and all our content, is purely for your information and exploration. Think of it as your crypto compass, pointing you in the right direction to do your own research and make informed decisions.

No legal, tax, investment, or financial advice should be inferred from these pixels. We’re not fortune tellers or stockbrokers, just passionate crypto enthusiasts sharing our knowledge.

And just like that rollercoaster ride in your favorite DeFi protocol, past performance isn’t a guarantee of future thrills. The value of crypto assets can be as unpredictable as a moon landing, so buckle up and do your due diligence before taking the plunge.

Ultimately, any crypto adventure you embark on is yours alone. We’re just happy to be your crypto companion, cheering you on from the sidelines (and maybe sharing some snacks along the way). So research, explore, and remember, with a little knowledge and a lot of curiosity, you can navigate the crypto cosmos like a pro!

UnCirculars – Cutting through the noise, delivering unbiased crypto news

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Dr. Jane Chen

Dr. Jane Chen

Armed with a PhD in cryptography and years of research, Dr. Chen dives deep into the technical intricacies of blockchain. Her insightful analyses of white papers and on-chain data provide a unique understanding of the technology's potential and limitations.

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