The ability to quantify performance is critical for any market, but even more so for crypto.
Still suffering from the stigma surrounding a lack of tangible assets as a base, cryptocurrency relies on information and data of any sort to maintain credibility and establish market confidence.
Even though it is becoming easier to study value through usage and relevancy, it is nowhere near what mainline investors are accustomed to. On a very basic level, actual products are still difficult to analyze. Anyone can look at NASDAQ leaders such as Apple, Amazon, Google, or Microsoft, and — especially with these tech-based stocks — it is obvious how they are doing. It is possible to find information on not only their performance but also consumer attitudes toward them, both currently and historically.
Cryptocurrency and distributed ledger technology (DLT), with a history of just under ten years, do not have historical data to compare and evaluate against current market trends. In fact, the technology, including products and services, is so new, even finding accurate representative current state data is a dubious task.
As more experts seek innovative ways to analyze market trends, capture and optimize data usage, and distribute appropriate, relevant information to consumers, investors will be operating within a higher level of trust and confidence.
At this point, anyone who is invested in cryptocurrency believes in the technology as a solution, whether as a better financial tool, or a strong tech base for communication and commerce. It is exciting to see analysts trying to provide investors with the data they need to continue supporting the crypto market.
In a fresh analysis of the cryptocurrency performance over the past twelve months, blockchainenthusiast Chris Burniske not only assumes the existence of cryptocurrency fundamentals but suggests these fundamentals should be considered alongside network value when assessing market performance.
His theory that cryptocurrencies are inherently oversold is based on an analysis of the two cryptocurrency giants: Bitcoin and Ethereum. Two vastly different assets, Burniske did not use the same indicators when comparing these coins on the demand-side. While he did review daily transactions for both, he used estimated daily transaction value for Bitcoin and total daily gas for Ethereum.
Bitcoin is still primarily a storage of value platform, daily transactions are a solid indicator of native functionality within the network. Because Ethereum was designed with smart contract/DApp heavy activity in mind, and most users consider this its primary function, gas is a reasonable metric. It depicts the native demand-metric for each network as opposed to an arbitrary number, prioritizing usage.
The analysis shows a clear divergence between network value and both daily transactions and native functionality for Bitcoin and Ethereum alike.
Hash Rate as a Viable Metric
Even on the supply side, there is a strong divergence between price and hash rate. While the hash rate is typically a lagging indicator behind price, there is nevertheless a higher hash rate for both Bitcoin and Ethereum than even the Dec 2017 peak. Hash rates are dropping for both, but still outperforming network value.
Why is this happening? Do plummeting prices over the past year actually imply a terrible market state, or has the continuing negative news cycle surrounding this situation inaccurately and unfairly skewed network value across the entire market?
Historically, in more traditional financial spaces with established fundamentals, trusted metrics, and long-standing regulatory standards, numbers in the form of market value really are an accurate indicator of status. True to form, cryptocurrency may not fit into that box. Burniske’s analysis may be true.
To see industry leaders such as this exploring the possibilities for authentic financial analysis in the cryptocurrency space is encouraging. Investors are hungry for a higher level of verifiable information and a greater degree of trust, and a better and more robust analysis of the market space than a simple evaluation of price data.
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