Trading Bitcoin During Major Announcement Cycles

The latest news out of Palo Alto left the world in shock and awe as Tesla, the first major Fortune 500 company invests part of its treasury in Bitcoin. The size of Tesla’s purchase of Bitcoin at rumoured to have taken place during January was to the tune of $1.5bn. But while normal folk flabbergasted, the crypto community had simply received confirmation of what they strongly believed would happen eventually. And by every indication on the blockchain, the writing had already been written on the wall long before Tesla’s reveal. One simply needed to look at the tightening of supply.

While the Financial Times has poured cold water on the prospect of many Tesla copycats, the reality is that the publication has long been sour on cryptocurrencies. As of date, the FT has been fairly snide and inaccurate in its extrapolation analysis on the cryptocurrency. The determination of the community of seeing the success of decentralized hard money is fact and one that even major banks such as Goldman Sachs agrees has been displacing gold even to some effect.

Major news from significant financial market players are bound to keep popping up. Traders need to look for the signs to know when. And blockchain analytics gives clues no other traditionally traded assets give.

In this quick-fire series, our new sign-ups can take advantage of Glassnode’s Advanced subscription for free. We give some thoughts as to some metrics that traders can follow in order to become more profitable and minimize any upcoming risks. Today we take a look at several market indicators that are available to traders that will help the asses short-term and macro strategies.

With many moving parts in the cryptocurrency world, and the blockchain, there are various metrics that traders can employ to make educated guesses as to market direction and trends.

Blockchain analytics were certainly hard to come by back in 2017 but today they’re a few clicks away and metric-ready for traders. And the most advantageous way to benefit from the data is looking at multiple factors that could potentially tell a story. Our latest research for example highlights the importance of looking at both Bitcoin and Tether to see the economic directions of supply and demand in live fashion.

In this quick overview, ZUBR highlights three very important metrics that can be important to identifying the macro trend of bitcoin and even help with short-term decision making. For example, with Bitcoin hitting its all time high this week, is it an overvalued asset? And if so, by how much? And would there be any demand in case of a big price drop?

Stock-to-Flow is a very simple, yet powerful metric that will help traders identify the current value cycle Bitcoin is in, and which direction it is on (see chart 1 below).

1: Bitcoin: Stock-to-Flow (Link)

As defined by Glassnode: The Stock to Flow (S/F) Deflection is the ratio between the current Bitcoin price and the S/F model. If deflection is ≥ 1 it means that Bitcoin is overvalued according to the S/F model, otherwise undervalued.

With production of new Bitcoins now down to 6.25 BTC per block, the ratios will tend to look undervalued. This becomes increasing important to keep in mind as block rewards continue to decrease.

The metric though is vital at this point in time and allows for the better assessment of fundamentals. As mentioned, this

Bitcoin: Puell Multiple (Link)

As defined by Glassnode: The Puell Multiple is calculated by dividing the daily issuance value of bitcoins (in USD) by the 365-day moving average of daily issuance value. This metric was created by David Puell. For a detailed description see this article by @cryptopoiesis.

Bitcoin: Tether Exchange Balance (Link)

The total amount of coins held on exchange addresses. Note that exchange metrics are based on our labeled data of exchange addresses that we constantly keep updating, as well as data science techniques and statistical information that changes over time. Therefore these metrics are mutable – the data is stable, but especially most recent data points are subject to slight fluctuations as time progresses.

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