A common viewpoint amongst those who view Bitcoin primarily from a software perspective, and secondarily from a financial or economic perspective, is that the coin’s value is ultimately tied to utility: the more people use the coin, the more demand there is for the coin, and thus the more valuable it becomes. This viewpoint, influenced by the fact that the most valuable software companies — Facebook, Amazon, Google, etc. — tend to be the ones that are used the most, and so, the theory goes, the most valuable coins will be the ones used the most. This perspective stands in stark contrast to that Gresham’s Law, which suggests that forms of money that are used the most will have less value, as valuable forms of money are more likely to be hoarded and not used for transactions. Which perspective is right?
To answer this question, we observed the past eight months of data regarding Bitcoin’s daily on-chain transaction volume and its daily price, provided courtesy of Blockchair. We normalized both price and daily transaction count on a scale from 0 – 100, so that the numbers could be more easily compared visually; when then took the 7 day moving average of price and daily transactions to help smooth the data and understand trends more clearly. The resulting data is illustrated in the chart below.
At first glance, the chart shows the two are directionally correlated; in other words, transaction volume and market price of Bitcoin tend to move in the same direction. Statistically, they have a correlation of about .30, which suggests a clear relationship between the two variables. Moreover, we observed the correlation with Bitcoin’s price and the transaction volume of the preceding 1 – 7 days, and found day 4 had the strongest correlation — suggesting that previous transaction count may have some predictive power in terms of Bitcoin’s price. We stress that Bitcoin is a very young asset relative to other assets, and our 9 month sample here is far from conclusive — and so traders should consider exploring more before immediately incorporating this information into their trading strategy. Nonetheless, it does offer traders a potential starting point to formulating a trading strategy around Bitcoin rooted in real world fundamental data.
To that end, it should also be noted that the chart does show curious behavior around relative highs and lows in Bitcoin’s price. As the chart above illustrates, when Bitcoin makes relative highs but transaction volume does not, price tends to decline shortly thereafter. Divergence between Bitcoin price and daily transaction volume may thus be a potential indicator in a trading strategy; if Bitcoin makes a relative high that is not supported by higher on-chain transaction volume, the high may not last. This implementation of divergence is supported by a rich history of price/volume divergence in technical trading, in which many traders prefer to see breakouts in price confirmed by higher volume — and view weak volume as a sign the move in price is not sustainable. The concept of Bitcoin price and on-chain volume divergence is also compatible with the idea that on-chain volume can forecast price, as the correlation between price and volume 4 days prior illustrates.
In sum, at least over the past 9 months, it does seem as though the technologist’s perspective has some merit: Bitcoin’s volume has preceded its price. This may be a data point that traders wish to explore further to develop their own trading strategy and find their edge in the market. Specifically, traders interested in developing a strategy based on this potential insight may wish to start by observing a period larger than 9 months, observing the behavior of on-chain transactions when price reaches a clearly defined relative high/low, and explore what direction the market moves in and with what kind of volatility — in other words, what kind of risk/reward the market tends to accommodate during these times. As a final step after this work has been done, a backtest based upon clearly defined rules may provide a loose baseline for expected returns from the strategy (though returns typically fall short of backtested results when tested in real life). Last but certainly not least, the relationship between on-chain transactions and price may yield even greater insights when exploring crypto-to-crypto trades, in which relative highs/lows and on-chain volume is compared between two or more chains.