It’s been a tough year for risky assets across the board, and it’s fair to blame the macroeconomic environment. A combination of factors drove up inflation in developed countries and forced central banks to respond.
As a result, many events, including inflation, wages, interest rate announcements, and speeches by monetary authorities (especially in the United States), have had a significant impact on the prices of risky assets around the world. As the bad news spread, the turmoil spread to different asset classes and regions. In mid-September, all major stock indices in developed countries posted negative double-digit returns (so far, currency adjusted).
In these turbulent waters, crypto assets have been hit hard. The Nasdaq Crypto Index (NCI), which reflects the performance of major crypto assets, is down 52.3% through September 12 (YTD). During this crisis, the cryptocurrency has also shown an unprecedented high correlation with traditionally risky assets, especially technology stocks, which constitute one of the sectors worst affected. Under these circumstances, it is worth asking if the encrypted winter is caused by a macro scenario. Let’s see what the data can tell us.
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We fitted a simple regression model to understand how macroeconomic shocks affect NCI returns. We used the Nasdaq 100 Index (NDX), which is closely related to cryptocurrencies, as a proxy for changes in the macroeconomic environment. Our data-driven approach also identified two extreme values that require special processing, but we’ll look at that later. Using daily returns from March 1 to September 12, the estimate shows that for a 1% change in the NDX, a 1.27% change in the NCI should be expected. Given that the NDX was down 21.9% by September 12th, we can conclude that the negative return in the NCI of 27.0% was directly caused by the macroeconomic condition. That’s definitely a big amount, but the 34.6% drop still needs an explanation. Can we declare the macro “not guilty” of this residual error? The model gives us some clues.
Outliers were determined based on data-based criteria only. But if you look closely, you can see that there is a meaningful narrative about these dates. The first date is May 9, coinciding with the collapse of Terra (the algorithm stable ecosystem), and the second date is June 13, the same day Celsius, the leading centralized lending platform at the time, stopped withdrawing funds. According to the model, these two days represent a decrease of 22.4%, while the last two represent two-thirds of the decrease.
Terra and Celsius are two examples of classic financial disasters: a currency crisis and a supervised agent going bankrupt, respectively. These situations usually occur when risk aversion grows (exactly what happens during large and large-scale crises). A famous quote attributed to Warren Buffett describes this idea well: “You never know who’s been swimming naked until the tide goes out.” While it would be unfair to place all the blame for these events on the macro environment, it is hard to believe that they did not play a major role in accelerating the death spirals and amplifying the spillover effect of the rest of the crypto ecosystem. It would be fair to classify these two instances as crypto-specific macro-enhanced events (what a fancy name).
After removing the effect of the two outliers, we get a negative return of 15.5%, which can be referred to as the net performance of the cryptocurrency. Well, if you call it winter, you probably live near the equator.
