The Correlation Controversy
Part III: Crypto Correlations
This article series aims to answer the question of whether crypto moves independently from traditional assets in such a way that it can be considered its own asset class. If that is the case, investors can use crypto to diversify their multi-asset portfolios and limit their exposure to extreme market movements, as discussed in Part I. Afterwards, in Part II, we encountered multiple difficulties than come with measuring correlation. Being aware of these complications, we may better understand to what extent crypto and other asset classes are intertwined. We wrap up our search for this answer in the third and final part of this series.
Data
Let’s start off by introducing the data that we will be using for our analysis. We use the Bitwise 10 Crypto Index Fund as a proxy for the crypto market. The fund is comprised of the 10 largest cryptocurrencies, weighted by market capitalization and rebalanced monthly, making it a valid choice. Besides crypto, we will be investigating four other asset classes and their corresponding proxies:
- Equities; The MSCI World Index captures the performance of global large and mid-cap equities across 23 developed market countries.
- Fixed Income; The SPDR Bloomberg Global Aggregate Bond Index ETF consists of a broad range of government and corporate bonds and securities.
- Commodities; The iShares S&P GSCI Commodity-Indexed Trust tracks the performance of various commodities, such as energy, industrial and precious metals markets.
- Real Estate; The Vanguard Real Estate ETF measures performance of real estate-related investments.
The scaled time series, running from 4 January 2021 until 29 July 2022, are displayed below. Right off the bat, we observe a major difference in volatility. Crypto reaches higher highs and lower lows than any of the four other asset classes. As expected, the bond market shows the smallest movements, making it especially suitable for decreasing volatility in a portfolio. One striking observation is that equities and real estate appear to move in tandem over the full sample period. And particularly at the end of the sample period, crypto seems to follow a similar pattern.
Correlation analysis
From the previous article, we know that judging correlation by eye can lead to false conclusions, so we must dive deeper into the data. We ignore the raw values (for reasons given in the previous article) and use day-to-day changes to obtain sample correlation coefficients. These are shown in the correlation matrix below. We find that there is a high degree of independency across most asset classes. Apart from two exceptions, all correlations are below 0.2, which can be considered very low. This confirms that we may be dealing with separate asset classes across our sample set. One might argue that the significant positive correlation of 0.74 between real estate and equities refutes the statement that real estate should be considered its own asset class. But the same may not be said about crypto, showing only a 0.22 correlation coefficient with equities.
We know that day-to-day changes may not capture the full picture. We therefore also consider week-on-week changes. The results are more or less the same, except that fixed income correlations with equities and real estate have ramped up considerably. This suggests that bonds may not be the safe haven they were in past decades. Again, we observe that the crypto correlations are very low.
The correlation matrices make the critical assumption that correlation is constant across our sample period. We have seen in Part II that relaxing this restriction may provide us with more insights. From now on, we will only focus on correlations between crypto and the four other series. The graph below displays the 90-day rolling window correlations of crypto and each of the four other asset classes. These correlations are highly time-varying, showing negative values during mid-2021. Afterwards, crypto becomes increasingly correlated with both equities and real estate, which we know are heavily interconnected. It is important to note that at the end of our sample period, correlation with equities, fixed income and real estate is well above 80 and even exceeds 90 in the last couple of days. This suggests that crypto has considerably lost its diversifying power over the course of last year. Of course, there is no way of knowing whether this will persist, but it is good to be aware that exceptionally high correlation is not a rarity.
Interpreting the results
Can we think of an explanation as to why the correlation between crypto and equities reached such high levels in the past few months? After looking at the data, it seems to be that the downturn in equity prices may be one of the possible causes for this to happen. The graph below shows where this suspicion comes from. It is very clear that once equity prices started to fall in January 2022, the correlation increased from 0 to over 0.9. A similar feature can be found during the short downturn in September and October 2021.
To find out whether the relationship between crypto and equities actually becomes stronger in an economic decline, let’s consider the scatter plot below. It distinguishes between dates on which equity returns are positive (blue) and dates on which they are negative (red). A linear regression yields R-squared values, which give an indication of how strong the relationship between crypto and equity returns are. Note that the relationship during periods of negative equity returns is significantly higher than during periods of positive equity returns. Nevertheless, since the R-squared values are low, we can conclude that this distinction only explains a small part of the positive correlation between the two asset classes.
Another approach of explaining the correlation would be to consider extreme market conditions. We can, for instance, define such conditions as dates on which the equity returns are highest or lowest. The scatter plot below shows what that looks like, with the 10% most extreme equity return dates in red. Looking at the R-squared of these red observations, we immediately spot that the relationship is better explained than in the previous case. Crypto returns are generally negative during exceptionally low equity returns and positive during exceptionally high equity returns. The R-squared of 0.33 more or less confirms this observation. We thus draw the conclusion that the high correlation between crypto and equities at the end of our sample period may, to a certain extent, be explained by extreme market conditions and volatile price movements.
Final remarks
We now know what is going on between crypto and equities. Our analysis on the data since January 2021 tells us that the correlation between the two has been low or even sharply negative. But in the past few months, it settled above 90% in what looks to be a steady and decisive manner. Does this then revoke crypto’s right to be considered a diversifying asset? Not necessarily, because two other asset classes, fixed income and real estate, are also heavily correlated with equities during this time. Furthermore, we don’t know whether this correlation will continue indefinitely. We have reasons to believe that this strong interconnection between crypto and equities is caused by the economic downturn that held the markets in its grip in the first two quarters of 2022. It thus appears that the state of the global economy affects the behaviour of crypto assets relative to other assets.
