Recent crypto market gyrations after the Bankruptcy of the FTX exchange require a fresh look at the evolving relationships between cryptocurrencies and traditional asset classes. Despite current market dynamics, interest in digital assets remains high: 16% of Americans have invested, traded, or used cryptocurrencies, while around 87% say they know at least a little about them. according to data from the Pew Research Center for July. While Bitcoin was once touted as a hedge against equity markets and a potentially uncorrelated addition to investment portfolios, its increasing correlation with the S&P 500 indicates otherwise.
The role of correlation in portfolio diversification is well known: lower correlation reduces overall portfolio volatility and risk. However, from 2019 to 2022, the correlation of the S&P Cryptocurrency Broad Digital Market Index (SPCBDM) with the S&P 500 increased from 0.54 to 0.801, indicating that cryptocurrencies have increasingly moved along with stocks.
To better understand the relationship of cryptocurrencies to other asset classes and the larger market, we investigated how various digital currencies correlate with active and passive funds, SPDR sector ETFs, and commodities. If uncorrelated or negatively correlated, cryptocurrencies could potentially contribute to reducing overall portfolio risk through diversification. Otherwise, a cryptographic mapping can be counterproductive.
To perform our analysis, we collected daily closing price data for five cryptocurrencies: bitcoin (BTC), Ether (ETH), Litecoin (LTC), XRP, and Cardano (ADA), from October 2019 to October 2022. We collected the same subset data for a selection of mutual funds, including large-cap growth, large-cap value, and mid-cap growth, among other varieties, as well as for various active and passive equity and bond funds, with each category consisting of out of a total of 30 funds. We also selected daily closing price data for the following eight SPDR sector ETFs over the same period: XLB (US Materials), XLE (US Energy), XLF (US Financials) , XLI (US Industry), XLK (US Technology), XLP (US Consumer Staples), XLU (US Utilities), and XLV (US Healthcare). USA).
Finally, we collect the same data for gold, silver, crude oil, natural gas, and the Bloomberg Commodity Index (BCOM). We then calculate daily returns based on these prices using Python. From there, we created correlation matrices and heat maps to assess the relationships between cryptocurrencies and various funds, sectors, and commodities.
Crypto and Sector ETFs: Correlation Heatmap
cryptographic coefficients
Of the five cryptocurrencies, Litecoin had the highest correlation with bitcoin and Ether at 0.81, while bitcoin and Ether had a significant positive relationship, with a correlation of 0.79. Comparatively, Cardano and XRP had lower correlations, from 0.46 to 0.58, with their crypto peers.
All five cryptocurrencies have negligible or weak positive correlations with industry ETFs, based on our results. These correlations range from 0.1 to a maximum of 0.39, with XRP exhibiting the lowest. Among ETFs, XLK (US Technology) and XLB (US Materials) demonstrated the highest, albeit only weakly positive, correlation with cryptocurrencies. Correlations within sector ETFs were much higher, peaking at 0.92 for XLI (US Industrials) and XLF (US Financials), and XLI and XLB.
So what about the correlation between cryptocurrencies and the various mutual funds? The following heat map illustrates the low positive correlation between them. The correlations range from a minimum of 0.19 to a maximum of 0.41. These suggest a relatively weak but slightly stronger relationship than that between digital currencies and sector ETFs. As with industry ETFs, of all cryptocurrencies, XRP shows the lowest mutual fund correlation.
Crypto and Mutual Funds: Correlation Heatmap
Growth funds exhibit a stronger correlation to cryptocurrencies than value funds. The correlation coefficient between small-cap growth funds and bitcoin, for example, is 0.41, compared to 0.35 for small-cap value funds and bitcoin. This relationship is similar for both mid-cap and large-cap funds and implies that crypto assets are weakly sensitive to the interest rate dynamics that have driven much of the recent decline in growth stocks. However, the correlation with mutual funds was much higher, as between mid-cap value and small-cap value funds it exceeded 0.97.
Cryptocurrencies show even weaker positive correlations with bonds than with stocks, according to the following heat map. demonstrating sharpe arithmeticthe correlation with active and passive equity funds is by far the highest at 0.98.
Active and Passive Crypto Equities and Bonds: Correlation Heatmap
Regarding the goodsone, the following heatmap demonstrates that all cryptocurrencies have negligible positive or negative correlations with each other. Only natural gas shows low negative relationships with cryptocurrencies, specifically BTC, LTC, ADA, and XRP. Since the values are close to zero, these assets have little to no co-movement. Silver has the highest correlation, peaking at 0.26 for silver and bitcoin. Bitcoin, the so-called “digital gold”, shows only a weak correlation with the precious metal.
Crypto and Commodities: Correlation Heatmap
So what can we get out of all this? The low positive correlation of cryptocurrencies with mutual funds and ETFs may indicate an increase in cross-market trading and point to the growing popularity of cryptocurrencies. Additionally, in an environment of rising interest rates and amid the declining effectiveness of the traditional 60/40 stock/bond portfolio, the weak correlation of cryptocurrencies to traditional assets may offer potential diversification benefits for investors. long-term investors who can withstand additional volatility in the short term. However, not all cryptocurrencies show the same lack of correlation with traditional assets, so investors need to discern which ones to target.
1. People usually invest in commodities through forward contracts or futures contracts. Since these contracts are derivatives, they derive their values from their underlying assets. A gold futures contract, for example, derives its value from spot gold prices. According to the transportation cost model, the futures price is influenced by the spot price of the underlying asset. The futures price is determined as the sum of the spot price of the asset plus the cost of transportation/storage. The use of spot prices allows for a better representation of the underlying value of the asset.
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All messages are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer.
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