The recent fluctuations within the crypto market after the Bankruptcy of the FTX exchange require a fresh take a look at the evolving relationship between cryptocurrencies and traditional asset classes. Regardless of current market dynamics, interest in digital assets stays high: 16% of Americans have either invested in, traded, or used cryptocurrencies, while around 87% say they know no less than a bit of about them. in line with July data from the Pew Research Center. While Bitcoin was once touted as a hedge against stock markets and a potentially uncorrelated addition to investment portfolios, its increasing correlation with the S&P 500 suggests the alternative.
The role of correlation in portfolio diversification is well-known: lower correlation reduces the chance and overall volatility of the portfolio. However, from 2019 to 2022, the S&P Cryptocurrency Broad Digital Market Index (SPCBDM) correlation to the S&P 500 increased from 0.54 to 0.801, suggesting that cryptocurrencies have increasingly moved in parallel with stocks.
To higher understand crypto’s relationship to other asset classes and the larger market, we examined how various digital currencies correlate with energetic and passive funds, SPDR sector ETFs, and commodities. If they’re uncorrelated or negatively correlated, crypto could potentially help reduce overall portfolio risk through diversification. If not, crypto allocation could be counterproductive.
To conduct our evaluation, we collected day by day 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 identical data subgroups for a number of mutual funds, including Large-Cap Growth, Large-Cap Value, and Mid-Cap Growth, amongst others, in addition to various energetic and passive equity and bond funds, with each category consisting of total 30 funds. We also chosen day by day closing price data for the next eight SPDR sector ETFs over the identical period: XLB (US Materials), XLE (US Energy), XLF (US Financials), XLI (US Industrials), XLK (US -Technology), XLP (US Consumer Staples), XLU (US Utilities) and XLV (US Health Care).
Finally, we compiled the identical data for gold, silver, crude oil, natural gas and the Bloomberg Commodity Index (BCOM). Based on these prices, we then calculated day by day returns using Python. From there, we created correlation matrices and heatmaps to evaluate the relationships between the cryptocurrencies and the several funds, sectors and commodities.
Crypto and Sector ETFs: Correlation Heatmap
Cryptocoefficients
Of the five cryptocurrencies, Litecoin had the best correlation with each Bitcoin and Ether at 0.81, while Bitcoin and Ether had a major positive relationship with a correlation of 0.79. In comparison, Cardano and XRP had lower correlations (from 0.46 to 0.58) with their crypto counterparts.
According to our results, the five cryptocurrencies have negligible or weak positive correlations with the sector ETFs. These correlations range from 0.1 to a maximum of 0.39, with XRP having the bottom value. Among ETFs, XLK (US technology) and XLB (US materials) showed the best – albeit weakly positive – correlation with cryptocurrencies. Correlations inside sector ETFs were much higher, at 0.92 for XLI (US Industrials) and XLF (US Financials), in addition to XLI and XLB.
So what in regards to the correlation between crypto and the assorted mutual funds? The heatmap below illustrates the low positive correlation between them. The correlations range from a low of 0.19 to a high of 0.41. These suggest a comparatively weak but barely stronger relationship than between digital currencies and sector ETFs. As with industry ETFs, XRP has the bottom correlation to mutual funds of all cryptocurrencies.
Crypto and Mutual Funds: Correlation Heatmap
Growth funds have a stronger correlation to cryptocurrencies than value funds. For example, the correlation coefficient between small-cap growth funds and Bitcoin is 0.41, in comparison with 0.35 for small-cap value funds and Bitcoin. This relationship is comparable for each mid-cap and large-cap funds and implies that crypto assets are weakly sensitive to the rate of interest dynamics which have driven much of the recent decline in growth stocks. However, the correlation with mutual funds was much higher, with the correlation between mid-cap value and small-cap value funds at 0.97.
According to the heatmap below, cryptocurrencies have even weaker positive correlations with bonds than with stocks. Demonstrate Sharpe’s arithmeticThe correlation to energetic and passive equity funds is by far the best at 0.98.
Crypto, passive and energetic stocks and bonds: correlation heatmap
As far as raw materials are concerned1The heatmap below shows that each one cryptocurrencies have negligible positive or negative correlations with themselves. Only natural gas has small negative relationships with cryptocurrencies, especially BTC, LTC, ADA and XRP. Since the values are near zero, there’s little or no co-movement in these assets. Silver has the best correlation and is at 0.26 for silver and Bitcoin. Bitcoin, the so-called “digital gold”, has only a weak correlation with the dear metal.
Crypto and Commodities: Correlation Heatmap
So what can we take away from all of this? The low positive correlation of cryptocurrencies with mutual funds and ETFs could indicate a rise in cross-market trading and indicate the growing popularity of cryptocurrencies. Additionally, in a rising rate of interest environment and given the reduced effectiveness of the normal 60/40 stock/bond portfolio, cryptocurrencies’ weak correlation with traditional assets may provide potential diversification advantages for investors with long-term horizons who can withstand additional short-term volatility. However, not all cryptocurrencies have the identical lack of correlation to traditional assets, so investors must fastidiously determine which of them to focus on.
1. People commonly put money into commodities through futures contracts or futures contracts. Because these contracts are derivatives, they derive their value from their underlying assets. For example, a futures contract on gold derives its value from the spot prices of gold. According to the price of carry model, the futures price is influenced by the spot price of the underlying asset. The futures price is decided because the sum of the asset’s spot price plus transportation/storage costs. Using spot prices allows for a greater representation of the underlying value of the asset.
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