The end of the crypto diversification myth

The recent cryptocurrency crash raises many questions. Without cash flows or self-evident fundamental value, it is unclear why cryptocurrencies should correlate with other asset classes. Why do cryptocurrencies crash? Why are cryptocurrencies correlated with the stock market? Why do Fed interest rates matter for Bitcoin prices? Since the outbreak of the Covid-19 crisis in 2020, the correlation between cryptocurrency and stocks has gone from low and negative to consistently high and positive. This pattern is troubling both in terms of causes, which current theories cannot trivially explain, and in terms of consequences, as many mainstream investors introduce cryptocurrencies into their portfolios, including 401(K)s (Bindseil et al. 2022).

Previous research has focused on cryptocurrency pricing (e.g., Biais et al. 2022, Feyen et al. 2022, Liu and Tsyvinski 2021, Cong et al. 2021, Makarov and Schoar 2020). The question of the connection between stocks and cryptocurrencies is still open. In a recent paper (Didisheim and Somoza 2022), we argue, theoretically and empirically, that this correlation is largely caused by the trading habits of retail investors—namely, the fact that crypto-oriented retail investors tend to trade cryptocurrencies and stocks at the same time and in the same direction.

Figure 1 Rolling correlation between Bitcoin and S&P500 daily returns

Notes: The figure above shows the three-month rolling correlation of daily returns between Bitcoin and the S&P500. Data: Thomson Reuters and Yahoo Finance.

A unique dataset

To show this mechanism, we rely on the portfolio and transaction data of 77,364 retail investors from the Swiss bank Swissquote. Crypto-friendly Swiss regulation makes Swissquote one of the few banks worldwide to offer both traditional securities trading accounts and cryptocurrency wallets. Thanks to this peculiarity, our database contains: (1) individual trades and daily portfolios of traditional assets, including stocks, indices and options, between 2017 and 2020; and (2) crypto wallets and transactions of 16,483 clients. To our knowledge, we are the first to observe transactions in cryptocurrencies, not in a vacuum, but as part of retail investors’ overall portfolio decisions.

Patterns at the investor level

Our main finding is that micro-level retail investors engage in cross-asset buying and selling, and that this behavior became prominent in early 2020. Indeed, during this period, we observe a correlation between net trading volume of cryptocurrencies and stocks close to 80 %. While identifying what is causing this new trading pattern to emerge is beyond the scope of this column, our data sheds some light on the phenomenon.

In fact, the data suggests that this recent trading pattern coincides with the rise of a new breed of crypto enthusiasts. Unlike early adopters, fans of the technology and its long-term theoretical benefits to society, this new group of traders seems to perceive cryptocurrencies as a kind of technology stock, well suited for short-term speculation. Looking at the stocks favored by agents holding cryptocurrencies, we observe a strong preference for growth stocks and speculative assets. In addition, we notice significant changes after an agent opens a cryptocurrency wallet: their overall portfolio becomes riskier, with higher annualized returns at the expense of volatility accumulating to a significantly lower Sharpe ratio (-10.23%, annual). Interestingly, we also observe that the Sharpe ratio of the non-crypto portion of their portfolio increases after they open a cryptocurrency wallet. This somewhat surprising result is consistent with the idea that retail investors are shifting their attention from traditional assets to cryptocurrencies and reducing speculative activities on traditional assets. This idea is supported by our data: we find that although overall volume and investor attention are increasing, there exists a substitution in attention between stocks and cryptocurrencies.

Given that this regime change coincides with the Covid-19 crisis, a possible explanation could be that these new crypto traders emerged due to the liquidity shock caused by lockdown policies and government support in the form of partial unemployment benefits (Switzerland/US) and/or Covid -19 auxiliary checks (USA).

Krypto-Kyle

Using a simple two-asset extension of the canonical Kyle (1989) model, we show that these micro-level patterns can cause cross-asset correlation. The model relies on one key assumption, derived from our empirical observations: while two assets have uncorrelated fundamental values, they have correlated uninformed trading volumes.

We draw three testable implications from the model: (1) there was a regime change in retail investors’ cross-asset trading habits, coinciding with the change in the correlation we observe between cryptocurrencies and the stock market (ie, spring 2020); (2) the correlation between stocks and cryptocurrencies should be stronger during periods when the uninformed volume across markets from retail investors is greater; and (3) this relationship should be stronger for stocks preferred by crypto-oriented retail investors.

Suggestive evidence

We test these implications using Swissquote data and stock returns. First, we show that the correlation between net trading in stocks and cryptocurrencies jumps from zero to almost 80% in March 2020, and remains high thereafter, thus highlighting the regime change in retail investor behavior. The figure below shows the correlation between net trading flows in cryptocurrencies (panel A) and shares of Swissquote clients and the correlation weighted by trading volume (panel B). The second panel highlights that the new trading pattern coincided with a significant increase in the retail volume of cryptocurrencies.

Figure 2 Correlation between net trading flows in cryptocurrencies and stocks

Notes: The figure on the left shows the correlation between net trading flows in cryptocurrencies and stocks by Swissquote clients. The figure on the right shows the same figures, weighted by trading volume.

Second, we use Swissquote volume on cryptocurrencies as an estimate of uninformed cross-market activity and the portfolio of crypto-oriented retail investors to identify stocks where cross-market retail is likely to be stronger. We sort the 3,000 most traded stocks in the US markets into quintiles determined by the preference of crypto-oriented retail investors. The first (fifth) quintile contains the stocks traded the least (most) by retail investors trading both cryptocurrencies and stocks on the Swissquote platform throughout our four-year sample. Using panel regressions, we find that for all but the first quintile, the total cryptocurrency volume of retail investors in a month predicts the correlation between the stock’s and Bitcoin’s daily returns. Furthermore, and as predicted by the model, the magnitude of the effects increases monotonically across quintiles.

Conclusion

We propose a possible mechanism that links the price of cryptocurrencies to the price of (growth/technology) stocks. This link is more than an interesting piece of trivia, as we are now seeing cryptocurrencies being included in the portfolios of well-established hedge funds, well-known investors and households. Nevertheless, the financial channel we identify highlights how little we know about this asset class and the potential systemic risk stemming from its inclusion in mainstream investment portfolios.

Asset and risk managers should consider the mechanism presented in this column when weighing the costs and benefits of introducing cryptocurrencies into a portfolio. If a high positive correlation with stocks can be driven by something as unpredictable as the trading habits of retail investors, diversification can hardly be a good rationale.

References

Biais, B, C Bisiere, M Bouvard, C Casamatta and AJ Menkveld (2020), “Equilibrium bitcoin pricing”, SSRN Working Paper 3261063.

Bindseil, U, P Papsdorf and J Schaaf (2022), “The Bitcoin challenge: How to tame a digital predator”, VoxEU.org, 7 January.

Cong, LW, Y Li and N Wang (2021), “Tokenomics: Dynamic adoption and valuation”, The review of economic studies 34: 1105–1155.

Didisheim, A and L Somoza (2022), “The End of the crypto-diversification myth”, SSRN Working Paper 4138159.

Feyen, E, Y Kawashima and R Mittal (2022), “The ascent of crypto assets: Evolution and macro-financial drivers”, VoxEU.org, 19 March.

Kyle, AS (1989), “Informed Speculation with Imperfect Competition”, The review of economic studies 56: 317–355.

Liu, Y and A Tsyvinski (2021), “Cryptocurrency Risk and Return”, The review of economic studies 34: 2689-2727.

Makarov, I and A Schoar (2020), “Trading and Arbitrage in Cryptocurrency Markets”, Journal of financial economics 135: 293–319.