Ending the crypto-diversification myth

The recent cryptocurrency crash raises numerous questions. With no cash flow or self-evident fundamental value, it is unclear why cryptocurrencies should be correlated with other asset classes. Why is cryptocurrency crashing? Why is cryptocurrency related to the stock market? Why Fed Interest Rates Matter to Bitcoin Price? Since the start of the Covid-19 crisis in 2020, the correlation between cryptocurrencies and equities has gone from low and negative to consistently high and positive. This pattern is troubling both in terms of reasons, which current theories cannot trivially explain, and in terms of outcomes, as many mainstream investors are introducing 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 correlation between equities and cryptocurrencies is still an open one. In a recent paper (Didisheim and Somoza 2022), we argued theoretically and empirically that this correlation is mainly caused by the trading habits of retail investors – namely, the fact that crypto-based retail investors trade cryptocurrencies and stocks at the same time and in the same direction.

Figure 1 Rolling Correlation Between Bitcoin and S&P500 Daily Returns

Comment: 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 illustrate this process, we rely on portfolio and transaction data of 77,364 retail investors from the Swiss bank Swisscote. Crypto-friendly Swiss regulations allow Swisscote to be one of the few banks worldwide to offer both trading accounts in conventional securities and cryptocurrency wallets. Thanks to this specialty, our database includes: (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 customers. To the best of our knowledge, we are the first to observe transactions in cryptocurrencies, not in a vacuum but as part of the overall portfolio decisions of retail investors.

Investor-level patterns

Our key finding is that, at the micro-level, retail investors engage in cross-asset trading and this behavior becomes prominent in the early 2020s. In fact, during this period, we observe a correlation between the net trading volume in cryptocurrencies. And the stock is close to 80%. While identifying the reasons for the emergence of this new trading pattern is beyond the scope of this column, our data shed some light on the phenomenon.

In fact, data suggests that this recent trading pattern coincides with the rise of a new breed of crypto enthusiast. In contrast to early adopters, technology enthusiasts and its long-term theoretical benefits to society, this new group of traders perceive cryptocurrencies as a kind of tech-stock, suitable for short-term speculation. Looking at the preferred stocks of agents holding cryptocurrencies, we notice a strong preference for growth stocks and speculative assets. Additionally, we observe significant changes after an agent opens a cryptocurrency wallet: their overall portfolio becomes riskier, with higher annual returns that come at the cost of volatility at a significantly lower Sharpe ratio (-10.23%, annualized). 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 shift their focus from traditional assets to cryptocurrencies and reduce speculative activity on traditional assets. This idea is supported by our data: we find that when aggregate volume and investor attention increase, there exists a substitution of attention between stocks and cryptocurrencies.

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

Crypto-Kyle

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

We highlight three testable implications from the model: (1) there has been a regime shift in the trading habits of cross-asset retail investors, which we assume coincides with a shift in the correlation between cryptocurrencies and the stock market (ie in spring 2020); (2) correlations between stocks and cryptocurrencies should be stronger at times when cross-market uncertainty from retail investors is large; and (3) this relationship should be stronger for stocks preferred by crypto-based retail investors.

suggestive evidence

We examine these effects using Swissquote data and stock returns. First, we show that the correlation between net trades of stocks and cryptocurrencies rises from zero to about 80% in March 2020 and remains high thereafter, thus highlighting a regime shift in retail investor behavior. The figure below shows the correlation between net trading flows in cryptocurrencies (Panel A) and SwissCot subscribers’ stocks and the correlation weighted by trading volume (Panel B). The second panel highlights that the new trading pattern has coincided with a significant increase in retail trading volume in cryptocurrencies.

Figure 2 Correlation between net trading flows in cryptocurrencies and stocks

Comment: The figure on the left shows the correlation between net trading flows in cryptocurrencies and stocks by SwissCot customers. The figure on the right shows the same numbers, weighted by trading volume.

Second, we use Swissquote volume in cryptocurrencies as a predictor of cross-market volatility activity and to identify portfolio stocks of crypto-oriented retail investors where cross-market retail trading is likely to be strong. We arrange the 3,000 most traded stocks in the US market into quintiles determined by the preferences of crypto-based retail investors. The first (fifth) quintile has the lowest (highest) stocks held by retail investors who trade both cryptocurrencies and stocks on the Swissquote platform across our four-year sample. Through panel regression, we find that for all but the first quintile, retail investors’ total cryptocurrency holdings in a month predict the correlation between stock and bitcoin daily returns. Additionally, and as predicted by the model, effect sizes increase monotonically across quintiles.

Conclusion

We propose a possible method of linking cryptocurrency prices to (growth/technology) equity prices. This link is more than just an interesting piece of trivia, as we now see long-established hedge funds, well-known investors and households include cryptocurrencies in their portfolios. Nevertheless, the economic channel we identify highlights how little we know about this asset class and the potential systemic risks arising from its inclusion in mainstream investment portfolios.

Asset and risk managers should take into account the process presented in this column when weighing the costs and benefits of introducing cryptocurrencies into a portfolio. If a highly positive correlation with equities can be driven by something as unpredictable as the trading habits of retail investors, then diversification is hardly a valid argument.

reference

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, 07 January.

Kong, LW, Y Li and N Wang (2021), “Tokenomics: Dynamic Adoption and Evaluation”, Review of Financial Studies 34: 1105–1155.

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

Fein, E, Y Kawashima and R Mittal (2022), “The Rise of Crypto Assets: Evolution and Macro-Financial Drivers”, VoxEU.org, 19 March.

Kyle, AS (1989), “Informed Inference with Imperfect Competition”, Review of Economic Studies 56: 317–355.

Liu, Y and A Tsyvinski (2021), “Cryptocurrency Risk and Returns”, Review of Financial Studies 34: 2689–2727.

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

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