How to deal with crypto winter
As announced, monetary tightening sparked a sharp reduction of digital token valuations and a sequence of distress events is now rippling through cryptocurrency markets. No question that this news is like déjà vu, the outcome of a recurrent 'financial sin' starting with a wave of irrational exuberance, ending with losses and collective anger against the 'greedy ones'.
In November 2008, on a visit to the London School of Economics (LSE), Queen Elizabeth II asked her hosts: "Why did no one see it coming?". She was referring to the financial storm of 2007/8. To avoid that the Queen's question resonates once again, let us take a look back and reconsider the vicissitudes that are taking place in decentralized markets leveraging on the body of research that financial economists have produced dissecting past financial crises.
The first advice is to refrain from the dangerous 'this time is different' narrative, claiming that the old rules of valuation no longer apply and that the new situation bears little similarity to past disasters. Decentralized markets are certainly made possible by a newly introduced technology, blockchain protocols, but the digital innovation layer should not hide the common traits that the unregulated growth of the cryptocurrency market shared with past episodes of uncontrolled financial expansion.
Consider for example the regulation under discussion aimed at reducing the impact of distress of stable-coins, it will necessarily have many similarities with the prudential approach established after 2008 to limit systemic risks created by money market funds.
During the big financial crisis excessive risk taking was driven by predatory lending practices that targeted low-income homebuyers. Similarly, crypto finance is characterized by an unprecedented ease of accessibility to financial products. DeFi (decentralized financial) applications target broad population segments, ranging from young millennials to unsophisticated consumers living in emerging countries.
In principle, extended participation is a positive spillover of financial innovation. However, another lesson we learned is that the effective ability of household consumers to capture the profits arising from financial innovation is severely limited by the existence of a financial literacy gap.
In simple words, the major threats to investors' safety do not arise because they do not understand how digital technology works. It is the lack of financial knowledge that limits the ability of investors to benefit from new opportunities.
Consider for example the notion of 'trust' in blockchain economics. Blockchain protocols are usually claimed to be "trustless", meaning that you don't have to trust a third party for the validation of a transaction: a bank, a person, or any intermediary that could operate between you and your cryptocurrency transactions or holdings.
On the other hand, financial economists have empirically verified that trust in a specific financial system, i.e. the willingness of members to act together to pursue shared objectives, is a necessary condition for the creation of a robust market.
Surprisingly, while the technical properties enforcing the 'trustless' nature of a protocol are usually well explained, far less is known about the organizational 'trust' that is determined by social and governance characteristics of the ecosystems created by the community of blockchain developers and adopters.
To foster more inclusive financial development, policy actions should therefore target the transparency on these organizational characteristics also in the crypto space. In this respect, a proper definition and regulation of the so called DAO's, Decentralized Autonomous Organizations, is certainly the most important step, yet to come.
A second interesting advice from current research is that information technology can be deployed to assist rather than harm investor's choice. Behavioral economists have shown that suboptimal selection of financial instruments may derive from cognitive biases that are by now well understood. Machine learning offers the possibility to implement efficient scalable advisory services at low prices to help the broad public avoid these behavioral traps, thus reducing the costs of uncontrolled financial development.