During the last two years, decentralized finance (DeFi) has become one of the most attractive venues for crypto investors and traders. Disproportionally high yields, asymmetrical arbitrage opportunities and what feels like a never-ending wave of new protocols have created a regular stream of lucrative opportunities in the DeFi space. We discussed some of the alpha opportunities in DeFi in a previous CoinDesk article.
The asymmetry of these opportunities is directly related to the inefficiencies of a nascent market like DeFi. The dominant narrative among DeFi supporters is that the alpha opportunities in DeFi are likely to dissipate as the market becomes more efficient. That thesis seems aligned with the behavior of most financial markets in history but how would it play out in DeFi? Can DeFi become an efficient market?
Jesus Rodriguez is the CEO of IntoTheBlock, a market intelligence platform for crypto assets. He has held leadership roles at major technology companies and hedge funds. He is an active investor, speaker, author and guest lecturer at Columbia University in New York.
A good recipe to try to answer these questions is to understand the fundamentals of capital markets efficiency and map those fundamentals to the world of DeFi. Theories about market efficiencies have a rich history involving some very colorful characters.
The efficient market hypothesis
The idea of quantifying the dynamics of efficiency in financial markets has been around for centuries. In 1863, French stockbroker Jules Regnault observed that price deviations in a security are directly proportional to the square root of time. In other words, the longer you hold a security, the more you are exposed to wins or losses due to price variations.
One relatively unknown hero in the evolution of ideas about market efficiency was the French mathematician Louis Bachelier, who is famous for being one of the fathers of modern statistics. In some of his works, Bachelier deduced that “the mathematical expectation of speculators in financial markets is near zero.” Many of these ideas were way ahead of their time and were rediscovered almost a century after in the context of efficient market theories.
Some of the ideas about efficiency in capital markets caught momentum in the 1950s with the work of economists Milton Friedman and Paul Samuelson. Samuelson, in particular, was a big promoter of Bachelier’s work and its applicability to equities markets. Genius mathematician Benoit Mandelbrot also dabbled in market efficiency models and challenged some of the common beliefs around stock prices distributions.
The work in the early second half of the 20th century takes us to the most important paper in the efficiency of financial markets. In 1970, Eugene F. Fama published “Efficient Capital Markets: A Review of Theory and Empirical Work,” in which he defines an efficient market as “a market in which prices always ‘fully reflect’ available information…” This was the essence of what we know as the efficient market hypothesis (EMH).
In the paper, Fama presented three types of efficient markets: (i) strong-form; (ii) semi-strong form; and (iii) weak based on the way public and non-public information is factored in the price of the asset. The other important contribution of Fama’s paper was the famous “joint hypothesis problem” that essentially says the EMH cannot be quite tested or rejected. To explain this, let’s assume for a short minute that crypto was an efficient market subject to the principles of the EMH. Let’s say that we have an asset pricing model that indicates that the price of ethereum should be $4,000 in a month. Then ethereum’s price skyrockets to $5,000, which is a high deviation from the asset pricing model. The joint hypothesis problem indicates that we can never be sure if the market was inefficient or the asset pricing model was wrong. In other words, we can’t quite prove if abnormal prices are a result of market inefficiencies or that the flaws in the model used to price the assets in the first place.
The EMH has divided economists and market experts for decades. Certainly, new markets are more prompt to show signs of inefficiencies and, therefore, challenge some of the principles of EMH. This is certainly the case of DeFi.
Six sources of market inefficiency in DeFi
Massive Information Asymmetry: Nothing causes more inefficiencies in a financial market like the asymmetry of information between insiders and general investors. In the case of DeFi, people who are close to the protocol projects have disproportionately richer access to information than the investors using the protocols. Earlier access to information such as new liquidity pools, governance changes or protocol modifications can result in significant edges in the DeFi market.
Let’s take the example of an automated market maker (AMM) protocol that is about to launch some new pools to boost liquidity for a specific token. Having access to information about that could allow insiders to be ready to supply liquidity right when the pool launches, thus capturing a significant portion of the rewards.
A growing protocol ecosystem: Traditional capital markets operate over an infrastructure that has been established for decades while DeFi is building on top of a constantly changing landscape. New financial primitives in the form of DeFi protocols are being launched every week. During the growth phase, those protocols are going to be natively inefficient and effects of those inefficiencies will cascade through other areas of the DeFi space. For instance, a new algorithmic stablecoin can regularly deviate from its pegged value creating arbitrage opportunities.
Governance changes: Governance proposals regularly change the behavior of DeFi protocols, leading to market inefficiencies. This dynamic is very unique to DeFi and has no clear equivalent in traditional capital markets. From changes in incentive mechanisms to more drastic modifications to the behavior of a specific protocol, DeFi governance is a regular source of inefficiencies in the market. A clear example of this could be a governance proposal that changes the length and weights of different liquidity pools in an AMM which leads to higher yields produced by the pools with better incentives.
Protocol attacks: By now, hackers and security attacks can be considered a native element of the DeFi ecosystem. New protocols are regularly exploited creating liquidity gaps in the market which can be leveraged in different trades. From that perspective, security attacks are, in effect, a source of inefficiency in DeFi which has no parallel in other financial markets.
The CeFi influence: The dichotomy between CeFi (centralized finance) and DeFi is one of the most unique dynamics in crypto and one that can be considered a source of market inefficiencies. Events that take place on centralized exchanges have ripple effects in the DeFi market and vice versa, creating regular opportunities for arbitrage. A classic example could be an increase in trading activity in a given DeFi governance token in centralized venues, which can lead to a price increase and translate into improved rewards in the corresponding DeFi protocol.
A fragmented ecosystem: The fragmentation of DeFi, with a large number of different protocols, is hard to mitigate. A large number of crypto assets traded in highly diverse protocols that are not integrated will produce price mismatches and regular arbitrage opportunities between those protocols. As DeFi continues to grow, this level of fragmentation is likely to increase, leading to higher market inefficiencies before it consolidates, producing the opposite effect.
An efficiently inefficient market
Traditional market wisdom tells us the future of DeFi is to become a relatively efficient market. We should expect a consolidation in protocols and blockchains, a contraction in the yields and liquidity mining programs and a more transparent flow of information across the ecosystem. However, some of the factors discussed in the previous section make that path to an efficient market far from trivial. DeFi is still a very nascent market that hasn’t seen a major adoption from mainstream investors.
Those variables indicate the inefficiencies in DeFi are likely to continue for the foreseeable future. And some sources of inefficiency in DeFi are native characteristics of the ecosystem and not a byproduct of market dynamics. Transitioning to efficient market dynamics is going to take a bit more than the natural growth of the DeFi ecosystem. Maybe we can all agree that DeFi will become an efficiently inefficient market.