Crypto price inefficiencies and thesis building

Prices move erratically, and crypto is infamous for having an extremely inefficient market. This is changing and will diminish as more sophisticated investors move into the space. I say sophisticated because all the alpha that has been squeezed out of the US equity market is the direct result of the millions of specialized individuals from hedge funds, banks, and institutions observing every single move, with billions of capital to deploy. So many people and so much money that inefficiencies get squeezed out. Crypto is an example of a market that is retail dominant — by number of participants. Now think about the state of valuations. Not necessarily the nominal amount, but projects relative to each other. These inefficiencies will be diminished but not at the same rate as the US equities market. I think this is largely due to the correlation between investors and their expertise. Finance is very closely related to business. Finance is in no way related to computer science or engineering. So even for many institutional financial analysts to be analyzing crypto, the knowledge gap required to make informed decisions is extremely large. This is true more so for the average retail investor, or quite frankly the majority of market participants. While different areas of expertise are required for different sectors within crypto, the projects that currently assume the largest valuations and mindshare are layer 1s. Requiring somewhat advanced knowledge to be able to properly analyze. Layer 1 mindshare may diminish as applications abstract the back end from users in the long-term, but currently that isn’t the case. As such, the majority of those analyzing the different layer 1s and trying to determine the most likely winner, or set of winners, lack the necessary knowledge to do so. The mismatch between the knowledge of investors, and the knowledge required to make well informed decisions is extremely wide. Thus, inefficiencies are born.

Knowing that, it is important to be thinking and crafting theses about long-term trends. This is so that short-term and long-term trends can be distinguished. An inability to distinguish between the two can distort the reality of the current and future situation. Good news, people can still make money and be wrong, but don’t confuse making money with being right. That is why having long-term theses can allow for ideas to be framed and tested against to understand where in context they will fit. A thesis about why Solana will do well over the next 6 months can be right, but don’t confuse that with thinking Solana will be the best layer 1 in the long term. Having a long-term thesis about the winning layer 1 can allow short term inefficiencies to be identified, which can then be capitalized on. This goes for any sector within crypto.