My Investment Process for Cryptoassets (July 2021)

Jason Choi
4 min readJul 12, 2021

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The following piece was posted as a thread on my Twitter account: https://twitter.com/mrjasonchoi/status/1412127013310140416

I’ve been investing full time in crypto since 2018 from a personal and professional ($100M+ long/short fundamentals fund, $110M long-only venture fund) capacity.

The following primarily pertains to my investments in secondary markets. When it comes to liquidly traded cryptoassets, my investment strategy can be summed up as follows.

First, some background: When I first started investing in crypto, I focused on making thesis-driven bets with a multi-month to year time frame. There wasn’t any real process besides finding what seems like a good project and buying it.

However, even after coming up with the most meticulous valuation models, market prices rarely seemed to reflect any of my fundamental projections. One of the reasons was no one can predict when adoption for new technologies happen, so growth assumptions are way off.

But more importantly, I was blindly applying equities analysis framework today to a market that was nascent and had no consensus around valuation approaches. e.g. Using NVT sounds like a crypto-proxy for PE ratios, but real prices have barely any relation to it.

Bitcoin and Ethereum NVT ratios versus price over time

Since we’re on the topic of valuation, an aside… whenever I feel like I’m thinking too small in crypto, I look back to one of the earliest attempts at valuing Bitcoin, back in 2016. The report had a price target of $62/BTC!

Needham valuation framework for Bitcoin, circa 2016

Anyway, back to my investment process. Crypto has come a long way since the days of using NVT to look at which Layer 1 is “underpriced”. Today, DeFi generates millions in fees *daily*, allowing for more sophistication around valuations.

Revenues generated by various DeFi protocols

My intuition: the lower the price, the less room it has to fall (margin of safety)…typically. Having a quantifiable screen (e.g. absolute FDV, mcap/TVL, mcap/revenue, inflation-adjusted revenues, ) helps me quickly screen for things that may be underpriced.

I say “typically” since illiquidity can be the reason behind gross mispricings. In a market selloff, thin liquidity will exacerbate downside (see my thread on the relationship between liquidity and price here). 2018’s 99% drawdowns, anyone?

Given the lack of consensus around valuation frameworks, having too strong of a valuation screen will also lead you to miss out on profitable investments. e.g. $SNX, which traded at a high premium but outperforming DeFi at multiple points.

Circulating and fully diluted valuations of decentralized exchange governance tokens compared to their daily average volumes as a simplistic heuristic

This is why the second step of my process is important. Ever noticed how when crypto rallies, it does so in categories? We had the algo-stable craze in July 2020, DeFi summer in late 20, NFT bubble in 2021, then ETH/BTC rally in 2021.

Understanding capital rotation is key. It doesn’t matter if an asset seems “cheap” — it can always get cheaper (value trap). Crypto today has the attention span of a 5-year old child. Imagine sector rotations in equities, but shrink that down to weeks, even days! This doesn’t mean sell everything not in vogue and chase every trend. It simply informs how aggressive and quickly I want to size an asset, or if I want to wait and be patient.

Say you found an undervalued DeFi token generating real revenues, and think DeFi as a sector is making a comeback. (3) is where the real work is done. This is where you dive deep into the project, and understand it intimately. This involves understanding the product roadmap, mechanism design, trade offs, and competitors. Practically this means using the product, speaking to developers, reading docs, lurking in community forums, reading research reports, quantifying user/fee growth.

Step (3) is the most intensive. Use tools and resources like:

@DuneAnalytics
@tokenterminal
@Delphi_Digital
@MessariCrypto
@nansen_ai

Using them may not always give you an edge, but not using them is a handicap. If you work at a fund, convince your boss to pay for these.

I lump (4 — Catalyst/Narrative) and (5 — Risks) together because they ask a similar question: what will cause this asset to re-price (or not)? As a corollary, you should know your re-underwriting price — i.e. how much do you allow your asset to fall in price before re-assessing whether you were wrong? What constitute as catalysts? Bullish example: governance proposal for new token update that is not properly priced in (e.g. long $AAVE in 2020, +5000% since)

Then finally, once all the boxes are checked, comes arguably the equally important part: sizing. In most funds, no one but the CIO/ portfolio manager gets a say over sizing. This is the single biggest differentiator between returns for funds who are in roughly the same bets.

I’ll leave the topic of sizing for another thread. In summary, the framework I used which resulted in ~75%+ of my investments outperforming a weighted index of top 30 cryptos over the bear and bull phases of the past 3 years is as follows:

https://twitter.com/mrjasonchoi/status/1412127085364084736?s=20

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Jason Choi

Investor @ Spartan Capital, a fundamentals driven crypto fund. Host of The Blockcrunch Podcast. Seeking radically honest and thoughtful feedback.