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1/ How do you value a governance coin? I’ll focus specifically on $YFI. Two methods you can utilize are a total-value-locked (TVL) approach and a comparative analysis based on P/E. I’ll start with the TVL approach.
2/ The logic here is that the value of a governance token should be at worth at least as much as the value locked in the protocol. If it is not, an activist investor could theoretically buy up a controlling interest and enact protocol changes that are in his best interest
3/ and at the expense of either liquidity providers, or other holders. Essentially, this is a hostile takeover; however, how can you calculate an accurate TVL metric? In DeFi, everyone has a 10 minute attention span and are constantly shifting yield farming strategies between
4/ protocols: known as fair-weather farming. The @iearnfinance ecosystem created by @AndreCronjeTech had a peak of ~345m in TVL during the initial $YFI farming craze according to DeFiPulse. Since 7/30 the TVL has fluctuated between $164m and $225m, with a 7-day mean of $187m
5/ This is likely a more accurate portrayal of TVL, net of fair-weather farmers for the @iearnfinance ecosystem. So under this valuation methodology, the marketcap of $YFI should be worth at least the amount of its TVL.
6/ There are 30,000 $YFI in circulation, and ignoring future inflation to be decided by governance. This gives a FMV of ~$6,235, but doesn’t take into account the PV of FCF, which is important since the ecosystem is already generating profit ($60k weekly ~$3.1m annually).
7/ Under the assumption that earnings will increase by 50% each year for the first 3 years, then increase terminally at 10% (the average APY of the y pool) can help paint a better picture of PV of FCF.
8/ These need to be discounted, which is where this analysis gets very subjective. VC funds don’t often employ a DCF analysis for seed or early-stage tech startups because there are so many variables that could blow up the model; however, when they do use a discount rate it is
9/ usually relatively high ~70%. Using the information above we can roughly estimate the PV of FCF to be ~$22m, which would imply a FMV of ~$7,000. Estimated growth and discount rates would change this quite a bit, and it also ignores any parabolic increases in TVL.
10/ Given that @iearnfinance is building an entire suite of products and the TVL right now is primarily the y pool on @curvefinance, it is not unreasonable to assert that the TVL will more likely than not increase drastically. Hard to accurately quantify such increases, however.
11/ Another method of valuation is using a comparative analysis of earnings of other projects in the DeFi space. @iearnfinance is a lending aggregator, and ultimately shifting to become the de facto yield generator that sits on top of nearly all existing DeFi protocols so there
12/ is no real direct or close comparison. But using the entire space as a metric, we can make some estimates. Comparing the P/E ratios between several of the most prominent DeFi protocols (AAVE, Balacer, Bancor, Compound, Maker, SNX, etc) the average P/E ratio for DeFi is ~161.
13/ It is subjective choosing which protocols should be included/excluded as they may not be truly comparable (i.e., is a lending aggregator comparable to a DEX?). But using the average P/E ratio as a proxy, this implies a marketcap for $YFI at ~517m, or $17,200 per coin.
14/ A notable weakness of the comparative analysis methodology is that maybe the comparable protocols are all overvalued based on their earnings. If the entire space is completely overvalued then this may not be an accurate or realistic methodology.
15/ For instance, Compound has an eye-popping 331 P/E ratio; SNX is another one with a very high ratio at 165. It’s likely the ratios are so high because the market is factoring in future growth of earnings, but it is yet to be seen if these numbers are justified.
16/ Either way it appears that $YFI is undervalued based on the total amount of capital locked in its ecosystem, and comparing its price-to-earnings to other DeFi protocols.
17/ The efficient market hypothesis may seem reasonable and rational in macroeconomics 101, but in real-world markets it doesn’t work. Markets are not efficient and this is even more obvious in crypto markets than traditional finance.
18/ Mainly due to information asymmetry, as a result of its largely unregulated nature, and unsophisticated market participants. Market participants are irrational, driven by emotional and cognitive biases. This is a separate discussion on game theory.
19/ But since it is crypto and there is a significant amount of irrational exuberance and greed add another 2x premium to the figures above in an attempt to quantify market irrationality.
20/ If nothing I said above makes sense, don’t worry because it doesn’t and it is a long-winded way of saying number go up.