Click here to open the Bloom Token Valuation Model sheet
This model is based on the wonderful Cryptoasset Valuation Framework by Chris Burniske. I copied his spreadsheet and modified it for the Bloom Token. I won't go into the details of the mode, but I highly suggest you read the original post by Chris before coming back to this one.
I'm primariliy working on this so I can get an idea of how much each variable might affect the utility value of the network. In the short term, the actual price of the asset will be dominated by it's speculation value, but I believe that the total value of the networks will trend towards the total amount of value being exchanged within the network.
Given my current assumptions, this is the primary output of the model:
This is saying that given the assumptions about the amount of value being exchanged in the network and the economics of the token supply, if you want to earn 30% per year (13.7x return) over 10 years, a reasonable price to pay would be roughly $1.16 per token. If the model is accurate, anything less than this would be undervalued and anything above would be overvalued. You can change the discount rate if you are aiming for different kinds of returns. This should be adjusted based on what you perceive to be the risk of the token. Since all cryptoassets are high risk endeavors, the possible return should be high to justify the risk.
In the sheet, I've prepared 3 different versions of it with different values. The first is what I think is optimistic but possible, the next is a very conservative view, and the last is what I see as the best case (if no new uses of the token are introduced). This post will only cover the optimistic but possible view.
Going Through the Assumptions
There are quite a lot of variables in the model. They will be shown as blue in the spreadsheet. Go ahead and copy the spreadsheet so you can edit the inputs and see what effect that has on things. I probably got some of these things wildly wrong, but I put in my best estimate for each one. If it isn't mentioned here, I left it the same as the original model.
When discussed in this post, they will show up like so:
Variable Name: Value
I'm hoping to generate discussion on what sensible values for these variables are. Please comment here or directly on the sheet with suggestions and ideas.
Tokens Taken in the Float
One of the key parts of the model is about estimating the number of tokens being held in various ways (taken out of the float) and the number being activately exchanged to fulfull the purpose of the network. The more tokens hodl'd or otherwise bonded makes the remaining, high-velocity token in the float worth more.
Voting
I think that in the begining, almost no one is holding tokens solely for the value in voting on the platform. Until the smart contracts are in place to allow voting, we still have to trust the Bloom team. I think as the network matures, and voting demonstrates real power over the network, the amount of tokens held purely to be allowed to vote will go up. This could be included in the model, but I didn't make that addition yet. Instead, I made an estimate for the 10 year period im looking at of 10% of the tokens held just for voting. I think it will be lower initially, and higher later, though.
Tokens Held for Voting: 10%
Invititation Collatoral
BLT will be locked up for several months when a new user is invited to the platform. This acts as collatoral, making it risky to try to game the system. I'm hoping to get a better estimate from the Bloom team on this, but for now I'm guessing 5%.
Tokens Held as Invite Collatoral: 5%
Bonding
Payment channels, like Raiden, effectively bond the asset and keep it tied up and unable to be part of the economy for some time. Liquidity used for exchange do this as well, as in Kyber Network. This is difficult to estmate, so I used a slightly lower value than the original model.
Tokens Bonded by Nodes: 15%
Addressable Markets
The two ways that you can spend BLT on the Bloom network is to get access to credit risk data and to perform identity verification through individual attestations. There might be more ways to spend BLT in the future, but this seems to be the current plan.
Credit Assessment
Right now in the US credit assessment , scoring, and analytics are completely dominated by FICO and the three credit bureaus: Equifax, TransUnion, and Experian. I can believe that a single, decentralized, system could take the same position as these three, while being international as well.
% of Risk Assessment Addressable for BLT: 90%
Identity Verification
There are lots of kinds of ID verification, and many competitors both in and out of the crypto world. I am not sure what a reasonable number to put here is, but I could imagine that the value of identity through attestations of other people who know you could be high. This is a different approach than Civic is taking, where they do the ID verification part in a centralized manner.
% of Global ID Verification for BLT: 20%
Other Markets
There may be other markets I haven't considered. Other kinds of risk assessment come to mind, such as insurance risk. I'd be interested to hear if I've left something big out of the picture.
Velocity
Velocity of tokens in the float is one of the more important variables. This is the average amount of times tokens exchange hands over a given period. I'm using the same estimate as the previous model, but it could be higher.
Velocity: 16
Market Adoption
The model assumes an S curve for market adoption. The curve itself has a couple of inputs, all of which are important. I think it will take a few years to start fast growth in both markets, and that Bloom will get larger market share in credit risk assessment than it will in ID verification.
Base year is 2018, the saturation percentage is the amount of the market we expect it to take when the network is mature, the start of fast growth is the year things start taking off, and the take over time is the amount of time to get close to the saturation point.
Credit Risk
I think the opportunity is bigger in credit risk, so it has a more aggressive adoption curve.
Base Year: 2018
Saturation Percentage: 30
Start of Fast Growth : 2020
Take Over Time: 12
ID Verification
Slightly slower adoption with a lower saturation point:
Base Year: 2018
Saturation Percentage: 10
Start of Fast Growth : 2021
Take Over Time: 15
Investment Inputs
To find a value of the token for you to be comfortable investing we have to specificy how big of a return you are looking for.
Discount Rate
Tokens are riskier than the stock market, and the S&P 500 has an annual return of almost 10%. We're looking for significantly better returns than that to justify all the risks that come with cryptoassets. I kept the original value of 30% which is a 13.7x return.
Discount Rate: 30%
Hold Period
This is the time over which you are expecting to hold the token before selling it. I'm in it for the long(ish) haul, so I put 10 years.
Years Between 2018 and End Year: 10
Closing Thoughts
This isn't a price target, it's not investment advice, and I might have gotten some things totally wrong. But, I do believe that this way of thinking about a utility token is helpful in wrapping your head around what ultimately determines it's value.
Please leave comments on the sheet or here if you think the model could be improved!