3. Background
o13 dabbled with Dogecoin → Memes, community economics
o14 B.A. Economics & International Affairs (St.Gallen, Cape Town)
o15 fell down the ETH rabbithole
o16 met Simon De La Rouvière in Cape Town
o16 worked on blockchain identity with UNICEF, token models, founded Linum Labs
o17 joined ConsenSys to work on uPort
o18 left ConsenSys to work on Molecule & curation markets
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4. Curation Markets
“... reduce information asymmetry in the market through the usage of novel,
skin-in-the-game signals generated through the use of tokenized
cryptoeconomic incentive games”
1. Market participants “put their money where their mouth is”
2. Stake value / attention into the markets they believe will be more valuable
3. The market’s currency is a proxy for attention
4. Early adopters are rewarded for early attention as the market value
increases
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(De La Rouviere, 2018)
5. Curation Markets
1. Crypto economic primitive
2. Building block in token engineering alongside TCRs
3. These are experiments, not blueprints
4. Very early days
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6. Token Bonding Contracts
1. Accepts ETH or another ERC20 token in exchange for minting
new token of its denomination
2. Holds the ETH or ERC20 in reserve (the bond or collateral)
3. Users can freely exchange ETH for tokens and vice versa along
the curve
4. Important: no one gets the bond ≠ ICO
a. Although exceptions possible (discussed later)
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7. Bonding Curves
Price per token (y-axis) is
bonded to a number of tokens
in circulation (x-axis) by a
predefined slope formula
Quadratic curve:
currentPrice = tokenSupply²
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(De La Rouviere, 2018)
10. Advantages of Bonding Curves
1. In a token bonding curve $1 is $1
2. In a free-market $1 → $25 market cap
3. Less opportunities for Pump and Dump
4. On-chain liquidity → lesser need for
centralized exchanges
5. More security as the asset’s market cap is
tied to its collateral
6. Less opportunity for derivatives or
leverage
7. Attention proxy
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13. Curve Types
1. Exponential Function
a. Price stays low for 80% of curve then accelarates unmanageably and unreasonable
b. Growth rate leads to volatile speculative upside and downside as project becomes popular
2. Linear Function
a. Magnitude change in price and tokens issued are on same level
b. Early token holders are rewarded disproportionately much (e.g. 1,000,000x return)
3. Rule-Based Function
4. Sigmoid Function
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(Wilson Lau, 2018)
https://medium.com/@wilsonplau/on-single-bonding-curves-for-continuous-token-models-a167f5ffef89
14. Rule-Based Functions
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● Rule to guide the token model
● “Token should appreciate by X%
for every doubling / tripling / Y of
the number of tokens issued or
numbers of users on the platform”
● ((a) x% appreciation; (m) adjusts slope; (c) is doubling
factor; b is constant similar to linear function
(Wilson Lau, 2018)
https://medium.com/@wilsonplau/on-single-bonding-curves-for-continuous-token-models-a167f5ffef89
15. Sigmoid Function
1. S-shaped curves
2. Best suited for market that stabilise
after a certain period (inflection point)
3. Found in population growth and
density
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16. Token Curated Intellectual Property
Problems with IP today:
1. Monopolies of IP
a. Ownership, rent extraction
b. Price gouging
2. Access to capital to develop
3. Good ideas often fail because of
bad companies or teams
4. Instead: tokenize IP using token
bonding curves
This could lead to:
1. Open source development of IP
2. Plutocracy of ideas vs. capital
3. Incentivize cross-collaboration
4. Faster development cycles
5. Sharing of
a. Risk
b. Costs
c. Rewards
6. Lower prices + more competition
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17. Tradeable Patents with Re-Fungibles
1. IP usually based on patents & proprietary data timestamped claim
2. Take information (data) in the patent and attach to an NFT (ERC721)
3. Set the ERC20 Bonded Curve Token as the owner address of the ERC721
a. Trade shares & attention in a cryptokitty
b. Trade shares & attention in engineering plans for a fusion reactor
c. Trade shares & attention in pharmaceutical molecules
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(Billy Rennekamp, 2018) https://medium.com/@billyrennekamp/re-fungible-token-rft-297003592769
23. TCR enabled Rewards (Arcade Bazar)
1. TCR enabled rewards (Simon DLR)
a. Alice deposits ETH to buy tokens along the bonding curve
b. Curve is linked to a TCR that maintains a list of eligible contributors
c. Bob is a beneficiary and EARNS 0.1 token when Alice BUYS 1 token
d. Bob can keep the token or sell it back into the contract to claim ETH
2. Beneficiaries are set by the TCR and are entities that support the asset
(developers, contributors, hosters)
3. Beneficiaries need to prove to be useful and reputable to earn rewards
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(De La Rouviere, 2018)
https://medium.com/@simondlr/the-arcade-bazaar-continuous-multi-party-tokenized-funding-without-central-issuance-2cba
c86ab5c
24. Bonded Token Sales
1. Launch a token bonding curve with the aim to raise 1000 ETH for 1m tokens
2. Creator retains 100,000 tokens (10%) upon launch
3. As more people buy in the creator can sell into the curve to get funding at the
risk of losing out on later rewards. This incentivizes delivery and #buidl
4. Once the funding goal is reached the token bonding contract closes
5. The creator receives 1000ETH and is left with his launch tokens (10% - X%)
6. Creates early liquidity, market making and more security for investors
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25. Deeper Nested Bonding Curves
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1. Alice creates a bonding curve backed by ETH issuing A(ETH) tokens
2. Bob creates a derivative bonding curve backed by A(ETH) tokens for B tokens
3. Carla creates a derivative bonding curve backed by B(A) tokens for C tokens
Compounded risk determined by:
a. Reserve ratio backing the initial token
b. Nesting ratio
(Slavas, 2018)
https://blog.relevant.community/how-to-make-bonding-curves-for-continuous-token-models-3784653f8b17
26. Key Challenges
1. Free-riders?
2. Curve governance?
3. Dynamic curvature?
4. Talent?
a. Economists
b. Mathematicians
c. Statisticians and data scientists
d. Programmers
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Such math
Much complex