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Decentralized Finance: On Blockchain- and
Smart Contract-Based Financial Markets
By Fabian Schär
1 INTRODUCTION
Decentralized nance (DeFi) is a blockchain-based nancial infrastructure that has
recently gained a lot of traction. e term generally refers to an open, permissionless, and
highly interoperable protocol stack built on public smart contract platforms, such as the
Ethereum blockchain (see Buterin, 2013). It replicates existing nancial services in a more
open and transparent way. In particular, DeFi does not rely on intermediaries and centralized
institutions. Instead, it is based on open protocols and decentralized applications (DApps).
Agreements are enforced by code, transactions are executed in a secure and veriable way,
and legitimate state changes persist on a public blockchain. us, this architecture can create
an immutable and highly interoperable nancial system with unprecedented transparency,
equal access rights, and little need for custodians, central clearing houses, or escrow services,
as most of these roles can be assumed by “smart contracts.”
e term decentralized nance (DeFi) refers to an alternative nancial infrastructure built on top of
the Ethereum blockchain. DeFi uses smart contracts to create protocols that replicate existing nancial
services in a more open, interoperable, and transparent way. is article highlights opportunities and
potential risks of the DeFi ecosystem. I propose a multi-layered framework to analyze the implicit
architecture and the various DeFi building blocks, including token standards, decentralized exchanges,
decentralized debt markets, blockchain derivatives, and on-chain asset management protocols. I con-
clude that DeFi still is a niche market with certain risks but that it also has interesting properties in
terms of eciency, transparency, accessibility, and composability. As such, DeFi may potentially
contribute to a more robust and transparent nancial infrastructure. (JEL G15, G23, E59)
Federal Reserve Bank of St. Louis Review, Second Quarter 2021, 103(2), pp. 153-74.
https://doi.org/10.20955/r.103.153-74
Fabian Schär is a professor for distributed ledger technologies and ntech at the University of Basel and the managing director of the Center for
Innovative Finance at the Faculty of Business and Economics, University of Basel. The author thanks two anonymous reviewers for their valuable
comments and especially Florian Bitterli, Raphael Knechtli, and Tobias Wagner for their support with data collection and visualization and
Emma Littlejohn and Amadeo Brands for proofreading.
© 2021, Federal Reserve Bank of St. Louis. The views expressed in this article are those of the author(s) and do not necessarily reect the views of
the Federal Reserve System, the Board of Governors, or the regional Federal Reserve Banks. Articles may be reprinted, reproduced, published,
distributed, displayed, and transmitted in their entirety if copyright notice, author name(s), and full citation are included. Abstracts, synopses,
and other derivative works may be made only with prior written permission of the Federal Reserve Bank of St. Louis.
Federal Reserve Bank of St. Louis REVIEW Second Quarter 2021 153
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154 Second Quarter 2021 Federal Reserve Bank of St. Louis REVIEW
DeFi already oers a wide variety of applications. For example, one can buy U.S. dollar
(USD)-pegged assets (so-called stablecoins) on decentralized exchanges, move these assets to
an equally decentralized lending platform to earn interest, and subsequently add the interest-
bearing instruments to a decentralized liquidity pool or an on-chain investment fund.
e backbone of all DeFi protocols and applications is smart contracts. Smart contracts
generally refer to small applications stored on a blockchain and executed in parallel by a large
set of validators. In the context of public blockchains, the network is designed so that each
participant can be involved in and verify the correct execution of any operation. As a result,
smart contracts are somewhat inecient compared with traditional centralized computing.
However, their advantage is a high level of security: Smart contracts will always be executed
as specied and allow anyone to verify the resulting state changes independently. When imple-
mented securely, smart contracts are highly transparent and minimize the risk of manipulation
and arbitrary intervention.
To understand the novelty of smart contracts, we rst must look at regular server-based
web applications. When a user interacts with such an application, they cannot observe the
application’s internal logic. Moreover, the user is not in control of the execution environment.
Either one (or both) could be manipulated. As a result, the user has to trust the application
service provider. Smart contracts mitigate both problems and ensure that an application runs
as expected. e contract code is stored on the underlying blockchain and can therefore be
publicly scrutinized. e contract’s behavior is deterministic, and function calls (in the form
of transactions) are processed by thousands of network participants in parallel, ensuring the
execution’s legitimacy. When the execution leads to state changes, for example, the change
of account balances, these changes are subject to the blockchain network’s consensus rules
and will be reected in and protected by the blockchain’s state tree.
Smart contracts have access to a rich instruction set and are therefore quite exible. Addi-
tionally, they can store cryptoassets and thereby assume the role of a custodian, with entirely
customizable criteria for how, when, and to whom these assets can be released. is allows
for a large variety of novel applications and ourishing ecosystems.
e original concept of a smart contract was coined by Szabo (1994). Szabo (1997) used
the example of a vending machine to describe the idea further and argued that many agree-
ments could be “embedded in the hardware and soware we deal with, in such a way as to make a
breach of contract expensive…for the breacher.” Buterin (2013) proposed a decentralized
blockchain-based smart contract platform to solve any trust issues regarding the execution
environment and to enable secure global states. Additionally, this platform allows the contracts
to interact with and build on top of each other (composability). e concept was further for-
malized by Wood (2015) and implemented under the name Ethereum. Although there are
many alternatives, Ethereum is the largest smart contract platform in terms of market cap,
available applications, and development activity.
DeFi still is a niche market with relatively low volumes—however, these numbers are
growing rapidly. e value of funds that are locked in DeFi-related smart contracts recently
crossed 10 billion USD. It is essential to understand that these are not transaction volume or
market cap numbers; the value refers to reserves locked in smart contracts for use in various
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Federal Reserve Bank of St. Louis REVIEW Second Quarter 2021 155
ways that will be explained in the course of this paper. Figure 1 shows the Ether (ETH, the
native cryptoasset of Ethereum) and USD values of the assets locked in DeFi applications.
e spectacular growth of these assets alongside some truly innovative protocols suggests
that DeFi may become relevant in a much broader context and has sparked interest among
policymakers, researchers, and nancial institutions. is article is targeted at individuals
from these organizations with an economics or legal background and serves as a survey and
an introduction to the topic. In particular, it identies opportunities and risks and should be
seen as a foundation for further research.
2 DeFi BUILDING BLOCKS
DeFi uses a multi-layered architecture. Every layer has a distinct purpose. e layers build
on each other and create an open and highly composable infrastructure that allows everyone
to build on, rehash, or use other parts of the stack. It is also crucial to understand that these
layers are hierarchical: ey are only as secure as the layers below. If, for example, the block-
chain in the settlement layer is compromised, all subsequent layers would not be secure. Simi-
larly, if we were to use a permissioned ledger as the foundation, any decentralization eorts
on subsequent layers would be ineective.
is section proposes a conceptual framework for analyzing these layers and studying
the token and the protocol layers in greater detail.1 It dierentiates between ve layers, as
shown in Figure 2: the settlement, asset, protocol, application, and aggregation layers.
1. e settlement layer (Layer 1) consists of the blockchain and its native protocol asset
(e.g., Bitcoin [BTC] on the Bitcoin blockchain and ETH on the Ethereum blockchain).
It allows the network to store ownership information securely and ensures that any
1.0 M
10.0 M
100.0 M
1,000.0 M
10,000.0 M
0.010 M
0.100 M
1.000 M
10.000 M
100.000 M
2018 2019 2020 2021
USD ETH
Total value locked in DeFi (ETH)
Total value locked in DeFi (USD)
Figure 1
Total Value Locked in DeFi Contracts (USD and ETH)
NOTE: M, million.
SOURCE: DeFi Pulse.
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156 Second Quarter 2021 Federal Reserve Bank of St. Louis REVIEW
state changes adhere to its ruleset. e blockchain can be seen as the foundation for
trustless execution and serves as a settlement and dispute resolution layer.
2. e asset layer (Layer 2) consists of all assets that are issued on top of the settlement
layer. is includes the native protocol asset as well as any additional assets that are
issued on this blockchain (usually referred to as tokens).
3. e protocol layer (Layer 3) provides standards for specic use cases such as decentral-
ized exchanges, debt markets, derivatives, and on-chain asset management. ese
standards are usually implemented as a set of smart contracts and can be accessed by
any user (or DeFi application). As such, these protocols are highly interoperable.
4. e application layer (Layer 4) creates user-oriented applications that connect to
individual protocols. e smart contract interaction is usually abstracted by a web
browser- based front end, making the protocols easier to use.
5. e aggregation layer (Layer 5) is an extension of the application layer. Aggregators
create user-centric platforms that connect to several applications and protocols. ey
usually provide tools to compare and rate services, allow users to perform otherwise
complex tasks by connecting to several protocols simultaneously, and combine relevant
information in a clear and concise manner.
Now that we understand the conceptual model, let us take a closer look at tokenization
and the protocol layer. Aer a short introduction to asset tokenization, we will investigate
decentralized exchange protocols, decentralized lending platforms, decentralized derivatives,
Aggregation layer Aggregator 1
Derivatives
(Ethereum) blockchain
Application layer
Protocol layer
Asset layer
Settlement layer
Aggregator 2 Aggregator 3
Exchange Lending Asset
management
Native protocol
asset (ETH)
Fungible
tokens: ERC-20
Non-fungible
tokens: ERC-721
…
…
Figure 2
The DeFi Stack
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Federal Reserve Bank of St. Louis REVIEW Second Quarter 2021 157
and on-chain asset management. is allows us to establish the foundation needed for our
analysis of the potential and risks of DeFi.2
2.1 Asset Tokenization
Public blockchains are databases that allow participants to establish a shared and immutable
record of ownership—a ledger. Usually, a ledger is used to track the native protocol asset of the
respective blockchain. However, when public blockchain technology became more popular,
so did the idea of making additional assets available on these ledgers. e process of adding
new assets to a blockchain is called tokenization, and the blockchain representation of the
asset is referred to as a token.
e general idea of tokenization is to make assets more accessible and transactions more
ecient. In particular, tokenized assets can be transferred easily and within seconds from and
to anyone in the world. ey can be used in many decentralized applications and stored within
smart contracts. As such, these tokens are an essential part of the DeFi ecosystem.
From a technological perspective, there are various ways in which public blockchain tokens
can be created (see Roth, Schär, and Schöpfer, 2019). However, most of these options can be
ignored, as the vast majority of tokens are issued on the Ethereum blockchain through a smart
contract template referred to as the ERC-20 token standard (Vogelsteller and Buterin, 2015).
ese tokens are interoperable and can be used in almost all DeFi applications. As of January
2021, there are over 350,000 ERC-20 token contracts deployed on Ethereum.3 Table 1 shows
the number of tokens listed on exchanges and the aggregated token market cap in USD per
Table 1
Listed Tokens and Total Token Market Cap by Blockchain Platform
Number Market capitalization
Platform Absolute Relative % Absolute (USD) Relative %
Ethereum 1,793 86.74 55,071,650,000 85.55
TRON 26 1.26 4,639,184,120 7.21
Binance Chain 83 4.02 2,297,032,000 3.57
Omni 3 0.15 1,407,629,950 2.19
NEO 25 1.21 160,789,200 0.25
XRP 1 0.05 156,223,800 0.20
Stellar 21 1.02 155,640,200 0.24
EOS 31 1.50 117,560,200 0.18
Qtum 8 0.39 71,898,580 0.11
RSK Smart Bitcoin 1 0.05 70,715,650 0.11
Others 75 3.63 227,652,769 0.35
SOURCE: coinmarketcap.com and tether.to as of September 3, 2020. Data preparation is in the style of Roth, Schär, and
Schöpfer (2019).
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158 Second Quarter 2021 Federal Reserve Bank of St. Louis REVIEW
blockchain. Almost 90 percent of all listed tokens are issued on the Ethereum blockchain.
e slight deviation in terms of market cap originates from the fact that a relatively large portion
of the USDT stablecoin has been issued on Omni.
From an economic perspective, I am more interested in the asset’s nature than in the
underlying technical standard used to implement the asset’s digital representation. e main
motivation for adding additional assets on-chain is the addition of a stablecoin. While it would
be possible to use the aforementioned protocol assets (BTC or ETH), many nancial contracts
require a low-volatility asset. Tokenization enables the creation of these assets.
However, one of the main concerns with tokenized assets is issuer risk. Native digital
tokens, such as BTC and ETH, are unproblematic in this regard. In contrast, when someone
introduces tokens with a promise, for example, interest payments, dividends, or the delivery
of a good or service, the corresponding token’s value will depend on this claim’s credibility.
If an issuer is unwilling or unable to deliver, the token may become worthless or trade at a
signicant discount. is logic also applies to stablecoins.
Generally speaking, there are three backing models for promise-based tokens: o-chain
collateral, on-chain collateral, and no collateral. O-chain collateral means that the underlying
assets are stored with an escrow service, for example, a commercial bank. On-chain collateral
means that the assets are locked on the blockchain, usually within a smart contract.4 When
there is no collateral, counterparty risk is at its highest. In this case, the promise is entirely
trust-based. Berentsen and Schär (2019) have analyzed the three categories in the context of
stablecoins.
On-chain collateral has several advantages. It is highly transparent, and claims can be
secured by smart contracts, allowing processes to be executed in a semi-automatic way. A
disadvantage of on-chain collateral is that this collateral is usually held in a native protocol
asset (or a derivative thereof) and, therefore, will experience price uctuations. Take the
example of the Dai stablecoin, which mainly uses ETH as its on-chain collateral to create a
decentralized and trustless Dai token pegged to the value of 1 USD. Since there is no native
USD-pegged token on Ethereum, Dai tokens must be backed by another asset. Whenever any-
one wants to issue new Dai tokens, they rst need to lock enough ETH as underlying collateral
in a smart contract provided by the Maker Protocol. Since the USD/ETH exchange rate is not
xed, there is a need for over-collateralization. If the value of the underlying ETH collateral
at any point falls below the minimum threshold of 150 percent of the outstanding Dai value,
the smart contract will auction o the collateral to cancel the debt in Dai.
Figure 3 shows some key metrics of the Dai stablecoin, including price, total Dai in circula-
tion, and the stability fee, that is, the interest rate that has to be paid by anyone who is creating
new Dai (see Section 2.3).
ere are also several examples of o-chain collateralized stablecoins. e most popular
ones are USDT and USDC, both USD-backed stablecoins. ey are both available as ERC-20
tokens on the Ethereum blockchain. DGX is an ERC-20-based stablecoin backed by gold, and
WBTC is a tokenized version of Bitcoin, making Bitcoin available on the Ethereum blockchain.
O-chain collateralized tokens can mitigate exchange rate risk, as the collateral may be equiva-
lent to the tokenized claim (e.g., USD claim, backed by real USD). However, o-chain collater-
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Federal Reserve Bank of St. Louis REVIEW Second Quarter 2021 159
alized tokens introduce counterparty risk and external dependencies. Tokens that use o-chain
collateral require regular audits and precautionary measures to ensure that the underlying
collateral is available at all times. is process is costly and, in many cases, not entirely trans-
parent for the token holders.
While I am unaware of any functional designs for unbacked stablecoins, that is, stablecoins
that do not use any form of collateral to maintain the peg, several organizations are working
on that idea. Note that rebase tokens such as Ampleforth or YAM do not qualify as stablecoins.
ey only provide a stable unit of account but still expose the holder to volatility in the form
of a dynamic token quantity.
0.95
1.00
1.05
2018 2019 2020
USD
SAI/Dai price weighted by dominance
0 M
100 M
200 M
300 M
400 M
500 M
2018 2019 2020
Token supply
Dai supply with DAI in DSR
0
5
10
15
20
2018 2019 2020
Fee (percent)
MCD WETH stability fee
SCD PETH stability fee
SAI supply
Total supply
Figure 3
Dai Stablecoin Key Metrics
NOTE: M, million; SAI, (discontinued) single collateral stablecoin; DSR, Dai savings rate; MCD, multi-collateral Dai stablecoin backed by ETH; S
CD, single collateral Dai stablecoin backed by ETH; MCD WETH stability fee, MCD stablecoin interest rate in ETH; SCD PETH stability fee, SCD
stablecoin interest rate in ETH.
SOURCE: DeFi Pulse and CoinMarketCap.
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160 Second Quarter 2021 Federal Reserve Bank of St. Louis REVIEW
Although stablecoins serve a vital role in the DeFi ecosystem, it would not do justice to
the subject of tokenization to limit the discussion to these assets. ere are all kinds of tokens
that serve a variety of purposes, including governance tokens for decentralized autonomous
organizations (DAO), tokens that allow the holder to perform specic actions in a smart con-
tract, tokens that resemble shares or bonds, and even synthetic tokens that can track the price
of any real-world asset.
Another distinct category are so-called non-fungible tokens (NFTs). NFTs are tokens that
represent unique assets, that is, collectibles. ey can either be the digital representation of a
physical object such as a piece of art, making them subject to the usual counterparty risk, or a
digitally native unit of value with unique characteristics. In any case, the token’s non-fungibility
attributes ensure that the ownership of each asset can be individually tracked and the asset
precisely identied. NFTs usually are built on the ERC-721 token standard (Entriken et al.,
2018).
e following sections discuss the protocol layer and examine how tokens can be traded
using decentralized exchanges (Section 2.2), how they can be used as collateral for loans
(Section 2.3) and to create decentralized derivatives (Section 2.4), and how they can be included
in on-chain investment funds (Section 2.5).
2.2 Decentralized Exchange Protocols
As of September 2020, there are over 7,092 cryptoassets5 listed on exchanges. While most
of them are economically irrelevant and have a negligible market cap and trading volume,
there is a need for marketplaces where people can trade the more popular ones. is would
allow owners of such assets to rebalance their exposure according to their preferences and
risk proles and adjust portfolio allocations.
In most cases, cryptoasset trades are conducted through centralized exchanges. Centralized
exchanges are relatively ecient, but they have one severe problem. To be able to trade on a
centralized exchange, traders must rst deposit assets with the exchange. ey thereby forfeit
direct access to their assets and have to trust the exchange operator. Dishonest or unprofessional
exchange operators may conscate or lose assets. Moreover, centralized exchanges create a
single point of attack and face the constant threat of becoming the target of malicious third
parties. e relatively low regulatory scrutiny intensies both problems and the immense
scaling eorts many of these exchanges had to go through within a short time. Accordingly,
it is no surprise that some centralized cryptoasset exchanges have lost customer funds.
Decentralized exchange protocols try to mitigate these issues by removing the trust require-
ment. Users no longer must deposit their funds with a centralized exchange. Instead, they
remain in exclusive control of their assets until the trade is executed. Trade execution happens
atomically through a smart contract, meaning that both sides of the trade are performed in one
indivisible transaction, mitigating the counterparty credit risk. Depending on the exact imple-
mentation, the smart contract may assume additional roles, eectively making many interme-
diaries such as escrow services and central counterparty clearing houses (CCPs) obsolete.
Early decentralized exchanges such as EtherDelta have been set up as walled gardens with
no interaction between the various implementations. e exchanges had no shared liquidity,
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Federal Reserve Bank of St. Louis REVIEW Second Quarter 2021 161
leading to relatively low transaction volumes and large bid/ask spreads. High network fees,
as well as cumbersome and slow processes to move funds between these decentralized
exchanges, have rendered supposed arbitrage opportunities useless.
More recently, there has been a move toward open exchange protocols. ese projects
try to streamline the architecture of decentralized exchanges by providing standards on how
asset exchange can be conducted and allowing any exchange built on top of the protocol to
use shared liquidity pools and other protocol features. However, most importantly, other DeFi
protocols can use these marketplaces and exchange or liquidate tokens when needed.
In the following subsections, I compare various types of decentralized exchange protocols,
some of which are not exchanges in the narrow sense but have been included in the analysis,
as they serve the same purpose. e results are summarized in Table 2.
Decentralized Order Book Exchanges. Decentralized order book exchanges can be imple-
mented in a variety of ways. ey all use smart contracts for transaction settlement, but they
dier signicantly in how the order books are hosted. One has to distinguish between
on-chain and o-chain order books.
On-chain order books have the advantage of being entirely decentralized. Every order is
stored within the smart contract. As such, there is no need for additional infrastructure or
third-party hosts. e disadvantage of this approach is that every action requires a blockchain
transaction. erefore, it is a costly and slow process for which even the declaration of the
intent to trade results in network fees. Considering that volatile markets will require frequent
order cancellations, this disadvantage becomes even more costly.
For this reason, many decentralized exchange protocols rely on o-chain order books and
only use the blockchain as a settlement layer. O-chain order books are hosted and updated
by centralized third parties, usually referred to as relayers. ey provide takers with the infor-
mation they need to select an order they would like to match. While this approach indeed
introduces some centralized components and dependencies to the system, the relayers’ role
is limited. Relayers are never in control of the funds and neither match nor execute the orders.
Table 2
Most Popular Decentralized Exchange Protocols
Protocol name Protocol type Price discovery
0x Exchange O-chain order books
(Air)Swap P2P / OTC P2P negotiation
Bancor CFMM Smart contract
Balancer CFMM Smart contract
Curve CFMM Smart contract
Kyber Network Reserve aggregator Proposal by maker
UniSwap CFMM Smart contract
NOTE: CFMM, constant function market maker.
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162 Second Quarter 2021 Federal Reserve Bank of St. Louis REVIEW
ey simply provide ordered lists with quotes and may charge a fee for that service. e
openness of the protocol ensures that there is competition among the relayers and mitigates
potential dependencies.
e dominant protocol that uses this approach is called 0x (Warren and Bandeali, 2017).
e protocol uses a three-step process for trades. First, the maker sends a pre-signed order to
the relayer for inclusion in the order book. Second, a potential taker queries the relayer and
selects one of the orders. ird, the taker signs and submits the order to the smart contract,
triggering the atomic exchange of the cryptoassets.
Constant Function Market Maker. A constant function market maker (CFMM) is a smart
contract-liquidity pool that holds (at least) two cryptoassets in reserve and allows anyone to
deposit tokens of one type and thereby to withdraw tokens of the other type. To determine the
exchange rate, smart contract-based liquidity pools use variations of the constant product
model, where the relative price is a function of the smart contract’s token reserve ratio. e
earliest implementation I am aware of was proposed by Hertzog, Benartzi, and Benartzi (2017).
Adams (2018) has simplied the model, and Zhang, Chen, and Park (2018) provide a formal
proof of the concept. Martinelli and Mushegian (2019) generalized the concept for cases with
more than two tokens and dynamic token weights. Egorov (2019) optimized the idea for
stablecoin swaps.
In its simplest form, the constant product model can be expressed as xy = k, where x and
y correspond to the smart contract’s token reserves and k is a constant. Considering that this
equation must hold, when someone executes a trade, we get (x + Δx) . (y + Δy) = k. It can then
be easily shown that Δy = (k/(x + Δx)) – y. Consequently, Δy will assume negative values for any
Δx > 0. In fact, any exchange corresponds to a move on a convex token reserve curve, which
is shown in Figure 4A. A liquidity pool using this model cannot be depleted, as tokens will
y-tokens y-tokens
x-tokens x-tokens
y y
k k
kΔ
y + Δ(y)
y + Δ(y)
x xx + Δ(x)x + Δ(x)
A. B.
Figure 4
Visualization of Liquidity Pool Token Reserves in a Constant Product Model
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Federal Reserve Bank of St. Louis REVIEW Second Quarter 2021 163
get more expensive with lower reserves. When the token supply of either one of the two tokens
approaches zero, its relative price rises innitely as a result.
It is important to point out that smart contract-based liquidity pools are not reliant on
external price feeds (so-called oracles). Whenever the market price of an asset shis, anyone
can use the arbitrage opportunity and trade tokens with the smart contract until the liquidity
pool price converges to the current market price. e implicit bid/ask spread of the constant
product model (plus a small trading fee) may lead to the accumulation of additional funds.
Anyone who provides liquidity to the pool receives pool share tokens that allow them to partici-
pate in this accumulation and to redeem these tokens for their share of a potentially growing
liquidity pool. Liquidity provision results in a growing k and is visualized in Figure 4B.
Prominent examples of smart contract-based liquidity pool protocols are UniSwap,
Balancer, Curve, and Bancor.
Smart Contract-Based Reserve Aggregation. Another approach is to consolidate liquidity
reserves through a smart contract that allows large liquidity providers to connect and advertise
prices for specic trade pairs. A user who wants to exchange token x for token y may send a
trade request to the smart contract. e smart contract will compare prices from all liquidity
providers, accept the best oer on behalf of the user, and execute the trade. It acts as a gateway
between users and liquidity providers, ensuring best execution and atomic settlement.
In contrast to smart contract-based liquidity pools, with smart contract-based reserve
aggregation, prices are not determined within the smart contract. Instead, prices are set by
the liquidity providers. is approach works ne if there is a relatively broad base of liquidity
providers. However, if there is limited or no competition for a given trade pair, the approach
may result in collusion risks or even monopolistic price setting. As a countermeasure, reserve
aggregation protocols usually have some (centralized) control mechanisms, such as maximum
prices or a minimum number of liquidity providers. In some cases, liquidity providers may
only participate aer a background check, including KYC (know your customer) verication.
e best-known implementation of this concept is the Kyber Network (Luu and Velner,
2017), which serves as a backbone protocol for a large variety of DeFi applications.
Peer-to-Peer Protocols. An alternative to classic exchange or liquidity pool models are peer-
to-peer (P2P) protocols, also called over-the-counter (OTC) protocols. ey mostly rely on a
two-step approach, where participants can query the network for counterparties who would
like to trade a given pair of cryptoassets and then negotiate the exchange rate bilaterally. Once
the two parties agree on a price, the trade is executed on-chain via a smart contract. In contrast
to other protocols, oers can be accepted exclusively by the parties who have been involved
in the negotiation. In particular, it is not possible for a third party to front-run someone
accepting an oer by observing the pool of unconrmed transactions (mempool).
To make things more ecient, the process is usually automated. Additionally, one can
use o-chain indexers for peer discovery. ese indexers assume the role of a directory in
which people can advertise their intent to make a specic trade. Note that these indexers only
serve to establish a connection. Prices are still negotiated P2P.
AirSwap is the most popular implementation of a decentralized P2P protocol. It was
proposed by Oved and Mosites (2017).
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164 Second Quarter 2021 Federal Reserve Bank of St. Louis REVIEW
2.3 Decentralized Lending Platforms
Loans are an essential part of the DeFi ecosystem. ere are a large variety of protocols
that allow people to lend and borrow cryptoassets. Decentralized loan platforms are unique
in the sense that they require neither the borrower nor the lender to identify themselves.
Everyone has access to the platform and can potentially borrow money or provide liquidity
to earn interest. As such, DeFi loans are completely permissionless and not reliant on trusted
relationships.
To protect the lender and stop the borrower from running away with the funds, there are
two distinct approaches: First, credit can be provided under the condition that the loan must
be repaid atomically, meaning that the borrower receives the funds, uses, and repays them—
all within the same blockchain transaction. Suppose the borrower has not returned the funds
(plus interest) at the end of the transaction’s execution cycle. In this case, the transaction will
be invalid and any of its results (including the loan itself) reverted. ese so-called ash loans
(Wol, 2018; Boado, 2020) are an exciting but still highly experimental application. While ash
loans can only be employed in applications that are settled atomically and entirely on-chain,
they are an ecient new instrument for arbitrage and portfolio restructuring. As such, they
are on track to become an essential part of DeFi lending.
Second, loans can be fully secured with collateral. e collateral is locked in a smart con-
tract and only released once the debt is repaid. Collateralized loan platforms exist in three
variations: Collateralized debt positions, pooled collateralized debt markets, and P2P collateral-
ized debt markets. Collateralized debt positions are loans that use newly created tokens, while
debt markets use existing tokens and require a match between a borrowing and a lending
party. e three variations are discussed below.
Collateralized Debt Positions. Some DeFi applications allow users to create collateralized
debt positions and thereby issue new tokens that are backed by the collateral. To be able to
create these tokens, the person must lock cryptoassets in a smart contract. e number of
tokens that can be created depends on the target price of the tokens generated, the value of
the cryptoassets that are being used as collateral, and the target collateralization ratio. e
newly created tokens are essentially fully collateralized loans that do not require a counter-
party and allow the user to get a liquid asset while maintaining market exposure through the
collateral. e loan can be used for consumption, allowing the person to overcome a temporary
liquidity squeeze or to acquire additional cryptoassets for leveraged exposure.
To illustrate the concept, let us use the example of MakerDAO, a decentralized protocol
that is used to issue the USD-pegged Dai stablecoin. First, the user deposits ETH in a smart
contract classied as a collateralized debt position (CDP) (or vault). Subsequently, they
call a contract function to create and withdraw a certain number of Dai and thereby lock the
collateral. is process currently requires a minimum collateralization ratio of 150 percent,
meaning that for any 100 USD of ETH locked up in the contract, the user can create at most
66.66 Dai.6
Any outstanding Dai is subject to a stability fee, which in theory should correspond to
the Dai debt market’s maximum interest rate. is rate is set by the community, namely the
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MKR token holders. MKR is the governance token for the MakerDAO project. As shown in
Figure 3, the stability fee has been uctuating wildly between 0 and 20 percent.
To close a CDP, the owner must send the outstanding Dai plus the accumulated interest
to the contract. e smart contract will allow the owner to withdraw their collateral once the
debt is repaid. If the borrower fails to repay the debt, or if the collateral’s value falls below the
150 percent threshold, where the full collateralization of the loan is at risk, the smart contract
will start to liquidate the collateral at a potentially discounted rate.
Interest payments and liquidation fees are partially used to “burn” MKR, thereby decreas-
ing the total MKR supply. In exchange, MKR holders assume the residual risk of extreme nega-
tive ETH price shocks, which may lead to a situation in which the collateral is insucient to
maintain the USD peg. In this case, new MKR will be created and sold at a discounted rate.
As such, MKR holders have skin in the game, and it should be in their best interest to main-
tain a healthy system.
It is important to mention that the MakerDAO system is much more complicated than
what is described here. Although the system is mostly decentralized, it is reliant on price ora-
cles, which introduce some dependencies, as discussed in Section 3.2.
MakerDAO has recently switched to a multi-collateral system, with the goal to make the
protocol more scalable by allowing a variety of cryptoassets to be used as collateral.
Collateralized Debt Markets. Instead of creating new tokens, it is also possible to borrow
existing cryptoassets from someone else. For obvious reasons, this approach requires a coun-
terparty with opposing preferences. In other words: For someone to be able to borrow ETH,
there must be another person willing to lend ETH. To mitigate counterparty risk and protect
the lender, loans must be fully collateralized, and the collateral is locked in a smart contract—
just as in our previous example.
Matching lenders with borrowers can be done in a variety of ways. e broad categories
are P2P and pooled matching. P2P matching means that the person who is providing the
liquidity lends the cryptoassets to specic borrowers. Consequently, the lender will only start
to earn interest once there is a match. e advantage of this approach is that the parties agree
on a time period and operate with xed interest rates.
Pooled loans use variable interest rates that are subject to supply and demand. e funds
of all borrowers are aggregated in a single, smart contract-based lending pool, and lenders start
to earn interest right when they deposit their funds in the pool. However, the interest rates
are a function of the pool’s utilization rate. When liquidity is readily available, loans will be
cheap. When it is in great demand, loans will become more expensive. Lending pools have
the additional advantage that they can perform maturity and size transformation while main-
taining relatively high liquidity for the individual lender.
ere is a large variety of lending protocols. Some of the most popular ones are Aave
(Boado, 2020), Compound (Leshner and Hayes, 2019), and dYdX (Juliano, 2017). Figure 5
shows the asset-weighted borrowing and lending rates for Dai and ETH. For Dai, the gure
also includes the MakerDAO stability fee, which should always be the highest rate in the system.
Surprisingly, this is not always the case, meaning that some people have paid a price premium
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in the secondary market. As of September 2020, Dai accounts for almost 75 percent of all
loans in the DeFi ecosystem.
2.4 Decentralized Derivatives
Decentralized derivatives are tokens that derive their value from an underlying asset’s
performance, the outcome of an event, or the development of any other observable variable.
ey usually require an oracle to track these variables and therefore introduce some depen-
dencies and centralized components. e dependencies can be reduced when the derivative
contract uses multiple independent data sources.
We dierentiate between asset-based and event-based derivative tokens. We call a deriv-
ative token asset-based when its price is a function of an underlying asset’s performance. We
call a derivative event-based when its price is a function of any observable variable that is not
the performance of an asset. Both categories will be discussed in the following sections.
Asset-Based Derivative Tokens. Asset-based derivative tokens are an extension of the CDP
model described in Section 2.3. Instead of limiting the issuance to USD-pegged stablecoins,
the locked collateral can be used to issue synthetic tokens that follow the price movements of
a variety of assets. Examples include tokenized versions of stocks, precious metals, and alter-
native cryptoassets. e higher the underlying volatility, the larger the risk of falling below a
given collateralization ratio.
A popular derivative token platform is called Synthetix (Brooks et al., 2018). It is imple-
mented so that the total debt pool of all participants increases or decreases depending on the
aggregate price of all outstanding synthetic assets. is ensures that tokens with the same
underlying assets remain fungible; that is, redemption does not depend on the issuer. e
ip side of this design is that users assume additional risk when they mint assets, as their debt
position will also be aected by everyone else’s asset allocation.
0
10
20
Jan 2019 Jul 2019 Jan 2020 Jul 2020
Interest rate (percent) Maker stability fee
Weighted borrowing rate
Weighted lending rate
Figure 5
Weighted Dai Collateralized Debt Market Rates and the MakerDAO Stability Fee
SOURCE: DeFi Pulse.
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Federal Reserve Bank of St. Louis REVIEW Second Quarter 2021 167
A particular case of asset-based derivative tokens are inverse tokens. Here, the price is
determined by an inverse function of the underlying assets’ performance within a given price
range. ese inverse tokens allow users to get short exposure to cryptoassets.
Event-Based Derivative Tokens. Event-based derivative tokens can be based on any objec-
tively observable variable with a known set of potential outcomes, a specied observation time,
and a resolution source.7 Anyone can buy a full set of sub-tokens for a given event by locking
1 ETH in a smart contract. A complete set of sub-tokens consists of 1 sub-token for each
potential outcome. ese sub-tokens can be traded individually. When the market resolves,
the smart contract’s cryptoassets will be split among the sub-token owners of the winning
outcome. In the absence of market distortions, each sub-token’s ETH price should, therefore,
correspond to the probability of the underlying outcome.
Under certain circumstances, these prediction markets may serve as decentralized oracles
for the likelihood of a future outcome. However, market resolution (and therefore the price)
greatly depends on the trustworthiness of the resolution source. As such, event-based deriva-
tive tokens introduce external dependencies and may be unilaterally inuenced by a malicious
reporter. Potential attack vectors include awed or misleading question specications, incom-
plete outcome sets that may render the event unresolvable, and the choice of unreliable or
fraudulent resolution sources.
e most popular implementation is called Augur (Peterson et al., 2019). It uses a multi-
stage resolution and disputing process that should minimize the dependency on a single
reporting source as much as possible. If the token holders do not agree with the designated
reporter, they may start a dispute, which should eventually lead to the correct outcome.
2.5 On-Chain Asset Management
Just like traditional investment funds, on-chain funds are mainly used for portfolio
diversication. ey allow users to invest in a basket of cryptoassets and employ a variety of
strategies without having to handle the tokens individually. In contrast to traditional funds,
the on-chain variant does not require a custodian. Instead, the cryptoassets are locked up in
a smart contract. e investors never lose control over their funds, can withdraw or liquidate
them, and can observe the smart contracts’ token balances at any point in time.
e smart contracts are set up in such a way that they follow a variety of simple strategies,
including semi-automatic rebalancing of portfolio weights and trend trading, using moving
averages. Alternatively, one or multiple fund managers can be selected to manage the fund
actively. In this case, the smart contract ensures that asset managers adhere to the predened
strategy and act in the investors’ best interest. In particular, asset managers are limited to
actions in accordance with the fund’s ruleset and the risk prole stipulated in the smart con-
tract. e smart contract can mitigate many forms of the principal-agent problem and incor-
porate regulatory requirements by enforcing them on-chain. As a result, on-chain asset
management may lead to lower fund setup and auditing costs.
Whenever someone invests in an on-chain fund, the corresponding smart contract issues
fund tokens and transfers them to the investor’s account. ese tokens represent partial
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ownership of the fund and allow token holders to redeem or liquidate their share of the assets.
For example, if an investor owns 1 percent of the fund tokens, this person would be entitled
to 1 percent of the locked cryptoassets. When the investor decides to close out the investment,
the fund tokens get burned, the underlying assets are sold on a decentralized exchange, and
the investor is compensated with the ETH-equivalent of their share of the basket.
ere are several implementations of on-chain fund protocols, including the Set Protocol
(Feng and Weickmann, 2019), Enzyme Finance (formerly Melon) (Trinkler and El Isa, 2017),
Yearn Vaults (Cronje, 2020), and Betoken (Liu and Palayer, 2018). All of these implementa-
tions are limited to ERC-20 tokens and Ether. Moreover, they heavily depend on price oracles
and third-party protocols, mainly for lending, trading, and the inclusion of low-volatility
reference assets such as the Dai or USDC stablecoins. Consequently, there are severe depen-
dencies, which will be discussed in Section 3.2.
Both Enzyme Finance and Set Protocol allow anyone to create new investment funds.
Enzyme Finance has a focus on building an infrastructure for decentralized funds, using
smart contract-based rulesets to ensure that fund managers stick to the funds’ strategies.
Trading restriction parameters such as maximum concentration, price tolerance, and the
maximum number of positions, as well as user and asset whitelists and blacklists, are enforced
by these smart contracts. e same is true for the fund’s fee schedule. Set Protocol is mainly
designed for semi-automated strategies with deterministic portfolio rebalancing triggered
by predened threshold values and timelocks. However, the protocol is also used for active
management. Betoken operates as a single fund of funds managed by a community of asset
managers through a meritocratic system. e more successful an individual fund manager is,
the greater their future inuence on allocating the collective resources. UniSwap’s liquidity
pool (see Section 2.2) also has some characteristics of an on-chain investment fund. e con-
stant product model creates the incentives for a semi-automatic rebalancing of portfolio
weights, while the trading fees generate passive income for the investors.
Yearn Vaults are collective investment pools designed to maximize yield for a given asset.
Strategies are quite diverse but usually involve several steps and active management. In many
cases, these actions would be too expensive (in terms of transaction fees) for smaller amounts.
Moreover, they require that the investor is vigilant and well-informed. Yearn Vaults mitigate
these issues by employing the knowledge of the masses and using collective action to split
network fees proportionally among all participants. However, the deep integration of the
protocol also introduces severe dependencies.
3 OPPORTUNITIES & RISKS
In this section, we analyze the opportunities and risks of the DeFi ecosystem. It lays the
foundation for the discussion in Section 4.
3.1 Opportunities
DeFi may increase the eciency, transparency, and accessibility of the nancial infrastruc-
ture. Moreover, the system’s composability allows anyone to combine multiple applications
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and protocols, thereby creating new and exciting services. We discuss these aspects in the
following subsections.
Eciency. While much of the traditional nancial system is trust based and dependent on
centralized institutions, DeFi replaces some of these trust requirements with smart contracts.
e contracts can assume the roles of custodians, escrow agents, and CCPs. For example, if
two parties want to exchange digital assets in the form of tokens, there is no need for guaran-
tees from a CCP. Instead, the two transactions can be settled atomically, meaning that either
both or neither of the transfers will be executed. is signicantly decreases counterparty
credit risk and makes nancial transactions much more ecient. Lower trust requirements
may come with the additional benet of reducing regulatory pressure and reducing the need
for third-party audits. Similar eciency gains are possible for almost every area of the nan-
cial infrastructure.
Additionally, token transfers are much faster than any of the transfers in the traditional
nancial system. Transfer speed and transaction throughput can be further increased with
Layer 2 solutions, such as sidechains or state- and payment-channel networks.
Transparency. DeFi applications are transparent. All transactions are publicly observable,
and the smart contract code can be analyzed on-chain. e observability and deterministic
execution allow—at least in theory—an unprecedented level of transparency.
Financial data are publicly available and may potentially be used by researchers and
users alike. In the case of a crisis, the availability of historical (and current) data is a vast
improvement over traditional nancial systems, where much of the information is scattered
across a large number of proprietary databases or not available at all. As such, transparency
of DeFi applications may allow for the mitigation of undesirable events before they arise and
help provide much faster understanding of their origin and potential consequences when
they emerge.
Accessibility. By default, DeFi protocols can be used by anyone. As such, DeFi may potentially
create a genuinely open and accessible nancial system. In particular, the infrastructure
requirements are relatively low and the risk of discrimination is almost inexistent due to the
lack of identities.
If regulation demands access restrictions, for example, for security tokens, such restric-
tions can be implemented in the token contracts without compromising the settlement layer’s
integrity and decentralization properties.
Composability. DeFi protocols are oen compared with Lego pieces. e shared settlement
layer allows these protocols and applications to interconnect. On-chain fund protocols can
make use of decentralized exchange protocols or achieve leveraged positions through lending
protocols.
Any two or more pieces can be integrated, forked, or rehashed to create something entirely
new. Anything that has been created before can be used by an individual or by other smart
contracts. is exibility allows for an ever-expanding range of possibilities and unprecedented
interest in open nancial engineering.
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3.2 Risks
DeFi also has certain risks, namely, smart contract execution risk, operational security,
and dependencies on other protocols and external data. We discuss these aspects in the fol-
lowing subsections.
Smart Contract Execution. While the deterministic and decentralized execution of smart
contracts does have its advantages, there is risk that something may go wrong. If there are
coding errors, these errors may potentially create vulnerabilities that allow an attacker to
drain the smart contract’s funds, cause chaos, or render the protocol unusable. Users have to
be aware that the protocol is only as secure as the smart contracts underlying it. Unfortunately,
the average user will not be able to read the contract code, let alone evaluate its security. While
audits, insurance services, and formal verication are partial solutions to this problem, some
degree of uncertainty remains.
Similar risks exist in contract execution. Most users do not understand the data payload
they are asked to sign as part of transactions and may be misled by a compromised front end.
Unfortunately, there seems to be an inherent trade-o between usability and security. For
example, some decentralized blockchain applications will ask for permissions to transfer an
innite number of tokens on behalf of the user—usually to make future transactions more
convenient and ecient. Such permission, however, puts the user’s funds at risk.
Operational Security. Many DeFi protocols and applications use admin keys. ese keys
allow a predened group of individuals (usually the project’s core team) to upgrade the con-
tracts and to perform emergency shutdowns. While it is understandable that some projects
want to implement these precautionary measures and remain somewhat exible, the existence
of these keys can be a potential problem. If the keyholders do not create or store their keys
securely, malicious third parties could get their hands on these keys and compromise the
smart contract. Alternatively, the core team members themselves may be malicious or cor-
rupted by signicant monetary incentives.
Most projects try to mitigate this risk with multisig and timelocks. Multisig requires
M-of-N keys to execute any of the smart contract’s admin functions, and timelocks specify
the earliest time at which a transaction can be (successfully) conrmed.
As an alternative, some projects rely on voting schemes, where the respective governance
tokens grant their owners the right to vote on the protocol’s future. However, in many cases,
the majority of governance tokens are held by a small group of people, eectively leading to
similar results as with admin keys. Some projects have tried to mitigate this concentration of
voting power by rewarding early adopters and users who fulll specic criteria, which range
from simple protocol usage to active participation in the voting process and third-party token
staking (yield farming). Nevertheless, even when a launch is perceived as being relatively
“fair,” the actual distribution oen remains highly concentrated.
Governance tokens may lead to undesirable consequences. In fact, a high concentration
of power may be even more problematic when these rights are tokenized. In the absence of
vesting periods, malicious founders can pull the rug by dumping their entire token holding on
a CFMM, causing a massive supply shock and undermining the project’s credibility. Moreover,
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Federal Reserve Bank of St. Louis REVIEW Second Quarter 2021 171
yield farming may lead to centralization creep by allowing an already well-established protocol
to assume a signicant portion of a relatively new protocol’s governance tokens. is may
create large meta protocols whose token holders essentially control a considerable portion of
the DeFi infrastructure.
Dependencies. As described in Section 3.1, some of the most promising features of the DeFi
ecosystem are its openness and composability. ese features allow various smart contracts
and decentralized blockchain applications to interact with each other and to oer new services
based on a combination of existing ones. On the ip side, these interactions introduce severe
dependencies. If there is an issue with one smart contract, it may potentially have wide-
reaching consequences for multiple applications across the entire DeFi ecosystem. Moreover,
problems with the Dai stablecoin or severe ETH price shocks may cause ripple eects through-
out the whole DeFi ecosystem.
e problem becomes apparent when illustrated by an example. Let us assume that a
person locks ETH as collateral in the MakerDAO contract to issue Dai stablecoins. Let us
further assume that the Dai stablecoins are locked in a compound lending smart contract to
issue interest-bearing derivative tokens, called cDai. e cDai tokens are subsequently moved
to the UniSwap ETH/cDai liquidity pool, along with some ETH, allowing the person to with-
draw UNI-cDai tokens representing a share of the liquidity pool. With every additional smart
contract, the potential risk of a bug increases. If any of the contracts in the sequence fail, the
UNI-cDai tokens could potentially become worthless. ese “token on top of a token on top
of a token” scenarios, which create wrapper tokens, can entangle projects in such a way that
theoretical transparency does not correspond to actual transparency.
External Data. Another point worth mentioning is the fact that many smart contracts are
reliant on external data. Whenever a smart contract depends on data that are not natively
available on-chain, the data must be provided by external data sources. ese so-called oracles
introduce dependencies and may, in some cases, lead to heavily centralized contract execution.
To mitigate this risk, many projects rely on decentralized oracle networks with a large variety
of data provision schemes.
Illicit Activity. A common concern among regulators is that cryptoassets may be used by
individuals who want to avoid records and monitoring. While the inherent transparency of
DeFi is a deterrent to this use case, the network’s pseudonymity may provide some privacy.
However, this may not necessarily be a bad thing, and the situation is more complicated than
it may seem at rst glance. On the one hand, pseudonymity can be abused by actors with dis-
honest intentions. On the other hand, privacy may be a desirable attribute for some legitimate
nancial applications. Correspondingly, regulators should act with great care, trying to nd
reasonable solutions that allow them to step in where necessary without stiing innovation.
Moreover, one has to be aware that regulating a decentralized network may not be feasible.
While it is questionable whether regulators can (or should) regulate a decentralized infra-
structure, there are two areas that deserve special attention, namely, at on- and o-ramps
and the decentralization theater.
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Fiat on- and o-ramps are the interface to the traditional nancial system. Whenever
people want to move assets from their bank account to the blockchain-based system or the
other way, they have to go through a nancial service provider. ese nancial service pro-
viders are regulated and may require background checks on the origin of the funds.
In a similar vein, it is important to dierentiate between legitimate decentralized protocols
and projects that only claim to be decentralized but are in fact under the exclusive control of
an organization or a few individuals. e former may provide exciting new possibilities and
remove some dependencies, while the latter may essentially introduce the worst of two worlds,
that is, de facto dependencies on a centralized operator with limited supervision. Keeping
this in mind, regulators should watch closely and analyze carefully if a given DeFi protocol is
indeed decentralized or if the DeFi label is just for show in an attempt to get around regulation.
Scalability. Blockchains face the ultimate trade-o between decentralization, security, and
scalability. While the Ethereum blockchain is generally regarded as relatively decentralized
and secure, it struggles to keep up with the great demand for block space. Escalating gas prices
(transaction fees) and long conrmation times adversely aect the DeFi ecosystem and favor
wealthy individuals who can conduct large trades.
Potential solutions to this problem include base-layer sharding, as well as various Layer 2
solutions, such as state channels, ZK (zero knowledge) rollups, and optimistic rollups. How-
ever, in many cases, scalability eorts weaken composability and general transaction atomicity—
two of DeFi’s most prominent features. On the other hand, moving DeFi to a more centralized
base layer does not seem to be a reasonable approach either, as it would essentially undermine
its main value proposition. us, it remains to be seen if a truly decentralized blockchain can
keep up with the demand and provide the foundation for an open, transparent, and immutable
nancial infrastructure.
4 CONCLUSION
DeFi oers exciting opportunities and has the potential to create a truly open, transparent,
and immutable nancial infrastructure. Because DeFi consists of numerous highly interopera-
ble protocols and applications, every individual can verify all transactions and data is readily
available for users and researchers to analyze.
DeFi has unleashed a wave of innovation. On the one hand, developers are using smart
contracts and the decentralized settlement layer to create trustless versions of traditional nan-
cial instruments. On the other hand, they are creating entirely new nancial instruments that
could not be realized without the underlying public blockchain. Atomic swaps, autonomous
liquidity pools, decentralized stablecoins, and ash loans are just a few of many examples that
show the great potential of this ecosystem.
While this technology has great potential, there are certain risks involved. Smart contracts
can have security issues that may allow for unintended usage, and scalability issues limit the
number of users. Moreover, the term “decentralized” is deceptive in some cases. Many pro-
tocols and applications use external data sources and special admin keys to manage the system,
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Federal Reserve Bank of St. Louis REVIEW Second Quarter 2021 173
conduct smart contract upgrades, or even perform emergency shutdowns. While this does
not necessarily constitute a problem, users should be aware that, in many cases, there is much
trust involved. However, if these issues can be solved, DeFi may lead to a paradigm shi in
the nancial industry and potentially contribute toward a more robust, open, and transparent
nancial infrastructure. n
NOTES
1 An alternative approach can be found here:
https://medium.com/pov-crypto/ethereum-the-digital-nance-stack-4ba988c6c14b.
2 For readers who wish to understand the settlement layer better and want to read a general introduction to block-
chain and cryptocurrencies, see Berentsen and Schär (2018).
3 Etherscan (2021).
4 UTXO-based blockchain implementations such as Bitcoin allow sophisticated unlocking conditions through their
scripting language. Although most people would not call these locking scripts a smart contract, they achieve
similar goals in terms of the blockchain’s custodial capabilities.
5 CoinMarketCap (2019).
6 In practice, the collateralization must be much larger, as any credit position with collateralization below 150 per-
cent is liquidated.
7 For example, such a token was created in regard to the outcome of the recent U.S. presidential election.
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