Blockchain Midterm 2

Defi Characteristics

Smart Contract Foundation - services executed by transparent auditable code rather than centralized institutions

Open Access - anyone can access through interest

Always Available - protocols operate continuously (unlike regular banks with banking hours, holidays, or geographic restrictions)

FTX

Collapsed in November 2022

$8 billion lost

opaque accounting and centralized control

users locked out

Defi Protocols

all transactions visible on-chain

users maintain full control over assets

zero downtime or fund freezes

cryptographic certainty instead of institutional trust

all transactions, collateral ratios, and protocol balances are publicly auditable in real-time

can only lend to anon using only on-chain verifiable assets

Centralized Exchanges

function as black boxes

users must trust management with custody of funds

Composability

all DeFi protocols can be combined to create sophiscated financial products

permissionless composability, so innovation does not require approval from any central authority

Main Protocols: stablecoins, AMMs, lending, perpetuals, governance

Example: acquire stablecoins, supply stablecoins to lending pool and receive interest-bearing tokens, use tokens as collateral to borrow and trade on Uniswap or GMX (tokens still earn yield)

Volatility Problem

native cryptos (ETH, BTC) experience dramatic price swings

unsuitable for predictable loan payments, merchant payment processing, denominating financial contracts (stating what currency to use in contract)

Stablecoin Solution

digital cash pegged to fiat currencies (typically USD) or crypto or algorithm

price anchor (stable reference for defi protocols)

safe haven (preserves value during crypto crashes)

programmable (smart contracts and blockchain capabilities)

enables other DeFi primitives

Fiat-Backed

backed by cash (typically USD)  or short term U.S. treasury securities (loans to government) held in traditional bank accounts

1:1 to fiat

subject to off-chain aduitors

examples: USDC (Circle), USDT

risk: requires trusting centralized entity with reserves, issuers can freeze addresses and block transactions, subject to government intervention and compliance requirements

if price below $1, buy cheap tokens and redeem for USDC, demand increases → price rises

if price above $1, mint new tokens and sell them, supply increases → price drops

Crypto-Collaterized

over-collateralized with crypto assets

up to 150% ratio ($150 ETH backs $100 DAI)

if collateral value drops below threshold, automatically liquidate collateral

user returns stablecoin plus stability fee to reclaim collateral

all data on-chain

example: DAI (MakerDAO)

if above $1, mint more DAI by opening more vaults or swap USDC for DAI to increase supply

if below $1, repay loans (burn DAI) and retrieve collateral or swap DAI for USDC to reduce supply

pros: more transparent, more decentralized, and more censorship resisitant than fiat-backed

cons: more complex than fiat-backed, capital-inefficient, code vulnerabilities could drain collateral, heavy reliance on USDC for Peg Stability Module (PSM) so not that decentralized, liquidation can cascade

Algorithmic

incentive mechanism adjusts supply based on demand

mint/burn relationship with governance token (LUNA for UST)

example: UST (Terra) → failed

risk: death spiral if market confidence breaks (mass withdrawal)

if above $1, burn token to mint stablecoin

if below $1, burn stablecoin to mint token

Traditional Order Books

requires matching buyers to sellers

constant order placement and cancellation

high frequency updates

high gas costs

AMM Solution

liquidity always available

no need to match orders

algorithmic pricing

single transaction

passive liquid provision

AMMs

pool holds reserves of two tokens

liquidity providers deposit both in proportion to current price

invariant ensures some formula of reserves stays constant (sum, product, etc.)

price adjusts to maintain constant product

always available, no operator needed

example: Uniswap (general purpose), Balancer (multi-asset pools), Curve (stablecoin-optimized)

Over-Collateralized Lending

lock up collateral more than loan value

if collateral price drops, collateral ratio drops (less for collateral)

borrow to maintain ETH exposure while accessing liquidity, anonymous, tax efficient

global, permissionless access to liquidity without personal info or delays

automatic liquidation if collateral drops below threshold

less capital efficient than traditional loans

Lending in Action

lenders deposit liquidity into protocol and receive interest-bearing tokens

lock collateral and borrow against it (interest goes to lenders)

interest rates adjust based on utilization (high demand leads to higher rates which lead to more lenders)

borrowers repay principal plus interest to unlock collateral

Perps

no expiration (can hold positions indefinitely)

long positions (rise) and short positions (fall)

periodic payments between longs and short to keep price anchored to spot price

example platforms: dYdX (order book-based), GMX (pool-based leverage), Hyperliquid (high-performance L1=low latency)

Purpose of Perps

offset spot holdings with short positions

express market views with leverage

arbitrage funding rates and spot prices (exploit difference in price)

gain exposure without holding underlying assets

Governance via DAOs

create proposals for protocol changes (fee adjustments, parameter updates, treasury spending, or code upgrades)

governance token holders votes on-chain (voting power proportional to token holdings)

changes execute automatically when passed

maximal transparency

Maximal Extractable Value (MEV)

reorder, insert, or censor transactions to extract additional profit

example: user buys ETH, bot detects pending transaction, bot buys before transaction, bot sells post transaction, bot profits from price movement

DeFi Stack

stablecoins, AMMs, lending, perps, governance

each entry builds on primitives before it

Peg Stability Module (PSM)

DAI price stabilized through 1:1 swaps with USDC

DAI also backed by U.S. treasury bonds

45% backed by USDC, 30% backed by bonds, 25% backed by crypto

Hybrid Approaches for Stablecoin

backed by real-world assets and crypto collateral

integrated with fiat

community control through DAO governance

transparent with regular audits and proof-of-reserves

Constant-Sum Market Maker (CSMM)

linear invariant

x + y = k, delta x = delta y

1:1 exchange

vulnerable to arbitrage

unable to react to external market price changes (if market price shift to not 1 Y per 1 X, arbitrageurs can exploit)

one token can get completely drained

unsafe in practice (not used in real-life)

1mil USDC → 1mil DAI (1.0000 price, 0% price impact)

Constant-Product Market Maker (CPMM)

hyperbolic invariant

x y = k, delta y = (delta x * y)/(x + delta x)

trades cause slippage

larger trades causes more deviations between prices

when pool prices deviate from external markets, arbitrage trades profit until pool’s ratio aligns with global market

slippage prevents pool drainage

used for crypto since no assumption of fixed ratio

1mil USDC  → 980392 DAI (0.9804 price, 1.96% price drop)

Slippage

difference between average execution price and marginal price at start of trade

Curve’s StableSwap

A(x+y) + D = AD + (D³)/(4xy)

A(x+y) provides flat pricing near equilibrium

(D³)/(4xy) ensures infinite liquidity at extremes

A is tuning parameter to control hybrid behavior (critical amplification coefficient)

D is total liquidity

low slippage when prices near 1:1

better capital efficiency (large trades have minimal price impact)

CPMM at extremes prevent pool drainage

used for stablecoin exchanges to allow for simple swaps

1mil USDC → 999990 DAI (0.99999 price, 0.001% price drop)

Amplification Coefficient (A)

tuning lever in stableswap

higher A value → flatter around equilibrium (closer to CSMM)

Loan-to-Value Ratio (LTV)

maximum borrowing against collateral

example: 80% LTV on ETH allows $800 loan against $1000 collateral

lower LTV for volatile assets

set by protocol governance

leveraged trading and accessing liquidity without selling assets → avoiding taxable events

Utilization Rate (U)

U = total borrowed / total available liquidity

low U → interest rates fall to encourage borrowing

high U → interest rates rise to incentivize repayment and attract liquidity

optimal rate ~80%

Kinked Interest Rate Model

balance capital efficiency with liquidity risk

below optimal U → interest rates rise slowly to encourage borrowing and maximize capital efficiency (gentle slope)

above optimal U → interest rates surge sharply to prevent pool drainage and attract new liquidity (steep slope)

Health Factor (HF)

HF = (total collateral value * weight avg liquidation threshold)/(total borrow value)

HF > 1 → safe

HF <= 1 → under-collateralized, eligible for liquidation

affected by collateral asset value decreasing, borrowed asset value increasing, taking on additional debt

improve HF by supplying more collateral or repaying debt

example: initial $10000 in ETH with threshold 80% for $6000 in GH, HF=10000×0.8/6000=1.33, ETH drops to $7000, HF=7000×0.8/6000=0.933, liquidate

Liquidation Process

triggered by borrower’s health factor falling below 1

automated liquidator bots monitor blockchain and identify vulnerable position

liquidator calls liquidate, repaying borrower’s debt for them

liquidator receives portion of borrower’s collateral at discount (liquidation bonus), usually 5-10%

previous example: HF=0.933 ($7000 ETH collateral, $6000 GHO debt), with 5% liquidation bonus

liquidator spends $6000 GHO, receives $6300 ETH, profits $300

protocol recovers $6000 GHO and remains solvent

borrower’s debt cleared, receives $700 ETH collateral, lost $6300 to liquidation

Blockchain Oracle

feeds external data to smart contracts

needed to trigger liquidation

has multiple independent sources

resistant to short-term manipulation

de-centralized with no single point of failure

Flash Loan

borrow with zero collateral

loan must be borrowed and repaid with same atomic transaction

reverts if lending contract did not get repaid

used for arbitrage, liquidations, collateral swaps

“money lego” for developers and traders

Atomic Transaction

all or nothing

if every step succeeds, transaction occurs

if any step fails, transaction reverts

Oracle Manipulation Attack

borrowing massive capital through flash loan

use funds to execute swap on low-liquidity DEX to artificially inflate price of token X

gives inflated token X to as collateral to lending protocol using manipulated DEX as oracle, borrows maximum ETH with falsely valued collateral

repays original flash loan, keeps stolen ETH, price of token X crashes, protocol no longer solvent

Oracle Security Strategies

Decentralized Oracle Networks (DONs) - aggregate price data from multiple independent sources

Time-Weighted Average Price (TWAP) - calculate average price over time window (30 minutes), resistant to short-term price spikes

Multi-Source Validation - price agreement across all sources needed before accepting value, detects and rejects outliers

Aave Protocol

liquidity protocol

choose between variable and stable interest rates

pioneered flash loans

supports diverse range of assets as collateral, including violate and niche tokens