This is the first part of a series exploring key aspects of the impact on price volatility of DEFI lending and borrowing activity. DeFi is reshaping how we approach lending, borrowing, and trading. At the heart of this transformation are stablecoins like USDC, USDT, and DAI. Designed to maintain a fixed value by pegging to assets such as the U.S. dollar, stablecoins offer a reliable medium of exchange and serve as crucial liquidity anchors amid market volatility.
In this installment, we provide an in-depth overview of stablecoins by examining their fundamental mechanisms, differences, and roles within the crypto ecosystem. We explore how fiat-backed models—such as USDC and USDT—contrast with decentralized, crypto-collateralized models like DAI. Each model employs distinct minting and burning processes to maintain its peg, contributing to overall market stability. We also highlight cautionary examples, such as the collapse of TerraUSD, to underscore the risks of relying solely on algorithmic stabilization without robust collateral.
Our analysis leverages high-quality, real-time data from Amberdata to break down key metrics—such as deposits, borrows, withdrawals, and repayments—providing an overview of user activity and identifying the major players in the market. In the next part of this series, we will examine how stablecoin lending and borrowing activity correlates with Ethereum’s price volatility using the Garman-Klass volatility estimator and advanced statistical techniques, uncovering hidden signals for traders and risk managers.
Stablecoins are cryptocurrencies pegged to the value of another asset (often a fiat currency like the U.S. dollar) to remain stable in price. Their primary purpose is to provide a reliable medium of exchange and store of value within crypto markets, avoiding the extreme volatility of coins like Bitcoin. Stablecoins maintain their peg through specific mechanisms: some hold reserves of assets (e.g. cash, bonds, or commodities) as collateral, and others use algorithmic formulas to control supply.
In practice, this means the supply of a stablecoin expands or contracts as needed. For example, when a user redeems a fiat-backed stablecoin for USD, that token is “burned” (destroyed) by the issuer, and new tokens are minted when users deposit more USD as collateral. These minting and burning processes keep the stablecoin’s circulating supply aligned with its backing, thereby anchoring its price to the peg.
In the crypto ecosystem, various stablecoins implement these ideas differently. Below, we compare three prominent stablecoins – USDC, USDT, and DAI – to illustrate their mechanisms, collateral models, and roles.
USD Coin (USDC) is a fiat-collateralized stablecoin pegged 1:1 to the U.S. dollar. Launched in 2018 by the Centre consortium (Circle and Coinbase), USDC is fully backed by dollar-denominated reserves held with regulated U.S. financial institutions. These reserves are kept in segregated accounts and invested in cash and short-term U.S. Treasury bills, ensuring that each USDC token is redeemable for $1.
USDC’s peg is kept via direct redeemability and transparency – if USDC’s market price dips below $1, arbitrageurs can buy it cheaply and redeem with the issuer for $1 of fiat, which reduces supply and pushes the price back to par. Conversely, new USDC is issued (minted) when users deposit USD with the issuer, increasing supply to meet demand.
This design relies on trust in the issuer and audits. Circle provides regular attestations of USDC’s reserves, and funds are custodied by major institutions like BlackRock and BNY Mellon. USDC’s use cases range from everyday payments to a popular base asset in decentralized finance. Its high degree of trust and regulatory compliance makes it attractive for institutions and traders needing a digital dollar, and it serves as a bridge between traditional money and crypto by enabling fast, global USD-denominated transfers.
Tether (USDT) is the oldest and largest stablecoin by market capitalization, also pegged 1:1 to the U.S. dollar. Issued by Tether Limited since 2014, USDT is backed by a reserve of assets equivalent in value to all Tether tokens in circulation. In practice, these reserves have included cash, cash equivalents, loans, and other investments.
Like USDC, USDT’s peg mechanism relies on convertibility – authorized participants can swap 1 USDT for $1 in reserve assets, and new USDT is created when new dollars (or equivalent assets) are deposited. This model has made USDT a cornerstone of crypto trading liquidity: Tether is involved in an outsized share of crypto transactions, often accounting for about half of all crypto trading volume on a given day. Traders worldwide use USDT as a substitute for USD on exchanges, especially where banking access to actual dollars is limited, giving USDT a critical role as a crypto-market funding currency.
However, USDT’s collateralization practices have drawn scrutiny. The issuer has been criticized for lack of transparency in its reserve disclosures and for not undergoing a full independent audit of reserves, leading to concerns about whether every USDT is truly backed 1:1. Despite these issues, USDT remains deeply embedded in the crypto ecosystem due to its first-mover advantage and liquidity. Its ubiquity provides utility (easy movement of dollar-value across exchanges and chains), but also poses a systemic risk if confidence in Tether’s backing wavers.
DAI is a decentralized, crypto-collateralized stablecoin governed by the MakerDAO protocol on Ethereum. Unlike USDC and USDT which rely on off-chain fiat reserves held by companies, DAI is backed by on-chain collateral: users deposit cryptocurrency (such as ETH, USDC, or other approved assets) into MakerDAO smart contracts (called Vaults) and in return mint DAI tokens. Every DAI in circulation is therefore backed by a surplus of crypto assets.
The MakerDAO system enforces over-collateralization – the value of locked collateral must exceed the DAI issued, often by 150% or more. If the collateral value falls too low (due to market volatility), the protocol automatically liquidates those positions to buy back and burn DAI, keeping the stablecoin’s value supported at $1. This design makes DAI essentially an algorithmic stablecoin with crypto backing: monetary stability is achieved through smart-contract rules and economic incentives rather than a central reserve. DAI’s issuance model is open; anyone can generate DAI by providing sufficient collateral, and DAI can be destroyed by repaying the associated debt to retrieve the collateral. DAI is a key building block in DeFi, widely used in lending platforms, decentralized exchanges, and yield farming.
Because it is permissionless and censorship-resistant, DAI is favored by users who want a stablecoin without reliance on any single company or bank. It serves as a stable unit of account within DeFi dApps, enabling borrowers to take out loans in DAI or traders to park value in a stable asset between investments. The trade-off is that DAI’s stability can be tested during extreme market swings (since its backing is volatile assets), but mechanisms like Peg Stability Modules (which allow direct swapping of DAI with other stable assets) and dynamic fees are used to help keep DAI tightly pegged to $1. Overall, DAI showcases an alternative model of stability: transparent, over-collateralized, and governed by a decentralized community rather than a centralized issuer.
TerraUSD (UST) was an algorithmic stablecoin that aimed to maintain a $1 peg without direct collateral. Instead, it relied on a mint-and-burn mechanism linked to its sister token, LUNA. When market pressures emerged, UST’s self-correcting mechanism failed. Mass redemptions led to hyperinflation of LUNA, triggering a collapse in value. This failure underscored the risks of relying solely on algorithmic stabilization without robust, tangible backing. TerraUSD’s dramatic fall serves as a warning that strong collateral, transparency, and effective governance are critical for a stablecoin to maintain its peg and protect users against market panic.
With these insights in mind, one can appreciate why stablecoins (when well-designed) are so pivotal in the crypto economy. Nowhere is this more apparent than in the realm of Decentralized Finance (DeFi), where stablecoins serve as critical infrastructure.
Stablecoins have become the cornerstone of decentralized finance (DeFi), powering a diverse range of lending, borrowing, and trading activities. In decentralized exchanges (DEXs) and liquidity pools, stablecoins serve as reliable trading pairs, ensuring that one side of a transaction remains stable even when paired with volatile assets. This stability minimizes price slippage and enhances overall market efficiency, with studies suggesting that stablecoins can account for nearly half of the liquidity on DEXs.
The chart above illustrates a significant increase in the cumulative total of stablecoins over recent months, with the current figure reaching $120 billion, up from $85 billion in October. This growth is primarily driven by major contributions from USDC and USDT, underscoring their dominant roles in the stablecoin market. This upward trend reflects the growing reliance on stablecoins as a liquidity anchor, especially in decentralized finance and broader cryptocurrency trading environments. These figures signal a market shift.
Stablecoins are vital in DeFi lending and borrowing. Platforms such as Aave, Compound, and MakerDAO enable users to borrow stablecoins against crypto collateral, while lenders earn interest on their deposits. This arrangement allows borrowers to secure “crypto-dollars” without the fear of sudden price spikes, and provides lenders with a predictable, steady yield. Additionally, stablecoins bridge the gap between traditional finance and the crypto world—1 USDC, for example, represents one U.S. dollar held in a bank, yet it can be transferred globally within minutes. By offering stability, liquidity, and interoperability, stablecoins not only facilitate seamless DeFi transactions but also lower the barriers for new market entrants.
Stablecoin velocity quantifies how actively a stablecoin is used as a medium of exchange relative to its total supply. In simple terms, it measures the rate at which coins change hands over a given period. The formula for velocity (V) is:
where T represents the total transaction volume over a set period (e.g., daily or monthly), and S is the average stablecoin supply during that same period.
A higher velocity suggests that the stablecoin is being actively used in transactions—be it for trading, payments, or other forms of exchange—rather than simply being held as a store of value.
When comparing established stablecoins like USDC and USDT with newer entrants such as PYUSD, the differences in velocity become particularly revealing. USDC and USDT, having been in the market longer, have built a solid reputation and extensive network integration across various platforms—from decentralized exchanges (DEXs) to centralized trading venues. Their higher velocity indicates robust usage and liquidity, which, in turn, contributes to greater market confidence and stability. Frequent transactions signal that these stablecoins are not only being used as collateral or a reserve asset but are also vital for day-to-day trading and payment operations. This active circulation reinforces their role as the lifeblood of the DeFi ecosystem, supporting efficient capital flows and price discovery.
In contrast, PYUSD, as a relatively newer stablecoin, shows a lower velocity. This suggests that it is currently less integrated into the transactional fabric of the crypto market, potentially due to limited adoption, fewer integration points, or cautious market sentiment among users. A lower velocity for PYUSD may imply that it is still in an early phase of adoption, serving more as a speculative or niche asset rather than a widely used medium of exchange.
Understanding stablecoin velocity is significant because it helps investors and analysts assess market activity and liquidity conditions. By comparing the velocity of different stablecoins, stakeholders can gauge not only the popularity and trust in these assets but also identify potential shifts in market dynamics, thereby informing strategic decisions and risk management practices.
For investors and traders navigating the DeFi landscape, understanding the metrics behind lending and borrowing activities is crucial. These metrics serve as vital indicators of protocol health, user engagement, and liquidity trends—essential factors for making informed decisions. By tracking key data points, you can gauge where market activity is heading and spot potential risks or opportunities early on. You can find the metrics used here and many more using our Amberdata API.
Transaction Values:
Metrics like depositedUSD, borrowedUSD, withdrawnUSD, and repaidUSD measure the dollar value of funds moving through various protocols. These figures help quantify the scale of activity and signal shifts in liquidity. For instance, a spike in borrowedUSD relative to depositedUSD might indicate increased demand for leverage, while rising repaidUSD values could suggest a trend toward deleveraging. As a trader, monitoring these values provides a window into market sentiment and liquidity flows.
Activity Counts:
Metrics such as numberOfDeposits, numberOfBorrows, numberOfRepays, and numberOfWithdraws capture how frequently users interact with the platform. High activity counts may reflect strong engagement and confidence, while sudden drops might hint at emerging concerns. For an investor, these counts offer a granular view of market participation, helping to differentiate between sporadic bursts of activity and sustained healthy usage.
Ratios and Cumulative Metrics:
Derived metrics like depositRatio, borrowRatio, and cumulativeInterestEarnedUSD provide deeper insights into how stablecoins perform relative to other assets. The depositRatio, for example, indicates the share of deposits allocated to a stablecoin compared to the total across protocols, while the borrowRatio reflects similar concentration on the borrowing side. Cumulative metrics track long-term performance, offering context for how a protocol has evolved over time. Such ratios are excellent for assessing liquidity risk and overall protocol stability.
Together, these metrics form the backbone of a data-driven approach to understanding DeFi lending and borrowing dynamics. They empower investors and traders to identify trends, assess risk levels, and make decisions backed by empirical evidence.
In practice, keeping an eye on these indicators can reveal much about market dynamics. For instance:
By integrating these metrics into your analysis, you can develop a nuanced understanding of DeFi’s lending and borrowing activities—turning raw data into actionable insights for better market positioning.
The depositedUSD metric reveals that, on average, USDC deposits reach about $104 million per intra-day period, while the median sits around $81 million. With the 25th percentile at approximately $48 million and the 75th at about $132 million, most transactions fall within a moderate range. However, outliers exist—with some deposits reaching as high as $770 million—which are likely driven by institutional players.
The high skewness (2.58) and kurtosis (10.88) indicate a heavy-tailed distribution, highlighting significant variability in deposit sizes that can impact overall liquidity and risk assessments.
For borrowedUSD, the average borrowing activity is roughly $84 million, with a median of about $64 million and values ranging from as low as $3.16 million to nearly $392 million. Similarly, withdrawnUSD and repaidUSD metrics show average values of about $105 million and $89 million, respectively, with medians around $83 million and $69 million. These figures suggest that while typical transactions tend to be moderate in size, there are instances of very large movements that could influence market dynamics. The variability in these metrics not only signals diverse user activity—from small-scale retail engagements to large institutional transactions—but also points to potential liquidity pressures under volatile market conditions.
The ratio-based metrics further deepen our understanding of USDC's market role. The depositRatio averages 0.19 (median 0.13), meaning that, on average, USDC constitutes about 13–19% of total deposits across protocols—though in some time periods, it was as high as 0.74. In contrast, the borrowRatio centers around 0.43 (median 0.43), indicating that nearly 43% of borrowing activity involves USDC. This disparity suggests that users might be leveraging USDC more heavily in borrowing scenarios, which could expose the market to higher risk if borrowing levels become unsustainable. Together, these insights highlight the centrality of USDC in DeFi lending ecosystems, reflecting both its widespread use and the underlying concentration risks associated with its deployment.
The USDT transaction metrics also provide an interesting picture of market activity. On average, USDT deposits amount to roughly $34 million per period, with a median of about $21 million—indicating that most transactions fall between $7 million (25th percentile) and $44 million (75th percentile).
The high skewness of 2.41 and a maximum value of approximately $261 million suggest occasional, very large deposits, likely driven by institutional activity.
Similar patterns emerge in borrowing, where the average borrowedUSD is around $29.8 million (median $20.4 million), and in withdrawals and repayments, which average $31.3 million and $28.3 million respectively, yet exhibit significant variability. These figures offer a nuanced view of both typical user behavior and outlier events that can shift market dynamics.
The variability in these transaction values implies that while the bulk of USDT movements are moderate, there are intermittent bursts of high-value transactions that can significantly influence overall liquidity. For example, the withdrawnUSD distribution—with a skewness of 2.97 and a maximum nearing $288.5 million—reveals that although most withdrawals cluster around a median of $20.2 million, extreme cases exist. Such outliers are crucial for traders as they indicate periods of heightened activity and possible liquidity stress. The same holds for repaidUSD, where the average is $28.3 million but the data spans from as little as $22,000 to over $157 million. These insights help market participants understand that routine activity coexists with sporadic, high-impact events, offering clues about market sentiment and potential volatility.
Ratio-based metrics further enrich this analysis by contextualizing USDT's role within the broader ecosystem. The depositRatio for USDT averages around 0.04 (or 4.25%), with a median of 0.03 (2.51%), indicating that USDT deposits represent a relatively small portion of total deposits across protocols. Conversely, the borrowRatio averages approximately 0.16 (15.54%) with a median of 0.13 (13.27%), suggesting a greater utilization of USDT in borrowing activities. This disparity points to a focused borrowing activity that may signal leveraged positions and associated liquidity risks. For investors and traders, tracking these ratios is key to understanding concentration risks and the overall health of the lending and borrowing markets.
The depositedUSD metric for DAI shows an average of approximately $571 million per period, with a median of around $83 million. The distribution is right-skewed—with the 25th percentile at about $4.9 million and the 75th at roughly $812 million, and a maximum nearing $4.95 billion—indicating that while most deposits are moderate, a few very large transactions, likely from institutional actors, significantly influence the average. Similarly, the withdrawnUSD values mirror this pattern, underscoring that DAI sees substantial liquidity flows. This variability gives a unique shape to overall liquidity and risk profiles.
In contrast, the borrowedUSD and repaidUSD metrics present a much lower scale of activity. The average borrowedUSD is around $4.32 million with a median of approximately $2.23 million, and repaidUSD averages about $4.50 million with a median near $2.28 million. Both metrics exhibit very high skewness (over 4.2 for borrowedUSD and 4.78 for repaidUSD) and extreme kurtosis, highlighting the presence of occasional large borrowings or repayments amid generally modest transactions. These figures suggest that while borrowing in DAI is relatively limited compared to deposits and withdrawals, the few large-scale borrowings could represent leveraged positions or unique market events, signaling potential shifts in risk or liquidity that traders and investors should monitor closely.
Looking at ratio metrics, the depositRatio averages 0.31 (with a median of 0.16), indicating that on average, DAI deposits make up about 31% of total assets deposited across protocols—though the distribution shows significant variability, with some time periods, perhaps early on, as high as 0.92. In contrast, the borrowRatio averages just 0.04 (median 0.02), suggesting that DAI accounts for a relatively small portion of borrowing activity. This disparity implies that DAI is primarily used as a deposit or collateral asset rather than for borrowing, reflecting conservative lending practices. For market participants, these ratios are key risk indicators, helping to assess concentration risk and overall market stability.
We have now shed light on the pivotal role of stablecoins in the decentralized finance ecosystem. We began by dissecting the underlying mechanisms of stablecoins such as USDC, USDT, and DAI, highlighting how each maintains its peg through distinct minting and burning processes. While USDC and USDT rely on fiat collateral to secure their value, DAI operates with crypto-collateralization, offering an alternative, decentralized approach to stability. We also examined cautionary examples like TerraUSD, which underscore the risks of relying solely on algorithmic mechanisms without robust backing.
We also discussed the dynamics of stablecoin velocity, revealing that established assets like USDC and USDT exhibit higher velocity, indicating active use in everyday transactions and robust liquidity, while newer entrants like PYUSD show lower velocity, hinting at limited market penetration and adoption. Additionally, we broke down key metrics—deposits, borrows, withdrawals, and repayments—using granular data from Amberdata. The detailed statistical view of each metric provided insights into user behavior, liquidity flows, and potential market risks. For instance, USDC’s significant outlier deposits suggest heavy institutional influence, whereas USDT’s intermittent bursts of high-value transactions point to occasional liquidity stress. DAI’s profile, dominated by large deposit flows but modest borrowing, reinforces its role as a primary collateral asset rather than a leveraged medium.
Together, these findings emphasize how stablecoins serve not only as liquidity anchors but also as critical conduits between traditional finance and the crypto world. They form the backbone of DeFi, enabling efficient trading, lending, and borrowing, while also helping to manage market volatility. For more information on the state of the stablecoin ecosystem see the Amberdata 2024 Digital Asset Market Intelligence Report: Stablecoins.
In the next part of this series, we will shift our focus to the interplay between stablecoin lending activity and Ethereum’s price volatility. By employing the Garman-Klass volatility estimator and advanced statistical techniques, we aim to uncover hidden signals that can help traders and risk managers to navigate the dynamic crypto landscape more effectively.
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