Article: Where Are Our Airdrops Going?
Date: March 2025
Publisher: Joshua Wong
Score: ₿₿₿
Read time: 13 minutes
Summary:
- Overview: The article explores the current landscape of crypto token airdrops, categorizing them into Retroactive and Engagement types. Retroactive airdrops reward past users based on historical activity, while engagement airdrops are designed to attract new users through incentivized actions. The report identifies critical issues with airdrops, such as sybil farming, insider-heavy allocations, and confusing eligibility criteria, and analyzes sentiment across several recent airdrops. Through examples like Redstone and Scroll, it outlines common pitfalls and lessons. Finally, the article offers recommendations for better airdrop practices, including improving transparency, involving the community, and adopting advanced monitoring tools.
- Two Airdrop Types Explained: Retroactive airdrops reward users without prior notice, usually benefiting existing communities. These work well for mature projects. In contrast, engagement airdrops announce future distributions and often use point systems to gamify user participation. These are suited for newer projects trying to grow user bases. Both types require different considerations regarding communication and eligibility rules.
- Recent Airdrop Sentiment Trends: Sentiment analysis of major airdrops shows that clear criteria and fair distribution lead to higher community satisfaction. Projects like Pudgy Penguins and Hyperliquid scored high due to strong alignment with user expectations. Others like Redstone and Scroll received criticism due to last-minute changes or opaque rules. The data highlights the importance of setting and maintaining user trust.
- Common Allocation Mistakes: The report identifies several recurring missteps: sudden allocation changes, unclear eligibility metrics, and heavy insider/influencer allocations. These often damage trust and trigger backlash. For example, Redstone cut its community allocation close to launch, and Kaito’s high insider share sparked criticism. Implementing vesting schedules and setting clear guidelines early can help prevent these issues.
- Suggestions for Future Airdrops: Three improvement areas are emphasized: (1) Transparency in token allocation and eligibility metrics, (2) Community involvement in designing distribution frameworks, and (3) Use of monitoring tools like on-chain analytics and proof-of-humanity systems to combat sybil farming. These approaches aim to align incentives and reduce manipulation, thereby restoring airdrops’ credibility as a distribution method.
Article: Tokenomics of DAO Treasuries: Sustainable Management Strategies in Decentralized Organizations
Date: Q4 2024
Publisher: Haider Khan
Score: ₿₿+
Read time: 30-35 minutes
Summary:
- Overview: This article explores how Decentralized Autonomous Organizations (DAOs) manage their treasuries, currently valued over $21.5 billion across the top 50 DAOs. It presents an in-depth analysis of treasury composition, allocation strategies, and associated risks. Most DAOs hold a high percentage of their native tokens, which creates a circular risk dynamic. The paper reviews various treasury structures, including grant funding, staking, and investment mechanisms. It also highlights governance issues and proposes risk frameworks and sustainable tokenomics practices. Case studies of Uniswap, Gitcoin, and MakerDAO are used to illustrate effective treasury and governance models, offering a set of actionable best practices for DAO developers and managers.
- DAO Treasury Composition: DAO treasuries are typically composed of 67.3% native governance tokens on average, leading to high volatility. Protocol DAOs hold even more (up to 72.5%), whereas service DAOs are more diversified with stablecoin holdings. Larger DAOs with treasuries over $500M tend to be more diversified and better risk-managed. This high concentration introduces liquidity and governance risks.
- Allocation Strategies in Practice: DAOs divide their expenditures across grants (22.4%), investments (14.8%), staking (18.3%), and operations (31.7%). Grant effectiveness is mixed, with under half of funded projects active after a year. Investments yield around 7.3% annually, but with high variance. Operational budgets are becoming more structured with formal compensation models to improve sustainability.
- Risk Categories Identified: The paper classifies DAO treasury risks into volatility exposure, concentration risk, governance attacks, and regulatory uncertainty. High token concentration leads to 3x higher volatility. Many treasuries rely on few platforms or stablecoins, exposing them to systemic risk. Governance attacks exploit low participation and voting manipulation. Regulatory clarity remains limited and unevenly addressed.
- Tokenomics and Sustainability: Sustainable treasury management is tightly linked to sound tokenomics. Revenue from protocol fees and services helps reduce reliance on token appreciation. Token utility-like governance rights and staking-is essential for value retention. Emission trends are shifting to deflationary or capped models, improving long-term sustainability. Metrics such as Revenue/Market Cap and Treasury Runway are proposed for evaluating DAO health.
- Case Study Insights: Uniswap's gradual diversification has reduced treasury volatility, while Gitcoin's community-driven quadratic funding enables decentralized but stable public goods funding. MakerDAO’s endowment model uses professional fund segmentation and governance specialization to manage risk conservatively. Each model emphasizes different trade-offs between decentralization, risk, and operational stability.
Article: Tariff Escalation and Crypto Markets: Impact Analysis
Date: April 7, 2025
Publisher: Binance Research (Moulik Nagesh)
Score: ₿₿+
Read time: 18 minutes
Summary:
- 1. Overview: The article analyzes how the sharp rise in U.S. import tariffs under President Trump in 2025 is affecting the global economy and crypto markets. These tariffs, the most sweeping since the 1930s, have triggered a wave of retaliatory measures from trading partners and contributed to fears of a prolonged trade war. In crypto, market capitalization has dropped nearly 26% as investors moved to safe-haven assets like gold. Bitcoin, Ethereum, and altcoins have seen sharp price declines, with volatility rising significantly. The broader macro environment now includes rising inflation expectations, slower growth, and increased speculation on Fed policy shifts, with markets pricing in rate cuts. The article concludes by highlighting how prolonged protectionism could influence crypto's role as a hedge or risk asset depending on upcoming macro and policy developments.
- 2. Tariffs as Inflation Drivers: The new tariffs have added to inflationary pressure by raising import costs, just as the Fed has been attempting to ease price growth. Market-based inflation expectations and consumer sentiment surveys both suggest inflation will remain high in the short term. This could complicate monetary policy and limit crypto’s appeal as a hedge if real returns remain compressed.
- 3. Market Volatility and Risk Sentiment: Crypto has shown high sensitivity to tariff announcements, with Bitcoin and Ethereum experiencing major single-day price drops. Volatility has risen sharply, especially in Ethereum, where one-month realized volatility surpassed 100%. This highlights the current vulnerability of digital assets to fast-moving macro shifts and policy uncertainty.
- 4. Changing Correlation Patterns: During the early stages of the trade conflict, Bitcoin's correlation with equities grew stronger while its correlation with gold declined. This behavior positions Bitcoin as more aligned with risk assets during stress events. However, long-term correlation metrics still suggest Bitcoin maintains a degree of independence from both traditional hedges and stocks.
- 5. Outlook in a Protectionist World: The outlook for crypto will depend heavily on the macro trajectory: prolonged trade disputes could hurt growth, curb investment, and limit liquidity flowing into crypto. Key variables include inflation data, global growth trends, central bank policy, and any crypto-specific catalysts like regulatory shifts or ETF approvals. Until clarity emerges, crypto markets may remain reactive and range-bound, lacking a clear direction.
Article: A Two-Stage Game Model of Probabilistic Price Manipulation in Decentralized Exchanges
Date: March 5, 2025
Publisher: Bumho Son, Yunyoung Lee, Huisu Jang
Score: ₿+
Read time: 35 minutes
Summary:
- Overview: This article builds a game-theoretic framework to understand sandwich attacks on decentralized exchanges (DEXs), a form of price manipulation where attackers exploit transaction sequencing. The authors propose a two-stage model where victims first set slippage tolerance, and attackers respond by selecting attack volume and fee strategies. Unlike prior models assuming perfect predictability and maximal exploitation, this model incorporates “external slippage”-random state changes in the liquidity pool caused by other transactions-which makes attack outcomes probabilistic rather than deterministic. Using both theoretical modeling and Uniswap transaction data, the study finds that attackers often opt for submaximal attack volumes, balancing cost with likelihood of success. The article further explores behavioral tendencies in crypto trading and shows that empirical data better support their probabilistic model over prior deterministic ones.
- Slippage and probabilistic attack outcomes: Slippage tolerance-the acceptable price deviation in a trade-is crucial in DEXs. This article reveals that attackers do not always aim to maximize slippage. Instead, they consider the risk that intervening transactions (external slippage) will alter pool conditions, making a full attack less predictable. This leads to more conservative strategies that trade off between fee costs and profit certainty.
- Fee prioritization and transaction ordering: The article empirically verifies that transaction order in blocks is heavily influenced by gas prices. Higher gas fees increase the likelihood of a transaction being executed earlier, making fee setting a strategic variable for attackers. This directly impacts the success probability of sandwich attacks, which rely on precise sequencing.
- Behavioral model validation: Introducing a bounded rationality framework, the authors account for the non-optimal behavior of real attackers and victims. They show that traders often act under social and emotional influences rather than purely rational calculations. By fitting different levels of rationality into the model, the paper demonstrates better empirical accuracy, reinforcing the need to integrate behavioral factors in tokenomics analysis.
- Empirical support for model assumptions: Using 4,810 swap transactions from Uniswap V2 and V3, the study finds that most sandwich attacks use less than the maximum feasible input volume. This behavior supports the model’s assertion that attackers account for uncertainty in transaction ordering. Additionally, optimal profits predicted by the model were statistically higher than real-world gains, suggesting that many attackers could improve outcomes by adopting this model’s strategies.
Article: Competition in the Cryptocurrency Exchange Market
Date: March 2025
Publisher: Junyi Hu (Columbia Business School), Anthony Lee Zhang (University of Chicago)
Score: ₿+
Read time: 40 minutes
Summary:
- 1. Overview: This article develops a theoretical and empirical framework to explain why the cryptocurrency exchange market remains highly fragmented despite offering fungible assets. The authors build a model where many small exchanges with captive customer bases are interconnected by arbitrageurs. These arbitrageurs create a “star-shaped” network, where a central exchange acts as a liquidity hub and facilitates price and inventory smoothing across peripheral exchanges. Using a comprehensive dataset from 2017 to 2023 covering 770 coins and 254 exchanges, the paper shows that when central exchanges like Binance or Coinbase list a coin, they reduce price dispersion, increase arbitrage and trading volumes on peripheral exchanges, and prompt further listings. These findings underline the role of centralized hubs in a decentralized asset ecosystem and have policy implications for regulating both exchange listings and arbitrage flows.
- 2. Centralized liquidity hubs: The paper introduces the idea that arbitrageurs coordinate to form a "star" network, linking smaller peripheral exchanges to a central hub. This structure emerges when arbitrage transportation costs are low relative to customer inventory costs. The central exchange becomes a critical point for liquidity redistribution, shaping the entire market's dynamics, including pricing and trade volumes.
- 3. Impact of central listings on market structure: Listing decisions by central exchanges significantly influence the broader market. When these exchanges list a new coin, price dispersion across peripheral exchanges drops, arbitrage activity rises, and trading volumes increase. These central listings also trigger more peripheral exchanges to list the coin soon after, confirming the central role of major exchanges in market coordination.
- 4. Empirical confirmation using Ethereum flows: The authors use Ethereum on-chain data to trace arbitrage flows, showing that most volume passes through Binance and Coinbase, reinforcing the central exchange theory. Arbitrage volumes at these hubs are large relative to trade volumes, distinguishing them from simply being venues with large user bases. The network analysis reveals a core-periphery structure matching theoretical predictions.
- 5. Policy implications for regulation: Given their systemic importance, central exchanges and arbitrageurs are flagged as potential targets for regulation. The authors suggest that exchange listing decisions could be subject to oversight, and arbitrageurs might require registration and reporting, akin to rules for market makers and ETF authorized participants in traditional finance. This oversight could influence local market efficiency and overall market structure resilience.
