Article: Application of the Federal Securities Laws to Certain Types of Crypto Assets and Certain Transactions Involving Crypto Assets
Date: 2026-03-23
Publisher: U.S. Securities and Exchange Commission (SEC); Commodity Futures Trading Commission (CFTC)
Score: ₿₿₿
Read time: 120-150 min
Summary:
- Overview: This rule explains how U.S. securities laws apply to crypto assets and related activities. It keeps the Howey test as the main rule for defining securities but adds clearer guidance for crypto markets. The SEC groups crypto assets into five types based on use: digital commodities, collectibles, tools, stablecoins, and digital securities. Most tokens are not securities by default, but can become part of a security if sold with promises of profit from a team’s efforts. The rule also explains when a token stops being tied to such promises. It covers staking, mining, airdrops, and token wrapping to clarify when these may involve securities laws.
- Token Classification Framework: The SEC defines five token types to reduce confusion. Digital commodities, collectibles, and tools are generally not securities, while digital securities always are. Stablecoins may or may not be securities depending on structure and regulation. This classification gives projects a clearer design path for tokenomics and compliance.
- Investment Contract Trigger: A token becomes a security when sold with promises of profit from a team’s work. These promises must be clear, specific, and made before or during the sale. Marketing, whitepapers, and official communications shape investor expectations. Without such promises, buyers are not assumed to expect profit from others.
- Separation Over Time: A token can stop being linked to a security if the team fulfills its promises. Once key development work is complete, buyers no longer rely on the team for profits. At that point, the token may trade as a non-security. This creates a lifecycle model for tokens from “security phase” to “commodity-like phase.”
- Implications for Token Design: Token value must come from utility or network use to avoid securities status. Systems should minimize reliance on a central team and avoid profit-based messaging. Governance, staking, and network incentives are allowed if they do not create profit expectations from others’ efforts. This pushes projects toward decentralized, utility-driven tokenomics.
Article: Do Green Reserve Assets Impact Stablecoin Stability?
Date: 2026-03-28
Publisher: Shrey Lingampalli
Score: ₿₿₿
Read time: 30-40 min
Summary:
- Overview: This paper studies how using green assets as reserves affects stablecoin stability. It finds that green bonds are less liquid than traditional assets like US Treasuries. During stress events, this low liquidity makes it hard for issuers to meet redemptions. The study shows that stablecoins backed by green assets take much longer to recover from de-pegging events. Price volatility increases and persists for longer periods. The stablecoin becomes closely tied to the performance of green bond markets. The paper concludes that green reserves introduce systemic fragility and weaken the reliability of the dollar peg.
- Liquidity mismatch risk: Green bonds have thin secondary markets and are often held long-term. This makes them hard to sell quickly without large price drops. Stablecoins require fast liquidity, creating a mismatch between assets and liabilities.
- Peg instability dynamics: The chart on page 5 shows a drop to about 0.96 USD during a crisis. Recovery takes weeks instead of hours due to liquidity constraints. The peg becomes sensitive to reserve price changes, losing its stability function.
- Volatility and tail risk: The distribution chart on page 12 shows heavy downside tail risk. Large negative price moves are more common than expected under normal models. Volatility clusters and persists, increasing systemic risk over time.
- Systemic design implications: Green reserves increase correlation between stablecoins and climate-related assets. This removes diversification and ties stability to external shocks. The paper suggests stronger liquidity backstops and revised risk models to maintain peg reliability.
Article: Stablecoins as Dry Powder: A Copula-Based Risk Analysis of Cryptocurrency Markets
Date: 2026-03-24
Publisher: Elliot Jones, Toshiko Matsui, William Knottenbelt
Score: ₿₿₿
Read time: 20-25 min
Summary:
- Overview: This paper studies how stablecoins influence cryptocurrency market behavior beyond just maintaining a price peg. It shows that stablecoins act as “dry powder,” meaning they store liquidity that later moves into crypto markets. The study finds that stablecoin activity and volatility can predict future crypto market volatility. Using advanced models, the authors show strong causal links between stablecoins and major cryptocurrencies. Including stablecoin data improves forecasting accuracy and trading performance. The paper concludes that stablecoins are not passive assets but active drivers of market dynamics and risk.
- Stablecoins as liquidity reserve: Stablecoins act as capital waiting to enter crypto markets. When users hold stablecoins, they are often preparing to deploy funds into risk assets. This makes stablecoin supply and activity a leading signal of future market moves.
- Volatility transmission effects: Stablecoin upside volatility and volume lead cryptocurrency volatility. This shows that changes in stablecoin markets propagate into broader crypto markets. The causality holds across daily, weekly, and monthly timeframes.
- Predictive and trading value: Including stablecoin factors reduces forecasting error for crypto volatility. Models using these signals outperform both baseline and traditional volatility models. In trading simulations, this leads to higher returns and better risk-adjusted performance.
- Tokenomics and market design: Stablecoins function as core infrastructure rather than neutral assets. Their design (liquidity, non-yield nature, accessibility) enables capital flow across the ecosystem. This creates systemic importance, where stablecoin dynamics shape overall market cycles.
Article: NFT Games: an Empirical Look into the Play-to-Earn Model
Date: 2026-02-14
Publisher: Yixiao Gao, Fei Li, Ruizhe Shi, Ruizhi Cheng, Jean Zhang, Bo Han, Songqing Chen
Score: ₿₿+
Read time: 25-35 min
Summary:
- Overview: This paper studies how play-to-earn (P2E) NFT games work in practice using real blockchain data from 12 games. It examines ownership, trading activity, and player profits. The study finds that NFT ownership is highly concentrated, with a few wallets holding large shares while most players hold very few assets. Trading activity is low, and many players rarely buy or sell NFTs. Promotion events can temporarily increase trading and prices, but these effects fade quickly. Most players do not earn profits, while developers capture most of the value. The paper concludes that current P2E models are not sustainable without better incentive design.
- Ownership concentration risks: A small number of wallets control a large portion of NFTs across games. Most players own only one or two NFTs and rarely trade them. This reduces market liquidity and limits fair participation in the ecosystem.
- Weak trading dynamics: NFT trading activity is infrequent, with long gaps between purchases. Promotion events can spike trades and prices, but the impact lasts only a few days. This shows that demand is unstable and driven by short-term events.
- Limited player profitability: In most games, average player profits are negative or near zero. Median and mode values confirm that many players lose money even when averages look positive. Developers earn most profits from initial NFT sales.
- Incentive design shortcomings: Current rewards, especially utility tokens, provide little real value to players. The model lacks stable equilibrium, making long-term sustainability difficult. The paper suggests improved incentive mechanisms, including better NFT-based rewards and stronger engagement incentives.
Article: Counted NFT Transfers
Date: 2026-02-22
Publisher: Qin Wang, Minfeng Qi, Guangsheng Yu, Shiping Chen
Score: ₿₿+
Read time: 20-25 min
Summary:
- Overview: This paper introduces a new NFT design called counted transfers, implemented as ERC-7634. It allows NFTs to be transferred only a limited number of times instead of unlimited or zero transfers. Each NFT has a transfer counter and a maximum limit, which decreases with each trade. This creates a new economic property called mobility, meaning how many transfers remain. The model shows that limited transfers can reduce speculation, wash trading, and excessive leverage. Simulations suggest that moderate limits affect only a small portion of normal users. The design aims to improve long-term sustainability of NFT markets.
- Bounded mobility design gap: Current NFTs are either fully transferable or non-transferable, with no middle option. ERC-7634 fills this gap by introducing a transfer cap per token. This allows controlled ownership changes while preserving compatibility with existing NFT systems.
- Mobility drives token value: Token value depends on remaining transfers, creating a “mobility premium.” As transfers are used, value declines because future resale options shrink. This makes later transfers more costly and encourages holding behavior.
- Anti-manipulation mechanism: Each transfer consumes a finite budget, making wash trading costly and self-limiting. Simulations show manipulation becomes unprofitable after a few cycles under capped systems. This introduces a protocol-level deterrent rather than relying on external detection.
- DeFi and lifecycle impacts: Transfer caps limit recursive collateralization and reduce leverage in NFT lending markets. They also enable lifecycle design such as burn, lock, or soulbound conversion after limits are reached. This expands NFT utility while improving economic stability.
