The recent wave of decentralized finances (DEFI) has moved to the orientation of technical risks at economic risks, as a tweet of intotheblock points out on May 2, 2025, at 10:30 am UTC (source: intotheblock Twitter). This transition in the perception of risks has important implications for cryptographic traders who sail in the DEFI space, where economic vulnerabilities such as impermanent loss, token inflation and liquidity pool imbalances become more critical than bugs or hackers of intelligent contracts, which have historically dominated concerns. As of May 2, 2025, at 12:00 pm UTC, the total locked value (TVL) in protocols DEFI reached $ 120 billion, an increase of 15% compared to the previous week, according to Defillama (source: defillama) data. This thrust indicates an increasing confidence of investors, but also amplifies the economic risks linked to over -growed positions and to volatile tokenomics. For example, trading pairs like ETH / USDT on UNISWAP have seen a 24 -hour negotiation volume of $ 1.2 billion on May 2, 2025, at 1:00 p.m. UTC, reflecting high liquidity but also a significant price lag potential during market stress (source: UNISWAP analytics). In addition, Glassnode chain metrics reveal that the number of unique addresses interacting with the DEFI protocols increased by 20% of the week to 5.3 million from May 2, 2025, at 2:00 p.m. UTC, signaling a robust user adoption but raising concerns about economic stability if sudden liquidations occur (source: source of glass). For merchants, understanding these economic risks is essential, especially when monitoring the DEFI tokens linked to AI like FET (Fetch.ai), which jumped from $ 2.35 in May 24, 2025, at 3:00 p.m. UTC, driven by IA integration announcements in Defid Feading Farming (Source: Coindecko). This intersection of AI and DEFI underlines how technological progress can influence the feeling of the market and the possibilities of negotiation in cryptographic space, in particular for automation led by AI in the supply of liquidity.
The commercial implications of this transition to economic risk in DEFI are deep, as traders must now prioritize the strategies that reduce exposure to the devaluation of tokens and liquidity crises compared to traditional technical guarantees. On May 2, 2025, at 4:00 p.m. UTC, the ETH / DAI pair on curve finance recorded a negotiation volume of $ 800 million, with a significant price difference of 5% during a 2 hour window, highlighting the economic risk of impermanent loss for liquidity suppliers (source: Curve finance Dashboard). These data suggest that traders should adopt dynamic rebalancing strategies or use AI -powered tools to predict liquidity pool changes. In addition, the correlation between the tokens linked to the AI and the main active ingredients such as Bitcoin (BTC) has strengthened, FET showing a correlation coefficient of 0.85 with the BTC price movements during last week May 2, 2025, at 5:00 p.m. UTC (Source: Coating). This correlation indicates that the performance of AI tokens can serve as an indirect indicator for a wider feeling on the market, offering trading opportunities during gatherings or hollows of the BTC. For example, traders could explore long positions on FET / USDT when BTC exceeds its mobile average at 50 days, because historical data suggests a probability of 70% of an increase in the price FET of 5 to 10% within 48 hours (source: historic tradingView data). In addition, IA -oriented trading robots have contributed to a 30% increase in the DEFI negotiation volume, reaching $ 5 billion per day on the main decentralized exchanges on May 2, 2025, at 6:00 p.m. UTC, by amplifying both the opportunities and the economic risks linked to automated liquidations (source: Dune Analytics). Traders focusing on the AI-Crypto crossover should monitor these volume tips for entry and exit points, especially on the Volatile DEFI markets.
From a technical point of view, key indicators highlight the growing economic risks in DEFI while offering usable information for merchants. As of May 2, 2025, at 7:00 pm UTC, the relative resistance index (RSI) for ETH on Binance was 62 years, indicating an almost drop -down condition which could precede a correction if the economic pressures rise (source: graphics of binations). Meanwhile, the divergence of Mobile Average Convergence (MacD) for FET showed a Haussier crossing on the table from 4 hours to 8:00 p.m. UTC on the same day, suggesting a short -term momentum for AI chips in the middle of DEFI growth (Source: TradingView). The volume of negotiation against FET / USDT on Kucoin increased by $ 40% to $ 150 million within 24 hours preceding on May 2, 2025, at 9:00 p.m. UTC, reflecting increased interest in trader potentially motivated by the news of AI-DEFI integration (Source: Kucoin Analytics). Chain data also reveals that whale transactions (more than $ 100,000) for FET increased by 25% to 120 transactions per day on May 2, 2025, at 10:00 p.m. UTC, reporting a strong institutional interest which could exacerbate the economic risks in the event of a sale (source: whale alert). For merchants, these measures highlight the importance of defining hitchhiking orders tight around key resistance levels, such as $ 2.40 for FET, to mitigate the risk of decline. In addition, the intersection of AI markets and cryptography continues to influence the feeling, because the DEFI protocols focused on AI reported an increase of 10% in user deposits at $ 15 billion on May 2, 2025, at 11:00 p.m. UTC, by intotheblock analytics (source: intotheblock). This data suggests that AI innovations have a direct impact on DEFI’s liquidity and trading dynamics, creating economic opportunities and vulnerabilities for market players looking for terms such as “DEFI Economic Risk Analysis” or “IA Crypto Trading Strategies”.
In summary, the evolutionary landscape of DEFI, as indicated on May 2, 2025, requires vivid emphasis on economic risks on technical risks, AI playing a central role in training trading opportunities and the feeling of the market. Merchants take advantage of the tools for “agricultural risks of DEFI performance” or the “prediction of the AI tokens prices” can capitalize on these trends by closely monitoring metrics and volume data on the chain. The correlation between AI toys like FET and the main assets offers unique crossover trading configurations, which makes it an exciting but difficult period for cryptographic investors.
