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#SSG# Don't chase high, don't rush without knowing anything, SSX to SSG, you see what the normal price of SSX should be

Grayscale, as one of the few altcoin allocators among Wall Street institutions, has attracted widespread attention in the market with its fund adjustments for the second quarter of 2025. This adjustment involves three major zones: DeFi, smart contracts, and AI, showcasing Grayscale's latest views on the crypto assets market. In the DeFi zone, Grayscale has added the ONDO coin, and the main holdings of this fund are UNI (34.01%), AAVE (30.74%), and ONDO (18.22%). This move indicates that Grayscale is optimistic about the continued development of the Decentralized Finance sector. The changes in the smart contracts fund are significant, with HBAR being added and DOT removed from the portfolio. The adjusted main holdings now include ETH (30.22%), SOL (29.87%), and ADA (18.57%). This change reflects Grayscale's latest assessment of the prospects of different public chain ecosystems. The AI fund's position ratio remains unchanged, with main allocations including TAO (29.10%), NEAR (28.41%), and RENDER (17.34%). This indicates that Grayscale maintains a stable optimistic attitude towards the application prospects of artificial intelligence in the blockchain field. Grayscale's recent fund adjustment has provided valuable insights for investors, especially in the allocation of alts. As one of the few institutions on Wall Street willing to diversify investments beyond mainstream Crypto Assets, Grayscale's investment strategy is undoubtedly worth closely following by market participants. However, when referring to institutional allocations, investors still need to cautiously assess their own risk tolerance and make independent investment decisions.

As the number of Web3 projects increases, investment risks also rise. Some projects attract investors through false advertising, leading to losses. To address this, security companies provide project risk assessment and fund tracking services to help identify risks and track the flow of funds, enhancing asset security. Investors need to choose projects carefully and strengthen their security awareness.

Intent: Potential Solutions to the Complexity Issues of DeFi Before the Luna crash, I operated a stablecoin yield strategy for a friend. He was not familiar with cryptocurrencies and had never even interacted on-chain. Our collaboration model was very simple: he would deposit funds into a hardware wallet, and we would communicate once or twice a week via video conference, where I would guide him in detail on the actions he needed to take. We will diversify our funds into almost all available DeFi protocols across various chains. Within just a few hours, we will conduct dozens of transactions, including approvals, transfers, swaps, deposits, reward claims, and withdrawals. Funds are allocated to customized liquidity pools, voting locks, and other projects to maximize returns. We have utilized almost all mainstream cross-chain bridges, decentralized exchanges, and yield aggregators to optimize our stablecoin portfolio. This process is extremely cumbersome. For transferring U on the Polygon network.

The Rise of Prediction Markets: From Kalshi to the Evolution of Encryption Gambling A prediction market is a speculative market based on trading future event outcomes, with its core function being to aggregate dispersed information through contract prices. Under specific conditions, contract prices can be interpreted as probability forecasts for the occurrence of events. A significant amount of research has shown that the accuracy of prediction markets often surpasses traditional forecasting methods, such as polls or expert opinions. This predictive capability stems from "collective intelligence": anyone can participate in the market, and traders with more information have economic incentives to engage in trading, driving prices closer to the true probabilities. In short, well-designed prediction markets can efficiently integrate a large number of individual beliefs to form a consensus estimate of future outcomes. The modern prediction market traces its origins back to pioneering experiments in the late 1980s. The first academic prediction market was established in 1988 at the Iowa Electronic Market at the University of Iowa.