2026-04-17 Пятница

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From "On-Chain Applications" to "Financial Infrastructure": The Generational Evolution and Transformation of Perp DEX

Title: From "On-Chain Applications" to "Financial Infrastructure": The Generational Evolution of Perp DEX The 2025 period was a "great filtering era" for the derivatives sector. Surviving Perp DEX platforms have moved beyond being mere "low-cost versions" of CEXs by solving the core cost in finance: trust. With the adoption of full-chain abstraction, users in 2026 can perform seamless cross-chain transactions while retaining asset sovereignty, as funds are secured in smart contracts rather than held by intermediaries. On-chain derivatives now consistently account for over 25% of total trading volume, marking a fundamental shift in user behavior. Over 90% of Perp DEXs failed due to product homogeneity, reliance on subsidized "rented liquidity," and soaring customer acquisition costs. Merely forking existing code or offering token incentives proved unsustainable. Four successful models have emerged: 1. **Hyperliquid**: Achieved near-CEX performance by building its own L1 blockchain optimized for low-latency order books, attracting quantitative capital. 2. **Aster**: Leveraged the Binance ecosystem to offer enhanced capital efficiency, allowing users to earn yield on collateral (e.g., staking rewards) while trading. 3. **Lighter**: Built an app-specific ZK-Rollup to provide a verifiable, mathematically-proven trading infrastructure with anti-MEV properties, appealing to institutions. 4. **Decibel**: Unified high performance and full-chain composability on Aptos, achieving sub-20ms latency and enabling cross-chain margin accounts for seamless trading from wallets like MetaMask. Future evolution will focus on: * **Intent-centric trading**: Users express a desired outcome, and solvers find the optimal execution path. * **AI Agents**: The rise of AI-driven trading strategies will require DEXs to provide high computational power and low latency. * **Advanced Pricing Models**: Dynamic risk engines will use real-time volatility data to automatically adjust parameters, increasing system robustness beyond traditional CEXs. The key to survival is providing unparalleled execution efficiency that capital and trading strategies cannot refuse.

marsbit01/15 04:34

From "On-Chain Applications" to "Financial Infrastructure": The Generational Evolution and Transformation of Perp DEX

marsbit01/15 04:34

Hiring at $200K Annual Salary: Wall Street Advances into Prediction Markets

Wall Street firms are aggressively entering the prediction markets, with trading giants like DRW, Susquehanna, and Tyr Capital building specialized teams. DRW is offering up to $200,000 in base salary to hire traders who can monitor and trade on platforms like Polymarket and Kalshi. Trading volume in these markets surged from under $100 million in early 2024 to over $8 billion by December 2025, attracting institutional interest. Unlike retail traders who often bet on single events, institutions focus on cross-platform arbitrage and structural opportunities. For example, hedge funds can use prediction markets to hedge investments with greater precision by pairing positions—such as buying "no recession" contracts on Polymarket while shorting overvalued bonds in credit markets. Market makers like Susquehanna, which has privileged access to lower fees and higher limits on platforms like Kalshi, are set to reduce arbitrage opportunities and improve liquidity. This professionalization may lead to more complex products, such as multi-event combos and conditional probability contracts. The entry of well-capitalized, technologically advanced institutions signals a maturation of prediction markets, mirroring the historical pattern of散户-driven innovation eventually dominated by professional players. While retail traders may find niches in long-tail events, the era of easy profits from informational edges is likely over.

marsbit01/15 04:02

Hiring at $200K Annual Salary: Wall Street Advances into Prediction Markets

marsbit01/15 04:02

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