很高興能夠為 @aptos 提供建議,幫助他們成為一個頂級的加密貨幣交易目的地。我相信他們正朝著正確的方向前進。
Abstract: To become the premier decentralized liquidity layer the @aptos trading engine needs to serve the needs of professional traders, institutional investors, high-frequency traders (HFT), and retail investors. In this talk, we will focus on the inner workings of HFT to reach a deeper understanding of the role and needs of HFT in a decentralized setting. We will argue that CLOBs are the only empirically backed price discovery mechanism, and briefly review the evidence that current AMM designs may not be viable in the long term. We will then revisit the optimal market-making model of Avellaneda and Stoikov (2008) and point out that, while insightful and celebrated, this model suffers from several shortcomings, among them the absence of price ticks and priority queues, the fixed order sizes, and other unrealistic assumptions regarding the price dynamics. We will then introduce alternative optimal market-making models, some of which have closed-form solutions, and are also easier to adapt to the multi-asset case. We will close with a discussion of the practical considerations that the stochastic price dynamics of the published market-making solutions of the Hamilton-Jacobi-Bellman equation often neglect, such as quote sniping by informed traders, and provide heuristic descriptions of what market makers do in practice to reduce their risk. When: July 16th at 11 am Where: aptos hq
查看原文
本頁面內容由第三方提供。除非另有說明,OKX 不是所引用文章的作者,也不對此類材料主張任何版權。該內容僅供參考,並不代表 OKX 觀點,不作為任何形式的認可,也不應被視為投資建議或購買或出售數字資產的招攬。在使用生成式人工智能提供摘要或其他信息的情況下,此類人工智能生成的內容可能不準確或不一致。請閱讀鏈接文章,瞭解更多詳情和信息。OKX 不對第三方網站上的內容負責。包含穩定幣、NFTs 等在內的數字資產涉及較高程度的風險,其價值可能會產生較大波動。請根據自身財務狀況,仔細考慮交易或持有數字資產是否適合您。