用超维向量Tsetlin机提升订单簿微观价格估计精度
High resolution microprice estimates from limit orderbook data using hyperdimensional vector Tsetlin Machines
- 基于订单簿深度与买卖盘失衡动态，构建误差校正微价模型
- 在真实市场数据上验证，该模型显著提升未来价格预测准确性
- 计算高效，适合高频交易场景下的实时微价估计
我们提出一种误差校正模型用于微价估计——一种基于订单簿高级信息不平衡的高频未来价格预测方法。该模型先根据买卖价差和最优买卖盘失衡给出初始微价估计，并结合近期高阶价格层级失衡的变化动态调整。引入一种基于新型超维向量Tsetlin机框架的快速计算方法，在实证中证明该估计算法可在订单簿数据上提供稳健的未来价格预测。
原文摘要 · Abstract (English)
We propose an error-correcting model for the microprice, a high-frequency estimator of future prices given higher order information of imbalances in the orderbook. The model takes into account a current microprice estimate given the spread and best bid to ask imbalance, and adjusts the microprice based on recent dynamics of higher price rank imbalances. We introduce a computationally fast estimator using a recently proposed hyperdimensional vector Tsetlin machine framework and demonstrate empirically that this estimator can provide a robust estimate of future prices in the orderbook.
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