红雀:在交换机内限制订单

Xinpeng Hong, Changgang Zheng, S. Zohren, Noa Zilberman
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引用次数: 5

摘要

如今,金融交易往往依赖于机器学习。然而,许多交易应用程序需要非常短的响应时间,传统的机器学习框架并不总是支持这一点。我们提出了Linnet,在可编程交换机中提供金融市场预测。Linnet根据交换机内的高频市场数据建立限价订单,并将其用于基于机器学习的市场预测。Linnet展示了以高精度和低延迟预测未来股票价格走势的潜力,从而增加了财务收益。
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Linnet: limit order books within switches
Financial trading often relies nowadays on machine learning. However, many trading applications require very short response times, which cannot always be supported by traditional machine learning frameworks. We present Linnet, providing financial market prediction within programmable switches. Linnet builds limit order books from high-frequency market data feeds within the switch, and uses them for machine-learning based market prediction. Linnet demonstrates the potential to predict future stock price movements with high accuracy and low latency, increasing financial gains.
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