日内外汇买卖价差模式-分析和预测

Andrius Paukste, A. Raudys
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引用次数: 5

摘要

在外汇交易中,市场流动性由最佳买入价和最佳卖出价价差表示。通过实验比较,我们发现神经网络和回归树最适合于流动性预测,并且优于简单的平均和回归。我们还对影响预测准确性的因素进行了评级。一天中的时间是影响流动性最大的因素,其次是一周中的哪一天。月份和日期对流动性没有影响。作为最后的结论,我们指出,在大多数货币对中,流动性可以比简单的平均预测更准确,这在实践中经常用于计划大订单的执行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intraday forex bid/ask spread patterns - Analysis and forecasting
In the foreign exchange, market liquidity is represented by the best bid and the best ask price spread. We searched for liquidity patterns during 24h trading sessions After experimental comparison, we found that neural networks and regression trees are most suitable for liquidity forecasting and outperform simple averaging and regression. We also rated the factors that most influence forecasting accuracy. Time of day is the factor that influences liquidity the most, followed by day of the week. Month and day of the month have no effect on liquidity. As a final conclusion, we state that in most currency pairs the liquidity can be forecasted more accurately than the simple averaging which is often used in practice for planning large order execution.
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