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基于字符串结构的外汇交易时间序列预测

文章 arXiv papers · 作者: Richard Pinčák et al.
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总结

本文提出将实际汇率变动映射为类似字符串的结构，以构建外汇交易预测模型。文中指出，传统的长期计量经济学方法可能会忽略交易成本、套利机会和观测时间间隔不规则等实际特征。所提出的表示方法旨在考虑这些市场特征，并支持更稳健的交易和投资组合选择。

作者介绍了使用多字符串结构的应用，并将所得方法与趋势跟踪策略进行比较。他们报告称，在长期交易期间考虑交易成本时，该算法仍保持稳定。摘录未说明数据时期、模型设定、成本假设、表现指标或统计不确定性。因此，这些主张提供的是一个研究方向，信息不足以评估其可复现性，也不足以确定该方法在其他市场或交易条件下的表现。

核心观点

  • 该方法用类似字符串的结构表示实际汇率动态，以进行预测。
  • 其研究动机是解决模型忽略成本、套利或不规则观测时间的问题。
  • 多字符串结构被用于稳健的投资组合选择。
  • 作者将该方法与趋势跟踪策略比较，并报告称其在考虑交易成本时仍保持稳定。
  • 摘录未提供足够的方法细节，无法独立评估所报告的结果。

标签

外汇统计学投资组合构建回测
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# With string model to time series forecasting


# With string model to time series forecasting









Overwhelming majority of econometric models applied on a long term basis in the financial forex market do not work sufficiently well. The reason is that transaction costs and arbitrage opportunity are not included, as this does not simulate the real financial markets. Analyses are not conducted on the non equidistant date but rather on the aggregate date, which is also not a real financial case. In this paper, we would like to show a new way how to analyze and, moreover, forecast financial market. We utilize the projections of the real exchange rate dynamics onto the string-like topology in the OANDA market. The latter approach allows us to build the stable prediction models in trading in the financial forex market. The real application of the multi-string structures is provided to demonstrate our ideas for the solution of the problem of the robust portfolio selection. The comparison with the trend following strategies was performed, the stability of the algorithm on the transaction costs for long trade periods was confirmed.

在遵守原作品许可的前提下，附作者信息全文展示。 许可协议: abstract CC0

此摘要由 Stratmill 研究智能体根据原文撰写，并非原文副本。