Edward P. K. Tsang, Shuai Ma, V. L. Raju Chinthalapati
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引用次数: 0
Abstract
Directional change (DC) is an alternative to time series in recording transactions: it only records the transactions at which price changes to the opposite direction of the current trend by a threshold specified by the observer. DC can only be confirmed in hindsight: one does not know that direction has changed until it is confirmed by a later transaction. The transaction in which the price confirms a DC is called a DC confirmation point. DC nowcasting is an attempt to recognize DC before the DC confirmation point. Accurate DC nowcasting will benefit trading. In this paper, we propose a method for DC nowcasting. This method is entirely data driven: it is based on the historical distribution of DC-related indicators. Empirical results suggest that DC nowcasting is possible, even under a naïve rule. This opens the door to a promising research direction on an important topic.
方向性变化（Directional Change，DC）是时间序列记录交易的一种替代方法：它只记录价格在观察者指定的临界值内向当前趋势相反方向变化的交易。方向性变化只能在事后确认：只有在后来的交易中得到确认，才能知道方向已经改变。价格确认 DC 的交易称为 DC 确认点。直流预报是在直流确认点之前识别直流的一种尝试。准确的 DC 现在预测将有利于交易。在本文中，我们提出了一种 DC 现在预测方法。该方法完全由数据驱动：它基于 DC 相关指标的历史分布。实证结果表明，即使在天真规则下，直流现在预测也是可行的。这为一个重要课题的研究方向打开了一扇大门。
期刊介绍：
Intelligent Systems in Accounting, Finance and Management is a quarterly international journal which publishes original, high quality material dealing with all aspects of intelligent systems as they relate to the fields of accounting, economics, finance, marketing and management. In addition, the journal also is concerned with related emerging technologies, including big data, business intelligence, social media and other technologies. It encourages the development of novel technologies, and the embedding of new and existing technologies into applications of real, practical value. Therefore, implementation issues are of as much concern as development issues. The journal is designed to appeal to academics in the intelligent systems, emerging technologies and business fields, as well as to advanced practitioners who wish to improve the effectiveness, efficiency, or economy of their working practices. A special feature of the journal is the use of two groups of reviewers, those who specialize in intelligent systems work, and also those who specialize in applications areas. Reviewers are asked to address issues of originality and actual or potential impact on research, teaching, or practice in the accounting, finance, or management fields. Authors working on conceptual developments or on laboratory-based explorations of data sets therefore need to address the issue of potential impact at some level in submissions to the journal.
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