Discovering Traders’ Heterogeneous Behavior in High-Frequency Financial Data
By a News Reporter-Staff News Editor at Technology News Focus -- Fresh data on Economics - Computational Economics are presented in a new report. According to news reporting from Taoyuan, Taiwan, by VerticalNews journalists, research stated, “This paper develops a utility-based heterogeneous agent model for empirically investigating intraday traders’ behaviors. Two types of agents, which consist of fundamental traders and technical analysts, are considered in the proposed model.”
Funders for this research include Ministry of Science and Technology, Taiwan, Chang Gung University.
The news correspondents obtained a quote from the research from the Lunghwa University of Science and Technology, “They differ in the expectation of future asset returns and the perceived risk. This paper incorporates the unique characteristics of high-frequency data into the model for the purpose of having a reliable and accurate empirical result. In particular, a two-test procedure is developed to test the market fractions hypothesis that distinguishes the heterogeneous agent model from the representative agent model. The proposed heterogeneous agent model is estimated on the Taiwan Stock Exchange data. The results suggest that fundamental traders expect the correction of over- or under-pricing in the future. Technical analysts act as contrarian traders. Technical analysts also believe that buyer-initiated (seller-initiated) trading will further raise (lower) future prices. The bid-ask spread has a crucial effect on the investment risk for the technical analysts.”
According to the news reporters, the research concluded: “Moreover, technical analysts are short-sighted, have less market fraction, but perform slightly better.”
For more information on this research see: Discovering Traders’ Heterogeneous Behavior in High-Frequency Financial Data. Computational Economics , 2018;51(4):821-846. Computational Economics can be contacted at: Springer, Van Godewijckstraat 30, 3311 Gz Dordrecht, Netherlands. (Springer - www.springer.com; Computational Economics - http://www.springerlink.com/content/0927-7099/)
Our news journalists report that additional information may be obtained by contacting Y.C. Huang, Lunghwa Univ Sci & Technol, Dept. of Int Business, Taoyuan 33306, Taiwan.
The direct object identifier (DOI) for that additional information is: https://doi.org/10.1007/s10614-016-9643-7. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.
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CITATION: (2018-04-18), Recent Studies from Lunghwa University of Science and Technology Add New Data to Computational Economics (Discovering Traders’ Heterogeneous Behavior in High-Frequency Financial Data), Technology News Focus, 651, ISSN: 0000-0000, BUTTER® ID: 015510488
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