Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/42980
Title: Technical Trading Behaviour: Evidence from Chinese Rebar Futures Market
Authors: Liu, Guanqing
First Published: 10-Sep-2018
Publisher: Springer Verlag (Germany) for Society for Computational Economics
Citation: Computational Economics, 2018
Abstract: Technical Traders adopt mathematical methods to formulate various technical trading rules on their trading strategies. This paper utilises two unique datasets—individual and market tick-by-tick data—to disclose the categories and characteristics of technical traders’ strategies in Chinese rebar futures market. Firstly, we use a simple multiple regression model to filter technical traders in individual dataset. By using market dataset to generate dummy signals according to six popular kinds of technical rules, we created dummy trading directions as benchmark for real trading actions. Based on the similarity between dummy signals with different technical rules and traders’ real actions, we employ k-means algorithm to classify technical traders. Through these empirical works, technical traders in my dataset are classified into 11 groups. Finally, on the basis of 11 clusters’ coordinates, the features of technical strategies in each group are summarised.
DOI Link: 10.1007/s10614-018-9851-4
ISSN: 0927-7099
eISSN: 1572-9974
Links: https://link.springer.com/article/10.1007%2Fs10614-018-9851-4
http://hdl.handle.net/2381/42980
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © the authors, 2018. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Appears in Collections:Published Articles, Dept. of Economics

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