標題: An inter-market arbitrage trading system based on extended classifier systems
作者: Hsu, Yu-Chia
Chen, An-Pin
Chang, Jia-Haur
資訊管理與財務金融系 註:原資管所+財金所
Department of Information Management and Finance
關鍵字: Trading rule;High frequency data;Intra-day trading;Data stream;XCS
公開日期: 1-Apr-2011
摘要: Traditionally, the most popular arbitrage strategy is derived from the cost of carry model or by using the econometrics approach. However, these approaches have difficulty in dealing with intra-day 1-min trading data and capturing inter-market arbitrage opportunity in the real world. In this research, we propose computational intelligence approaches based on the extended classifier system (XCS). First, in order to reduce the amount of data, the original data streams of intra-day 1-min trading data are filtered by the conditions of variant price spread relation. XCS is then adopted for knowledge rule discovery. After analyzing the property with domain-specific knowledge that the price of index futures will get close to that of spot products at the time the futures mature, four important factors related to bias, price spread, expiry date, and intraday trading timing are considered as the conditions of XCS to build the inter-market arbitrage model. The inter-market spread of the Taiwan Stock Index Futures (TX) traded at the Taiwan Futures Exchange (TAIFEX) and the Morgan Stanley Capital International (MSCI) Taiwan Index Futures traded at the Singapore Exchange Limited (SGX) are chosen for an empirical study to verify the accuracy and profitability of the model. (C) 2010 Elsevier Ltd. All rights reserved.
URI: http://dx.doi.org/10.1016/j.eswa.2010.09.039
http://hdl.handle.net/11536/9098
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2010.09.039
期刊: EXPERT SYSTEMS WITH APPLICATIONS
Volume: 38
Issue: 4
起始頁: 3784
結束頁: 3792
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