Explorations in LCS Models of Stock Trading
IWLCS '01 Revised Papers from the 4th International Workshop on Advances in Learning Classifier Systems
Cognitive systems based on adaptive algorithms
ACM SIGART Bulletin
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Stock market trading rule discovery using pattern recognition and technical analysis
Expert Systems with Applications: An International Journal
A TSK type fuzzy rule based system for stock price prediction
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Classifier fitness based on accuracy
Evolutionary Computation
A type-2 fuzzy rule-based expert system model for stock price analysis
Expert Systems with Applications: An International Journal
Flexible least squares for temporal data mining and statistical arbitrage
Expert Systems with Applications: An International Journal
Trading rule discovery in the US stock market: An empirical study
Expert Systems with Applications: An International Journal
Computational intelligence for evolving trading rules
IEEE Transactions on Evolutionary Computation - Special issue on computational finance and economics
A Hybrid System Integrating a Wavelet and TSK Fuzzy Rules for Stock Price Forecasting
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Hi-index | 12.05 |
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.