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The main purpose of this thesis is to develop a steady Program Trading System of Taifex Index Futures. Various collections of indicators are generated based on AiSM futures platform. By means of artificial intelligence, an effective program trading system is developed according to Taifex 90-M index data by analyzing the properties of index fluctuation. Program Trading Models can be identified based on evaluation indicators. In this paper, selective models Taifex_A to Taifex_E have been proposed. By analyzing the evaluation indicators, a single model is sensitive to a certain period of time which may not fit to the model. Such sensitivity may cause great loss and high pressure to the model users. Therefore, we proposed a mean-oriented multi-model trader to diversify the risk with the potential of extra cost.
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