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This research used Bollinger channel and Keltner channel, combined with a filter net and exiting mechanism, according to the classification parameters and continuous parameters concept design of multiple sub-strategies. Then, choosing Taiwan 50 ETF, Taiwan dividend plus ETF, Taiwan mid-cap 100 ETF, TWSE corporate governance 100 ETF, the stock of listed company and, the stock of listed company in OTC, for the six data sets to implement multiple sub-strategies optimization, after optimizing will produce a huge amount performance information of sub-strategies, and further using the algorithm of plateau automatic searching to look for high net profit performance of plateau.
After looking for the high performance plateau, according to the continuous parameters characteristics of the sub-strategies, provided multidimensional plateau visualization chart to evaluate the internal relation of the sub-strategies. According to classification parameters characteristics of the sub-strategies, provided heatmap visualization chart of companies to evaluate the external relation of the sub-strategies. According to the comparative characteristics of the stock, provided the interactive parallel coordinate visualization chart of geometric figures to do stock and stock comprehensive evaluation.
In addition, this research also integraed the core process and functions, and built into the Python Django automation platform, through automation of the advantages, initiative on computing performance results, initiative on analyzing a huge of performance data, finally initiative on providing visualization charts, let investor can see the implicit relevance and significance of huge amounts of performance data by visualization charts to help investors use superior stock and sub-strategies. | en_US |