| Summary: | 碩士 === 國立中山大學 === 財務管理學系研究所 === 106 === This paper uses macroeconomic variables, institutional investors data, systematic risk variables and shipping industry related variables to forecast Taiwan transportation stocks returns through the application of Classification and Regression Trees. We use 7 Taiwan transportation stocks and 23 variables from 2002 to 2017 June and examine the prediction accuracy and its performance as a trading strategy of the decision tree model. The results show that the accuracy rate of all decision tree predictions is between 50% and 70%. In addition, by using the decision tree model as the trading strategy between 2012 and 2017, Evergreen Marine was the best of all transportation stocks with a cumulative return rate of 151.79% over a five-year period, followed by Sincere Navigation and Taiwan Navigation with cumulative returns of 72.56% and 25.79%, respectively. In general, the trading strategy based on decision tree prediction is significantly better than the long-term holding strategy with considering transaction costs. Finally, this study links between the rules from decision tree model and the history research, and it also found that the S&P 500 monthly return (lagging behind in the second period), the Taiwan’s Coincident Indicators composite index change rate (lagging behind in the one period), the North Sea Brent Crudev’s oil price change rate (lagging behind the second period), and the Baltic Dry Index (BDI) change rate ( Behind the second period) can be used as a reference for forecasting the direction of Taiwan transportation stocks.
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