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Research Article

Ensemble Classifier for Stock Trading Recommendation

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Article: 2001178 | Received 18 Jul 2021, Accepted 28 Oct 2021, Published online: 26 Nov 2021

Figures & data

Figure 1. Process.

Figure 1. Process.

Table 1. Technical indicators used

Figure 2. Determining classd from δd.

Figure 2. Determining classd from δd.

Table 2. Final decision of trend prediction results

Figure 3. Trading recommendation based on classd.

Figure 3. Trading recommendation based on classd.

Figure 4. Algorithm for trading recommendation.

Figure 4. Algorithm for trading recommendation.

Table 3. Characteristics of stocks used in the experiment

Figure 5. Price charts of all stocks in dataset A (2014–2018). Training and testing datasets are shown in green and blue colors.

Figure 5. Price charts of all stocks in dataset A (2014–2018). Training and testing datasets are shown in green and blue colors.

Figure 6. Price charts of all stocks in dataset B (2015–2019). Training and testing datasets are shown in green and blue colors.

Figure 6. Price charts of all stocks in dataset B (2015–2019). Training and testing datasets are shown in green and blue colors.

Figure 7. Price charts of all stocks in dataset C (2016–2020). Training and testing datasets are shown in green and blue colors.

Figure 7. Price charts of all stocks in dataset C (2016–2020). Training and testing datasets are shown in green and blue colors.

Figure 8. Proportions of % price changes.

Figure 8. Proportions of % price changes.

Table 4. Results of accuracy values and returns of trading

Figure 9. Comparative returns for some largest stocks.

Figure 9. Comparative returns for some largest stocks.

Figure 9. Continued.

Figure 9. Continued.

Table 5. Return Surpluses ΔX = RX – RBH

Table 6. Averages of return surplus (ΔX = RX – RBH), Sharpe ratios (Sr), and accuracy (Ac)

Table 7. Averages of returns from B&H (RBH)

Table 8. Average ranks of return

Table 9. Correlation coefficients (Cor) of return and accuracy