# The Stock Index Prediction Based on SVR Model with Bat Optimization Algorithm
## 5 Empirical Research and Result Analysis
### Comparison and Analysis of Long-Term Forecast Results

Table 13: Comparison of long-term forecast results. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Index** & **Evaluation Index** & **BA-SVR** & **Poly-SVR** & **Sigm-SVR** \\ \hline \multirow{4}{*}{SZSE B shares} & RMSE & 0.0612 & 0.1067 & 0.0604 \\ \cline{2-5}  & MAE & 0.0416 & 0.0931 & 0.0430 \\ \cline{2-5}  & MAPE & 0.1007 & 0.2422 & 0.1050 \\ \hline \multirow{4}{*}{SZSE} & RMSE & 0.3559 & 0.4804 & 2.9184 \\ \cline{2-5}  & MAE & 0.2728 & 0.3623 & 2.1387 \\ \cline{2-5}  & MAPE & 0.2641 & 0.3544 & 2.0001 \\ \hline \multirow{4}{*}{SZSE A shares} & RMSE & 0.3588 & 0.4779 & 2.9256 \\ \cline{2-5}  & MAE & 0.2749 & 0.2605 & 2.1438 \\ \cline{2-5}  & MAPE & 0.2661 & 0.3526 & 2.0037 \\ \hline \multirow{4}{*}{SME} & RMSE & 0.5440 & 0.6926 & 3.9422 \\ \cline{2-5}  & MAE & 0.4461 & 0.5099 & 2.9136 \\ \cline{2-5}  & MAPE & 0.3960 & 0.4339 & 2.4305 \\ \hline \multirow{4}{*}{SME 300} & RMSE & 0.3698 & 0.4028 & 2.4111 \\ \cline{2-5}  & MAE & 0.2891 & 0.3110 & 1.7876 \\ \cline{2-5}  & MAPE & 0.2817 & 0.3119 & 1.7096 \\ \hline \multirow{4}{*}{SME CI} & RMSE & 0.2343 & 0.3069 & 2.0145 \\ \cline{2-5}  & MAE & 0.1651 & 0.2358 & 1.4856 \\ \cline{1-1} \cline{2-5}  & MAPE & 0.1805 & 0.2593 & 1.5401 \\ \hline \hline \end{tabular}
\end{table} 
Table 12: _Cont._and the SVR model of the Sigmoid kernel function. In addition, the combined analysis of the 18 stock indices under the three forecasting models for forecasting performance evaluation model, and the results are shown in Table 13. On average, the long-term forecasting results show that BA-SVR has a better forecasting performance improvement compared with the polynomial kernel function SVR model with default free parameters and the Sigmoid kernel function SVR model. Further, the changes in the BA-SVR model's prediction performance in the short, medium and long term are then compared together. According to Tables 6, 9 and 12, the forecasting performance of the BA-SVR model decreases to different degrees between different groups. Taking the SSE Composite Index as an example, the MAPE of the short-term BA-SVR model is 0.0329, the MAPE of the medium-term BA-SVR model is 0.0609, and the MAPE of the long-term BA-SVR model is 0.1756. The MAPE shows a gradual increase, which corresponds to the decrease in forecasting performance. This quality also matches with the average prediction performance of the BA-SVR model in the second column of Tables 7, 10 and 13. Unlike the polynomial kernel function SVR model and the Sigmoid kernel function SVR model, this trait does not appear significantly, and for both control models, in some groups, there is a higher long-term prediction performance than the short-term and medium-term. Here is a comprehensive comparison of the changes in the performance of the BA-SVR model in the short, medium and long term. According to Tables 6, 9 and 12, the predictive performance of BA-SVR models in different groups has decreased to varying degrees. Take the above stock index as an example, the MAPE of the short-term BA-SVR model is 0.0329, the MAPE of the medium-term BA-SVR model is 0.0609, and the MAPE of the long-term BA-SVR model is 0.1756. It can be clearly found that MAPE is showing a gradual upward trend, which corresponds to the decrease in prediction performance. Coincidentally, this characteristic also matches the average predicted performance of the BA-SVR model in the second column of Tables 7, 10 and 13. In contrast, the polynomial kernel function SVR model and the Sigmoid kernel function SVR model do not have this characteristic, and the long-term prediction performance of these two comparison models is higher than that of the short-term and medium-term in some groups. For the empirical investigation of the forecasting ability of the bat algorithm optimized SVR model constructed in this paper in different periods, based on the 18 mainland China stock indices and the full sample interval selected in this paper, the following conclusions can be drawn.