# EL-MTSA: Stock Prediction Model Based on Ensemble Learning and Multimodal Time Series Analysis
## 4 Experimental Results and Discussion
### Experimental Results and Analyses
#### 4.4.5 Comparative Analysis of Simulated Investments  
In this section, we conducted simulated investments based on the predictive results of the EL-MTSA model and performed a comprehensive comparative analysis against the buy-and-hold strategy and the martingale model. Through this comparison, we aim to  
Figure 8: Comparison experimental results of data volume on different stock datasets. rigorously evaluate the effectiveness and advantages of the EL-MTSA model in forecasting stock prices, providing insights into its practical applicability in financial markets. In this subsection, several key parameters were initialized to establish the trading environment. The initial capital was set at RMB 100,000, with the current capital also initialized to this amount. The number of shares held was initially set to 0, indicating no equity ownership at the outset. The value of the investment portfolio was recorded in a list, starting from the initial fund value of RMB 100,000. Slippage was set at 0.1%, representing the potential deviation between the expected and actual execution prices due to market volatility. Additionally, a fixed transaction fee of RMB 5 per trade was applied to account for brokerage charges. We utilized the following performance metrics to evaluate the performance of the three strategies:  
1. Final portfolio value (FPV) is the total value of the investment portfolio at the end of the simulation period, reflecting the cumulative growth of the initial capital. 2. Total profit (TP) is the absolute monetary gain achieved over the investment horizon, calculated as the difference between the final portfolio value and the initial capital. 3. Maximum drawdown (MDD) is the largest peak-to-trough decline in portfolio value during the simulation period, expressed as a percentage of the peak value. This metric quantifies the worst-case loss and serves as a critical measure of downside risk. 4. Sharpe ratio (SR) is a risk-adjusted performance measure that evaluates the excess return per unit of risk, with risk represented by the standard deviation of portfolio returns. This metric provides insights into the efficiency of returns relative to the level of risk undertaken. These metrics collectively offer a comprehensive assessment of the strategies' profitability, risk exposure, and risk-adjusted performance, ensuring a robust evaluation framework. Table 5 presents the evaluation metrics for the three distinct strategies, providing a comparative analysis of their performance. As shown in Table 5, the final portfolio value (FPV) of the EL-MTSA model's predictive investment is RMB 151,876.98, which is 6.51% higher than that of the buy-and-hold strategy and 21.37% higher than that of the martingale model. This indicates that the EL-MTSA model possesses a certain advantage in predicting price movements. The total profit (TP) of the EL-MTSA model is RMB 51,876.98, surpassing the buy-and-hold strategy by 21.78% and the martingale model by 106.43%. The annualized return of the EL-MTSA model is significantly higher than those of the other two strategies, demonstrating its potential in investment applications. The Sharpe ratio (SR) of the EL-MTSA model is 3.76, compared to 1.42 for the buy-and-hold strategy and 1.16 for the martingale model. The higher Sharpe ratio of the EL-MTSA model suggests superior risk-adjusted returns, highlighting its efficiency in generating excess returns per unit of risk. The maximum drawdown (MDD) of the EL-MTSA model is 3.59%, significantly lower than the 15.82% of the buy-and-hold strategy and the 10.18% of the martingale model. The relatively lower maximum drawdown of the EL-MTSA model indicates its robust performance in risk management and downside protection.