## 3 Empirical Results
### Stock Indices  
In Table 4, we report the forecasting performance of our forecasting models in forecasting the national stock index of each developing economy, using the GPR index and the lagged value of the stock index as regressors. This empirical setting of employing machine learning and the specific GPR index in forecasting the stock markets of developing economies has not been used before in the relevant literature.  
In all countries and horizons, neither the OLS nor the SVR outperform the RW model, except for the SVR model for Mexico, Argentina, and Malaysia in the one-month forecasting horizon. The efficacy of the GPR index in forecasting the national stock index is rather limited, given the transitory nature of geopolitical shocks on stock prices that cannot be detected in our monthly dataset. In Figures 6 and 7, we depict the actual and the forecasted values of the Shanghai Composite index for the one-month and the 12-months ahead forecasting, which represents the index with the largest capitalization among the emerging economies in our sample. As expected, the deviations of the models' forecasts that form the actual data are larger on the yearly than the monthly forecasting horizon.  
Figure 5: Out-of-sample 12-month ahead exchange rate forecasts for Mexico based on the GPR index for the SVR and OLS model for the period Jan-2017 to May-2018.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c c} \hline \hline
**Forecasting Horizons** & \multicolumn{3}{c}{**1 Month**} & \multicolumn{3}{c}{**3 Months**} & \multicolumn{3}{c}{**6 Months**} & \multicolumn{3}{c}{**12 Months**} & \multicolumn{3}{c}{**24 Months**} \\ \hline Country & OLS & SVR & RW & OLS & SVR & RW & OLS & SVR & RW & OLS & SVR & RW & OLS & SVR & RW \\ \hline Turkey & 7.84 & 7.70 & 7.63 & 13.33 & 12.85 & 12.10 & 22.26 & 21.80 & 17.35 & 35.86 & 35.07 & 24.18 & 66.99 & 47.70 & 27.88 \\ Mexico & 3.64 & 3.62 & 3.68 & 6.90 & 7.09 & 6.63 & 11.31 & 11.69 & 10.16 & 21.18 & 22.32 & 15.76 & 40.06 & 39.75 & 21.64 \\ Korea & 5.55 & 5.54 & 5.47 & 10.53 & 10.52 & 10.25 & 16.25 & 16.55 & 14.85 & 24.19 & 24.72 & 22.12 & 26.46 & 26.28 & 26.23 \\ Russia & 5.62 & 5.54 & 5.30 & 12.04 & 11.60 & 10.63 & 20.33 & 19.55 & 17.09 & 33.08 & 32.08 & 23.65 & 40.08 & 19.85 & 19.90 \\ India & 5.41 & 5.48 & 5.39 & 9.86 & 10.04 & 9.58 & 15.30 & 15.41 & 13.87 & 24.83 & 24.22 & 20.36 & 35.30 & 35.86 & 25.75 \\ Brazil & 5.20 & 5.21 & 5.09 & 10.00 & 10.05 & 9.63 & 15.57 & 16.03 & 14.40 & 22.03 & 23.28 & 19.68 & 32.90 & 31.02 & 21.09 \\ China & 5.83 & 6.00 & 5.80 & 11.95 & 12.02 & 11.44 & 19.25 & 18.44 & 17.76 & 24.57 & 23.50 & 25.73 & 41.07 & 33.80 & 30.19 \\ Indonesia & 5.54 & 5.56 & 5.52 & 11.15 & 11.24 & 10.83 & 17.05 & 17.22 & 16.22 & 27.46 & 29.24 & 23.62 & 33.54 & 34.33 & 28.08 \\ Saudi Arabia & 6.00 & 6.45 & 5.83 & 11.54 & 12.50 & 11.18 & 20.02 & 21.40 & 16.98 & 38.68 & 40.42 & 26.67 & 75.58 & 70.66 & 30.84 \\ Argentina & 7.63 & 7.49 & 7.39 & 13.86 & 13.86 & 13.81 & 21.97 & 22.00 & 21.68 & 37.13 & 36.42 & 34.51 & 46.62 & 50.09 & 42.79 \\ Thailand & 2.80 & 2.83 & 2.72 & 5.54 & 5.83 & 5.08 & 8.41 & 8.50 & 7.61 & 10.50 & 10.80 & 11.10 & 12.47 & 18.90 & _7.69_ \\ Israel & 3.74 & 3.75 & 3.71 & 7.41 & 7.78 & 7.18 & 12.45 & 12.58 & 11.04 & 27.13 & 27.17 & 16.98 & 29.11 & 30.16 & 21.04 \\ Malaysia & 1.77 & 1.75 & 1.76 & 2.93 & 2.96 & 2.85 & 4.02 & 3.96 & 3.72 & 3.18 & 7.00 & 6.30 & 7.93 & 9.06 & 8.64 \\ Philippines & 4.22 & 4.13 & 4.13 & 8.57 & 8.46 & 8.02 & 14.76 & 14.60 & 13.02 & 23.26 & 22.83 & 19.49 & 27.43 & 31.67 & 25.17 \\ \hline \hline \end{tabular} Note: All values are percentages.  
\end{table}
Table 4: Stock Indices out-of-sample forecasting accuracy—MAPE.