S&P 500 Index and Volatility Forecast of Chinese Stock Market
DOI:
https://doi.org/10.54691/bcpbm.v26i.2009Keywords:
Volatility; Autoregressive Model; Out of Sample Prediction.Abstract
The main purpose of this article is to examine the role of the S&P 500 index in predicting the volatility of China's stock market. Our work is based on the autoregressive model (AR). We further extend this simple benchmark model by adding the volatility of the S&P 500 index. Intrasample regression shows that after adding this indicator, the overall goodness of fit of the model is rising, the explanatory ability is enhanced, and the added variables are also very significant. The out of sample prediction shows that, in terms of statistical test, the extended model has a positive out of sample R-square compared with the benchmark model, and has passed the CW test; In terms of economic test, we find that the extended model has positive CER and Sharp Ratio (SR) compared with the benchmark model. The out of sample predictions of these two aspects show that the newly added S&P 500 index has a good prediction effect. In addition, we also conducted various robustness tests, such as replacing the previous dependent variable (Shanghai Stock Exchange Index) with the CSI 300 index, replacing the previous extended window with a rolling window for prediction, and extending the previous single period prediction to multi period prediction. In the multi period forecast, we found that the S&P 500 index is only effective in a short period, for example, within 3 months, but cannot play a predictive role when it is extended to 6 months.
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