Siwen Liu

Passionate about quantitative research and data analysis.

• Involved in the internal program regarding fertility prediction as a thesis student. The VAR model and the ordinary linear regression model are constructed based on Google Trends and Twitter data to project fertility.
• Developed a semi-automated fertility keywords generation and selection method based on Natural language processing to avoid time cost and bias by subjective selection.

• Constructed two SARIMA models and achieved 12 lags(3 years) ahead GDP prediction with the 95% prediction interval.
• Compared and selected the best model with MAE of 94678.57 and RMSE of 250.7 and tested the model differences by Diebold-Mariano test.
• Integrated and constructed VAR model between two time series (GDP and tax receipt) and observed the incremental explanatory power of tax receipt in the prediction of GDP.