Financial Econometrics Coursework: Time Series Analysis and Modeling

This report presents a comprehensive analysis of financial time series data using econometric techniques. It begins by selecting two time series (X1 and X2) and applying a step-by-step approach to model identification, estimation, and diagnostic testing. The analysis includes descriptive statistics, unit root tests (Augmented Dickey-Fuller), and the construction of AR models (AR(2) for X1 and AR(4) for X2). The report then evaluates the models using in-sample and out-of-sample forecasting, calculating RMSE to assess model performance. The second part of the report expands to VAR modeling, exploring the impact of oil price shocks on financial variables like EPU, NASDAQ, and VIX. It performs unit root tests, lag selection, and VAR estimation, followed by Granger causality tests to determine the relationships between the variables. The report provides detailed interpretations of the estimated coefficients and statistical results, including the impact of oil price changes on economic policy uncertainty, stock market indices, interest rate spreads, and financial market volatility. The analysis demonstrates the application of econometric methods for understanding and forecasting financial time series.