Certificate of attendance
Cass Business School, Bunhill Row, London EC1Y 8TZ
Financial econometrics applies mathematical and statistical tools to financial economics. In recent years, the growing complexity of the financial markets has led to the formulation of several econometric techniques, which could help practitioners to model and forecast the behaviour of market fundamentals.
This course provides a review of and a practical guide to several major econometric methodologies frequently used to model the stylised facts of the financial time series via ARMA models, univariate and multivariate GARCH models, risk management analysis and contagion.
Practical demonstrations of the alternative techniques will be illustrated using the software Stata and asset prices and forex time series.
The course is based on the new publication: Boffelli, S and Urga, G (2015). Financial Econometrics Using Stata. Stata Press Publication. All attendees will receive a complimentary copy of the book.
Day 1 - Modelling the conditional mean of financial time series
- Introduction to financial time series features: distributions of asset returns, stationarity, autocorrelation, heteroscedasticity.
- Univariate models of conditional mean (MA, AR, ARMA, ARIMA, ARMAX). Analysis of the properties and practical applications of identification and diagnostic checking of ARMA models.
- Forecasting with ARMA models.
- Vector Autoregressive models. Analysis of the properties and practical applications of identification and diagnostic checking of VAR models.
- Impulse response function.
Day 2 - Modelling the volatility of financial time series
- Characteristics of asset returns volatility.
- ARCH and GARCH models, Integrated GARCH model, GARCH in mean, GARCHX. Analysis of the properties and practical applications of identification and diagnostic checking of GARCH models.
- Forecasting with GARCH models.
- Asymmetric GARCH models: SAARCH, EGARCH, GJR, TGARCH, APARCH. Estimating the news impact curve.
- Alternative GARCH specifications: Power ARCH, Non-linear GARCH models.