Our web based ARCH & GARCH modelling with Stata course provides an introduction to Stata’s ARCH/GARCH Commands.
The course is ideal for beginner/intermediate level user who wants to learn how to model and forecast financial markets volatility via most used heteroscedasticity models.
The course is based on the recent Stata Press publication by S. Boffelli and G. Urga (2016), Financial Econometrics Using Stata.
The course runs from 13.00-17.00 (London Time)
The course provides an introduction to Stata’s
Taking a “learning-by-doing” approach, we aim to turn intermediate users into confident ones employing plenty of examples and a constant stream of challenging exercises. Participants leave with the know-how and courage to independently perform their own market volatility analysis.
The course is intentionally flexible. The agenda emerges dynamically and depends on the group’s prior background and knowledge of Stata. By the end of the course, all participants will feel comfortable undertaking the following tasks:
- Analysing the main features of asset returns volatility:
- fat tails
- Detecting ARCH effects in asset returns volatility
- Building and estimating GARCH and MGARCH models
- Conducting diagnostic tests to evaluate correct specification of GARCH and MGARCH models
- Modelling asymmetries in volatility (i.e. leverage effect)
- Forecasting with GARCH & MGARCH models
- Automating tasks with do-files
Principal texts for pre & post-course reading:
- Basic prior knowledge of Stata is required.
- Introductory level knowledge of time series econometrics is assumed.
Terms & Conditions
- Student registrations: Attendees must provide proof of full time student status at the time of booking to qualify for student registration rate (valid student ID card or authorised letter of enrolment).
- Additional discounts are available for multiple registrations.
- Delegates are provided with temporary licences for the software(s) used in the course and will be instructed to download and install the software prior to the start of the course.
- Payment of course fees required prior to the course start date.
- Registration closes 5-calendar days prior to the start of the course.
- 100% fee returned for cancellations made over 28-calendar days prior to start of the course.
- 50% fee returned for cancellations made 14-calendar days prior to the start of the course.
- No fee returned for cancellations made less than 14-calendar days prior to the start of the course.