Training Calendar

Modelling & Forecasting Market Risk with OxMetrics & XlModeler (Excel add-in)

Cass Business School, Bunhill Row, London EC1Y 8TZ Half day (11th September 2019 - 12th September 2019) OxMetrics Intermediate
Finance, Forecasting, Time series


The course will cover volatility modelling and forecasting. Traditional regression tools have shown their limitation in the modelling of financial time-series. Assuming that only the conditional mean could be changing with covariates while the variance remains constant over time often revealed to be an unrealistic assumption. Indeed, it is now widely accepted that financial returns are heteroskedastic. Said differently, the main stylised feature of financial time series is that large changes tend to be followed by large changes, of either sign, and small changes tend to be followed by small changes. Since the seminal paper of Engle (1982), autoregressive moving average (ARMA) models have been extended to essentially equivalent models for the variance. The framework, its basic concepts and main implications will be sketched.

The following topics will be described in the course:

  • The ARCH model and some of its most important extensions like leverage effect, Generalized Autoregressive Scores, multivariate GARCH models, value-at-risk forecasting, back-testing, etc.
  • Lectures will be illustrated by empirical forecasting exercises using OxMetrics and the XlModeller, a new add-in for Excel that allows to estimate sophisticated models in Excel.


Day 1

Session 1: Introduction to univariate GARCH models and testing for return predictability

  • stylized facts of financial time series
  • general framework of univariate ARCH models
  • random walk hypothesis
  • empirical illustrations

Session 2: ARCH models

  • properties of ARCH models
  • estimation
  • empirical illustrations

Session 3: GARCH models

  • leverage effect
  • long-memory
  • prediction
  • non-normal distributions
  • empirical illustrations

Session 4: Generalized Autoregressive Score (GAS) Models

Day 2

Sessions 1 & 2

  • non-normal distributions
  • Value-at-risk
  • empirical illustrations

Session 3-4: Multivariate GARCH models

  • BEKK, CCC, DCC, DECO and OGARCH models
  • empirical illustrations

Pre-Course Reading

  • Handbook of Volatility Models and Their Applications, Bauwens, L. Hafner, C. and Laurent, S. ed. (within the Wiley Handbook in Financial Engineering and Econometrics series), 2012.

Post-Course Reading

  • G@RCH8, Estimating and Forecasting ARCH Models, London: Timberlake Consultants Press.


  • Intermediate level knowledge of econometrics and time series econometrics.

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.
  • Cost includes course materials, lunch and refreshments.
  • Delegates are provided with temporary licences for the principal software package(s) used in the delivery of the course. It is essential that these temporary training licenses are installed on your computers prior to the start of the course. We can provide laptops to attendees. Prior notice is required and additional charges will apply.
  • Should you need assistance in locating hotel accommodation in the immediate vicinity of the course location, please notify us at the time of booking.
  • 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 more than 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.

The number of attendees is restricted. Please register early to guarantee your place.

  •  CommercialAcademicStudent
    1-Day Pass (11/09/2019 - 12/09/2019)
    2-Day Pass (11/09/2019 - 12/09/2019)

All prices exclude VAT or local taxes where applicable.

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