Course 1: Time Series Modelling and Analysis
Date: Location: Course duration: Software: Level: Delivered by: Course Code:	21-23 July 2013 Clare College, University of Cambridge, UK 2.5-days STAMP Intermediate Prof. Andrew Harvey, University of Cambridge CSS-120-UK

This 2.5-day course forms part of our 2013 Econometrics Summer School at the University of Cambridge.

Contents

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Course overview

The course will show how economic and financial time series can be modelled and analysed. The aim is to provide understanding and insight into the methods used, as well as explaining the technical details. Statistical modelling will be demonstrated using the STAMP package and participants will be given the opportunity to use the package in class. Participants are expected to have taken an introductory course in econometrics or time series analysis. The references to Time Series Models (TSM) in the course outline give an indication of the material covered. Some participants may find some of the maths difficult. However, the lectures will stress the concepts and the implications for applied work and the STAMP package.

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Agenda

For full course agenda, please see the following Time Series and Modelling (PDF).

Day One

1. Introduction. Stationary time series. Unobserved components and signal extraction. TSM, chs 1,2,3.
2. Time Series Models. ARIMA models. Structural time series models. Explanatory variables and intervention analysis. TSM, ch 5.
3. STAMP package. State space models and the Kalman filter. Signal extraction. Missing observations and other data irregularities. TSM, ch 4.

Day Two

1. Spectral analysis. Spectra of ARMA processes; stochastic cycles; linear filters; estimation of spectrum. TSM, ch6, sections 1-7.
2. Trends and cycles. Analysis of the e¤ects of moving average and differencing operations. Hodrick-Prescott and band-pass filters. TSM, ch6, sections 5, 6.
3. STAMP package. Seasonality.
4. Multivariate time series models. Common trends and co-integration; control groups. TSM, ch 7.

Day Three

1. Nonlinear models. Financial econometrics; distributions of returns, stochastic volatility and GARCH.
2. Dynamic conditional score models. Multivariate volatility models. Copulas. TSM, ch8, Taylor, chs 8-11, 15, Harvey (2013).

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Prerequisites

Basic knowledge of econometrics and time series analysis.

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Accommodation

Accommodation will be available for the duration of the Summer School at Memorial Court (part of Clare College, University of Cambridge). Click here for the digital brochure (PDF) »

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Prices

Cost (per participant):

The following prices also include accommodation at the Memorial Court site on Clare College (see Accommodation for more information).

Non-academic (single course)	£1,400.00
Non-academic (2 courses)	£2,150.00
Non-academic (3 courses)	£2,750.00
Academic and Student (single course)	£675.00
Academic and Student (2 courses)	£1,125.00
Academic and Student (3 courses)	£1,650.00

• All costs exclude local taxes, where applicable
• 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 enrollment)
• Additional discounts are available for multiple registrations (non-academic only)
• Cost includes course materials, lunch and refreshments (please advise us if you have any dietary requirements)

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

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Registration

We welcome delegates to find out more and register for the course by contacting our sales and training team either by email: training@timberlake.co.uk, phone: +44 (0) 20 8697 3377 or by filling out an online registration form.

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Terms & Conditions

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

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