United Kingdom, London

Factor Models in Time Series with Applications in Macroeconomics and Finance

when 20 August 2018 - 24 August 2018
language English
duration 1 week
fee GBP 975

Large datasets are becoming increasingly available to researchers and practitioners in many disciplines. In particular, during this “big data” revolution the analysis of high–dimensional time series has become one of the most active subjects of modern statistical methodology with applications in various areas of social science including finance, macroeconomics, and econometrics. Although the value of information is unquestionable, the possibility of extracting meaningful and useful information out of this large amount of data is also of great importance. To this end, several new analytical and computational techniques have been developed under the name of factor models.
The aim of this course is to give an introduction to factor models in time series analysis by teaching students the basic analytical methods and their applications to macroeconomics and finance via the use of Matlab software. These models are widely used in central banks for forecasting key macroeconomic indicators such as GDP and inflation. They are also used to study the impact of economic policies on economic activity and in validating models of the economy. Financial institutions adopt factor models for risk management.

The aim of this course is to give an introduction to factor models in time series analysis by teaching students the basic analytical methods and their applications to macroeconomics and finance via the use of Matlab software. These models are widely used in central banks for forecasting key macroeconomic indicators such as GDP and inflation. They are also used to study the impact of economic policies on economic activity and in validating models of the economy. Financial institutions adopt factor models for risk management.

Course leader

Mr Matteo Barigozzi

Target group

This course is designed for postgraduates, academics and professionals with an interest in big data analysis and who have some analytical background in time series analysis.

Course aim

After successful completion of this course, participants should be able to:
identify macroeconomic and/or financial policy problems that can benefit from factor analysis and consequently identify the appropriate dataset and methodology to be used
extract and analyse relevant information from large datasets
apply the analytical tools of time series analysis to the data using Matlab software
conduct empirical research in time series, i.e. to interpret the information extracted from the data in a critical way also in relation to the existing literature forecast time series using many predictors.

Credits info

Students who wish to receive credit for their course will need to contact either their Study Abroad Office or the office in their university that deals with external credit. It is up to students' home institutions as to how much credit is awarded but the Methods Programme Office is happy to provide any necessary information to your registry or academic advisor, to help them evaluate the courses.

Fee info

GBP 975: Course fees are approximate only, based on 2017 fees. These are likely to increase slightly for 2018
GBP 1660: Course fees are approximate only, based on 2017 fees. These are likely to increase slightly for 2018

Scholarships

Previous students of LSE may be eligible for a 15% discount on their tuition fees.