Presented By: Dr. Malvina Marchese (Cass Business School, City, University of London)

At times of great uncertainty for financial markets, this course provides participants with an understanding of the time series methods involved in modelling and forecasting financial markets volatilities. Participants will learn how to build, estimate and assess alternative models of volatility of financial time series. Each concepts will be explained from an econometric perspective and by means of many examples and applications in Eviews or Oxmetrics

Presented By: Dr. Giovanni Cerulli, IRCrES-CNR

Recent years have witnessed an unprecedented availability of information on social, economic, and health-related phenomena. Researchers, practitioners, and policymakers have nowadays access to huge datasets (the so-called “Big Data”) on people, companies and institutions, web and mobile devices, satellites, etc., at increasing speed and detail.

Presented By: Dr. George Naufal (Texas A&M University)

Time series data are nowadays collected for several phenomena in social and empirical sciences. Initially collected at year or quarter level, time series data are now used by marketing analytics, financial technology, and other fields in which data are collected at much smaller intervals (daily, hourly and even by the minute). This course focuses on the fundamental concepts required for the analysis, modelling and forecasting of time series data and provides an introduction to the theoretical foundation of time series models alongside a practical guide to the use of time series analysis techniques implemented in Stata 15. The course is based on the textbook by S. Boffelli and G. Urga (2016), Financial Econometrics Using Stata, Stata Press Publication.

Presented By: Dr. Lorenzo Trapani (Cass Business School)

The course offers an intermediate/advanced level overview of stationary VARs, cointegrated VARs and the VECM, and an introduction to Structural VARs (SVARs). It is a mixture, with equivalent weights, of methodology and practice, and each session is complemented by a data example. The SVAR part is also based on discussing several examples which are commonly encountered in macroeconometrics and monetary economics.

Presented By: Dr. Giovanni Cerulli, IRCrES-CNR

This course is for professionals and researchers from all academic disciplines who wish to improve their use of Stata.

Econometric modelling for causal inference and program evaluation have witnessed a tremendous development in the last decade, with new approaches and methods addressing an expanding set of challenging problems, both in medical and the social sciences. This course covers some recent developments in causal inference and program evaluation using Stata.

Presented By: Dr. Melvyn Weeks (University of Cambridge)

The course has been adapted to be delivered interactively and online. The course is made up of two-parts, with each part being delivered over two-consecutive days. The course covers topics at the intersection of machine learning and econometrics with a mix of theory and applications. Using Breiman’s (2001) notion of two cultures in the use of statistical modelling, we start with a review of the fundamental differences between machine learning and econometrics.

Presented By: Dr. George Naufal (Texas A&M University)

Time series data are nowadays collected for several phenomena in social and empirical sciences. Initially collected at year or quarter level, time series data are now used by marketing analytics, financial technology, and other fields in which data are collected at much smaller intervals (daily, hourly and even by the minute). This course focuses on the fundamental concepts required for the analysis, modelling and forecasting of time series data and provides an introduction to the theoretical foundation of time series models alongside a practical guide to the use of time series analysis techniques implemented in Stata 15. The course is based on the textbook by S. Boffelli and G. Urga (2016), Financial Econometrics Using Stata, Stata Press Publication.

Presented By: Dr. Malvina Marchese (Cass Business School, City, University of London)

Presented By: Fiona Wiltshier (Official NVivo Trainer)

The second of 3 modules on the Nvivo software. This session includes a Q&A from the previous session, and covers aspects such as capturing characteristics, working with surveys and social media and exploring your data through queries

Please note that this training will be hosted on Windows OS. If you wish to request a Mac OS demonstration, please contact us.

This session runs from 12:00-15.00 GMT.

Presented By: Dr. Vincent O’Sullivan (Lancaster University)

This comprehensive webinar is hosted through Zoom and runs over a total of 9 hours, with 4 hours each day (2 in the morning and 2 in the afternoon) with an extra Q&A session on the second day.

This course is for data managers and researchers who wish to learn Stata programming concepts and skills.

Presented by Prof. Christopher F Baum, Boston College, USA and Dr. Malvina Marchese, Cass Business School, London

This course is taught in two sections. The first, is for Stata users–professionals and researchers from all academic disciplines–who would like to use Stata programming techniques to enhance the efficiency and reliability of their research. The course assumes familiarity with Stata’s command-line interface and the use of do-files and log files to produce reproducible results. The participants will learn how to use do-file programming techniques effectively, including topics such as local and global macros, r-returns and e-returns, implicit and explicit loops and debugging techniques.

The second, is for users who have completed the companion course Introduction to Stata Programming and would like to use more advanced features of the Stata and Mata programming languages. The course assumes familiarity with Stata’s command-line interface and the use of do-files and log files to produce reproducible results. The participants will learn how to implement new Stata commands with ado-files and egen functions. Mata programming techniques will illustrate how this language can be used to simplify and accelerate computations.

Presented By: Dr. Austin Nichols

This course is for professionals and researchers from all academic disciplines who wish to improve their use of Stata.

Participants will be introduced to Stata and causal inference using practical examples. The fundamentals of data analysis and visualization will also be taught, using appropriate Stata commands and programming techniques