The International Institute of Forecasters sponsors workshops, each of which focuses on a specific forecasting theme. The purpose of these workshops is to hold smaller, informal meetings where experts in a particular field of forecasting can discuss forecasting problems, research, and solutions. There is generally a nominal registration fee associated with attendance. Following the usual refereeing process, papers from the workshops can be included in a special issue of the International Journal of Forecasting. If you are interested in hosting a workshop, contact Aris Syntetos, IIF Director, or click here for workshop guidelines.
26th IIF Workshop: Forecasting for Social Good | Kedge Business School, Bordeaux, France, June 11-12, 2020
Due to the COVID19 outbreak, we are postponing the workshop. We believe that this is the prudent decision given the circumstances. The current proposal is to hold the workshop June 30 – July 1, 2021.
The goal of this workshop is to improve the research and practice in issues related to forecasting for social good by: facilitating interactions between practitioners, researchers, and policy makers to develop a cohesive and sustainable network of international collaborations with a focus on issues related to forecasting for social good; promoting the development of new methodology and metrics to address the specific challenges related to forecasting for social good; providing professional development to policy makers; gaining a better understanding of the available data, challenges in data acquisition, and the uncertainty present in the data used to produce forecasts; and, addressing the ethical issues related to the use of forecasting methods for problems that impact society.
27th IIF Workshop: Feature-based Time Series Forecasting | Ordos City, China, August 2021
Feature-based forecasting aims to use meta-learning to produce more accurate forecasts based on time series features. As early as the 1970s, Adam (1973) argued that the statistical characteristics of time series can be used to improve forecasting performances. Later literature supported this argument. Recently, related feature-based algorithms have been developed with great success, while some key issues remain to be tackled including automatic feature extraction and selection, feature-based density forecasting, forecasting related time series with features, time series generation based on features, and minimum forecast model pools for forecast model averaging. The proposed workshop aims to bring people together with diverse expertise and facilitate new research collaborations.
This is a series of ongoing workshops on forecasting using R in developing countries. The aim of the project is to ‘train the trainers’ in the form of university students, academics and professionals on the principles of forecasting using R software to support decision making. The ultimate goal of this project is to train 400 individuals, over 5 years in 20 developing countries in the world. The first series of workshops have already been offered in 2017-18. The workshops are given by Dr. Bahman Rostami-Tabar, Assistant Professor in Management Science at Cardiff Business School. To organise a workshop in your country, contact [email protected]