IIF-SAS Grant to Promote Research on Forecasting
For the twenty-second year, the IIF, in collaboration and with financial support from SAS®, is proud to announce financial grants for research on how to improve forecasting methods and business forecasting practice. The awards for 2024 will be (2) $10,000 grants; in Business Applications and Methodology. The deadline for application is October 12, 2024. For full details on the research grant, click here. All questions can be directed to the IIF Business Manager. The next call for submissions will be in August 2025.
Applications must include:
- Description of the project (4 pages max)
- Brief CV, including references (4 pages max)
- Budget and work-plan for the project (1 page max)
- Letter of support is required for students. This should be from co-author, advisor or professor.
IIF-SAS Grant Application
Complete the form below and upload the required documents.
"*" indicates required fields
Award Recipients
2023
Kristen Schell, Carleton University, with joint appointment at Rensselaer Polytechnic Institute; Mario Arrieta-Prieto, National University of Colombia, for the project proposal in the category of Methodology, Spatio-temporal Probabilistic Forecasting of Circular Variables: Enhancing the Value of Wind Power Prospective Models by Incorporating Wind Direction Probabilistic Forecasts
Xuguang Simon Sheng, American University, for the project proposal in the category of Applications, A Novel Method for Eliciting Business Inflation Expectations
2022
Kin G. Olivares and Cristian Challu, Carnegie Mellon University, for the project proposal in the category of Methodology, Transferability of Neural Forecast Methods
Sushil Punia, Indian Institute of Technology Kharagpur, for the project proposal in the category of Applications, Ridership Forecasting in Public Transit Systems for Effective Operations Management
2021
Shanika L Wickramasuriya, University of Auckland; Kasun Bandara, University of Melbourne; Hansika Hewamalage, RMIT University, for the project proposal in the category of Methodology, Forecasting Hierarchical Time Series using Non-linear Mappings
Jean-François Toubeau, University of Mons; Yi Wang, University of Hong-Kong, for the project proposal in the category of Applications, Privacy-Preserving Renewable Energy Probabilistic Forecasting
2020
Hussain Syed Kazmi, KU Leuven; Maria Paskevich, King (Activision-Blizzard), for the project proposal in the category of Business Applications, Incorporating downstream, task-specific information in forecasting models
Ahmed Aziz Ezzat, Rutgers University, for the project proposal in the category of Methodology, Forecasting in Unknown Territory: Towards Physically Motivated Learning for Local Wind Fields
2019
Katie McConky and Omar Aponte, Rochester Institute of Technology, for the project proposal in the category of Business Applications, Actionable Peak Electric Load Day Forecasting Method for Facilities with Renewable Electricity Cogeneration
Xiaochun Liu, University of Alabama, for the project proposal in the category of Methodology, Conditional Encompassing Test for Value-at-Risk and Expected Shortfall Forecasts: A GMM Approach
2018
Arnaud Dufays, Université Namur, and David Ardia, HEC Montréal, for the project proposal in the category of Business Applications, Benchmark-testing volatility models with an open-source database
Jian Luo, Dongbei University of Finance & Economics, for the project proposal in the category of Methodology, Robust kernel-free nonlinear support vector regression models for load forecasting
2017
Cong Feng and Jie Zhang, The University of Texas at Dallas, for the project proposal in the category of Business Applications Hierarchy-based Disaggregate Forecasting Using Deep Machine Learning in Power System Time Series
Fernando Cyrino and Bruno Q. Bastos, Pontifical Catholic University of Rio de Janeiro, for the project proposal in the category of Methodology Forecasting Wind and Solar Time Series with Convolutional Neural Networks Approach to Spatio-Temporal [IJF publication: https://www.sciencedirect.com/science/article/abs/pii/S0169207020301618]
2016
Julie Novak and Beatriz Etchegaray García, IBM Thomas J. Watson Research Center, for the project proposal in the category of Business Applications A Bayesian Model for Forecasting Time Series in a Hierarchically Structured Organisation
Leopoldo Catania and Tommaso Proietti, University of Rome, for the project proposal in the category of Methodology Forecasting Realized Volatility and the Role of Time Varying Dependence with Market Returns
2015
Jaqueson K. Galimberti, ETH Zürich-KOF Swiss Economic Institute, for the project proposal in the category of Business Applications An outer space view of the business cycles
Tatevik Sekhposyan, Texas A&M University, for the project proposal in the category of Methodology Model Selection and Model Averaging based on Economic Fundamentals
2014
Valerio Poti, University College Dublin, for the project proposal in the category of Business Applications Predicting Predictability
David Ardia, University Laval; Lennart F. Hoogerheide, Vrije Universiteit Amsterdam; Jeremy Kolly, University Laval and Fribourg University, for the project proposal in the category of Methodology Bayesian Prediction of Market Risk using Regime-Switching GARCH Models
2013
Jeffrey Stonebraker, North Carolina State University, for the project proposal in the category of Business Applications Probabilistic Forecasting of the Global Demand for the Treatment of Hemophilia B
Yongchen (Herbert) Zhao, University at Albany, for the project proposal in the category of Methodology Robust Real-Time Automated Forecast Combination in SAS: Development of a SAS Procedure and a Comprehensive Evaluation of Recently Developed Combination Methods
2012
Zoe Theocharis, University College London; Nigel Harvey, University College London; Leonard Smith, London School of Economics, for the project proposal in the category of Business Applications Improving judgmental input to hurricane forecasts in the insurance and reinsurance sector
Yorghos Tripodis, Boston University, for the project proposal in the category of Business Applications Forecasting the Cognitive Status in an Aging Population
Elena-Ivona Dumitrescu, Janine Christine Balter, and Peter Reinhard Hansen, European University Institute, for the project proposal in the category of Methodology Forecasting Exchange Rate Volatility: Multivariate Realized GARCH Framework
2011
Siddharth Arora and James Taylor, University of Oxford, for the project proposal in the category of Business Applications Short-term Load Forecasting Using Rule-based Seasonal Exponential Smoothing Incorporating Special Day Effects
Stavros Asimakopoulos, Lancaster University, for the project proposal in the category of Business Applications How to design Mobile Forecasting User Interfaces (MFUI) to improve business forecasting
Juan Trapero, Universidad de Castilla-La Mancha; Nikolaos Kourentzes, Lancaster University; and Diego Pedregal, Universidad de Castilla-La Mancha, for the project proposal in the category of Methodology Minimizing the gap between judgmental and statistical forecasting in the presence of promotions
2010
Matthias Seifert, IE Business School, for the project proposal in the category of Business Applications Time series forecasting: The contribution of task, decision support and cognitive factors in judgmental effectiveness
Bryan Routledge and Noah Smith, Carnegie Mellon University, for the project proposal in the category of Methodology Text-Driven Forecasting of Mergers: Identifying Targets and Acquirers
2009
Robert Fildes, Lancaster University; and Paul Goodwin, University of Bath, for the project proposal in the category of Business Applications Improving the use of information and advice in supply chain forecasting
David Dickey and Melinda Thielbar, North Carolina State University, for the project proposal in the category of Methodology Neural Networks for Time Series Prediction: Practical Implications of Theoretical Results
2008
Hossein Hassani, Anatoly Zhigljavsky and Saeed Heravi, Cardiff University, for the project proposal in the category of Applications Forecasting European Industrial Production with Multivariate Singular Spectrum Analysis
2007
Eric Bélanger, McGill University; Michael S. Lewis-Beck, University of Iowa; and Richard Nadeau, University of Montreal, for their project proposal Improving Election Forecasting in the United Kingdom
Gloria González-Rivera, University of California – Riverside, for the project proposal Evaluation of Multidimensional Predictive Densities
2006
Carolina García-Martos, María Jesús Sánchez and Julio Rodríguez, Universidad Politécnica de Madrid, Unobserved Component Model for Forecasting Electricity Prices and Their Volatilities
Barbara Rossi, Duke University, New Methods for Forecasting and Model Evaluation
2005
Sven Crone, Lancaster University; and Konstantinos Nikolopoulos, Manchester Business School, Automatic Modeling and Forecasting with Neural Networks – A Forecasting Competition Evaluation
Pilar Poncela, Universidad Autónoma de Madrid; and Eva Senra, Universidad de Alcala, Combining Forecasts Through Factor Models: Assessing Consensus and Uncertainty
2004
Peter Zhang, Georgia State University; and Douglas M. Kline, University of North Carolina at Wilmington, Quarterly Times Series Forecasting
Ting Yu, University of Technology at Sydney, Incorporating Prior Domain Knowledge in Machine Learning
2003
Kesten Green, Monash University, Assessing Probabilistic Forecasts
Brajendra Sutradhar, Memorial University of Newfoundland, Best Practice Recommendation for Forecasting Counts
Min Qi, Kent State University; and Peter Zhang, Georgia State University, Trend Time Series Modeling and Forecasting with Neural Networks