IIF-SAS Grant to Promote Research on Forecasting

For the seventeenth year, the IIF, in collaboration and with financial support from SAS®, is proud to announce financial support for research on how to improve forecasting methods and business forecasting practice. The awards for the 2020-2021 year will be (2) $10,000 grants; in Business Applications and Methodology. The application deadline is 30 September 2020.

For more details, visit IIF-SAS award. Applications must include:

  • Description of the project (max. 4 pages)
  • Brief c.v., including references (max. 4 pages)
  • Budget and work-plan for the project (max. 1 page)

All applications and inquiries should be sent to IIF Business Director

IIF-SAS Research Award – Recipients

2019-2020

Grant awarded to Katie McConkle 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.

Grant awarded to 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.

2018-2019

Grant awarded to 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

Grant awarded to 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

2017-2018

Grant awarded to 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

Grant awarded to 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

2016-2017

Grant awarded to 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

Grant awarded to 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

2015-2016

Grant awarded to 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

Grant awarded to Tatevik Sekhposyan, Texas A&M University, for the project proposal in the category of Methodology Model Selection and Model Averaging based on Economic Fundamentals

2014-2015

Grant awarded to Valerio Poti, University College Dublin, for the project proposal in the category of Business Applications Predicting Predictability

Grant awarded to 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

2013-2014

Grant awarded to 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

Grant awarded to 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

2012-2013

Grant awarded to  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

Grant awarded to 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

2012-2013

Grant awarded to Yorghos Tripodis, Boston University, for the project proposal in the category of Business Applications Forecasting the Cognitive Status in an Aging Population

Grant awarded to 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

2011-2012

Grant awarded to 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

Grant awarded to 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

2010-2011

Grant awarded to 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

Grant awarded to 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

2009-2010

Grant awarded to 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

Grant awarded to 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

2008-2009

Grant awarded to Hossein Hassani and Anatoly Zhigljavsky, Cardiff University; Saeed Heravi, Cardiff University for the project proposal in the category of Applications Forecasting European Industrial Production with Multivariate Singular Spectrum Analysis

2007-2008

Grant awarded to Eric Bélanger, McGill University; Michael S. Lewis-Beck, University of Iowa; and Richard Nadeau, Department of Political Science, University of Montreal, for their project proposal Improving Election Forecasting in the United Kingdom

Grant awarded to Gloria González-Rivera, University of California – Riverside, for the project proposal Evaluation of Multidimensional Predictive Densities

2006-2007

Grant awarded to Carolina García-Martos, Universidad Politécnica de Madrid, and María Jesús Sánchez and Julio Rodríguez Universidad Politécnica de Madrid, Unobserved Component Model for Forecasting Electricity Prices and Their Volatilities

Grant awarded to Barbara Rossi, Duke University, New Methods for Forecasting and Model Evaluation

2005-2006

Grant awarded to Sven Crone, Lancaster University, Management School, and Konstantinos Nikolopoulos, Manchester Business School, Automatic Modeling and Forecasting with Neural Networks – A Forecasting Competition Evaluation

Grant awarded to Pilar Poncela, Universidad Autónoma de Madrid, and Eva Senra, Universidad de Alcala, Combining Forecasts Through Factor Models: Assessing Consensus and Uncertainty

2004-2005

Grant awarded to Peter Zhang, Georgia State University, and Douglas M. Kline, University of North Carolina at Wilmington, Quarterly Times Series Forecasting

Grant awarded to Ting Yu, University of Technology at Sydney, Incorporating Prior Domain Knowledge in Machine Learning

2003-2004

Grant awarded to Kesten Green, Monash University, Assessing Probabilistic Forecasts

Grant awarded to Brajendra Sutradhar, Memorial University of Newfoundland, Best Practice Recommendation for Forecasting Counts

Grant awarded to Min Qi, Kent State University, and Peter Zhang, Georgia State University, Trend Time Series Modeling and Forecasting with Neural Networks