Via the New York Times, September 19, 2015: The Upshot, Punditry and Predictions, Justin Wolfers

Scotland’s ‘No’ Vote: A Loss for Pollsters and a Win for Betting Markets

The Statistical Research Centre at Bournemouth University in UK together with the International Institute of Forecasters (IIF) presented the 2014 Singular Spectrum Analysis (SSA) Workshop. This unique workshop was a two day event dedicated solely to research in forecasting time series with complex structure using SSA.

The 2014 SSA Workshop was held September 8 – 9, 2014 at the Executive Business Centre of Bournemouth University. To read a full report of the proceedings, click here.

Interested in hosting an IIF Workshop?

The International Institute of Forecasters sponsors annual workshops, each of which focuses on a specific 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. After approval of the Editor-in-Chief and following the usual refereeing process, papers from the workshops can be included in a special issue of the International Journal of Forecasting.

To learn more about past workshops and workshop guidelines visit the IIF website.

If you are already hosting a workshop on a forecasting topic and need support from the IIF, or if you are interested in organising and hosting a new workshop please contact George Athanasopoulos or Aris Syntetos.

(Cross-posted from Hyndsight)

The first issue of the IJF for 2015 has just been published, and I’m delighted that it includes a special section honoring Herman Stekler. It includes articles covering a range of his forecasting interests, although not all of them (sports forecasting is missing). Herman himself wrote a paper for it looking at “Forecasting—Yesterday, Today and Tomorrow“.

He is in a unique position to write such a paper as he has been doing forecasting research longer than anyone else on the planet — his first published paper on forecasting appeared in 1959. Herman is now 82 years old, and is still very active in research. Only a couple of months ago, he wrote to me with some new research ideas he had been thinking about, asking me for some feedback. He is also an extraordinarily conscientious and careful associate editor of the IJF and a delight to work with. He is truly “a scholar and a gentleman” and I am very happy that we can honor Herman in this manner. Thanks to Tara Sinclair, Prakash Loungani and Fred Joutz for putting this tribute together.

We also published an interview with Herman in the IJF in 2010 which contains some information about his early years, graduate education and first academic jobs.

Why I became a Forecaster Herman Stekler

In writing this little biographical sketch, I have come to realize that reconstructing historical events as they occurred in real-time is as difficult as making an actual forecast. I did not plan on becoming a forecaster; it was completely fortuitous.

When I graduated from college in 1955 and went to MIT, I had hoped to become an applied economist and aspired to work in a large US corporation.

Given that goal, I took courses in accounting, industrial organization and applied statistics. I had the belief that forecasting would provide an entry into corporate America. Consequently, I wrote a term paper forecasting steel demand using multiple regression. (Using the technology of that time. It took over an hour to invert a 3×3 matrix.)

Then a fortuitous event occurred. Sidney Alexander, who had been a corporate economist, joined the MIT faculty and he would become my thesis advisor. He was writing what turned out to be a seminal paper on indicator forecasting and I started working with him even before I had passed my qualifying exams. I wrote a thesis that consisted of various topics in forecasting.

When I entered the job market, I had many job interviews, both academic and corporate. After these interviews, my career path changed because I realized that my personality and corporate culture collided. I, therefore, chose to become an academic economist. Then, for some reason that I cannot explain, I decided not to undertake further research into economic forecasting issues. I ventured off into the field of industrial organization, an area that also interested me, but did not have spectacular success.

Then a second fortuitous event occurred. A Berkeley colleague asked me to undertake a consulting project: Evaluate the forecasting record of all existing econometric models. I completed the task and wrote several papers on the subject. This revitalized my interest in forecasting.

The rest is history. My forecasting knowledge was useful at the Fed, the Council on Wage and Price Stability and even within the Defense community. This community was interested in forecasting technological progress in military aircraft and even the economic effects of a war similar to WWII. More recently I discovered interesting issues in sports and political forecasting. Although I became a forecaster by chance, it obviously was the right career for me. I am still working and interested in these topics even now at age 82.

The Year in Review | Mohsen Hamoudia, IIF President

This is the quietest time of the year for the IIF and, in three weeks, we are going to welcome a new year. So, it is time to briefly review 2014 activities and try a “preview” of 2015.

ISF2014 was a great success and provided all the ingredients for a memorable and rewarding Symposium held in Rotterdam, The Netherlands, from 29 June – 2 July 2014. 340 delegates from 45 different countries attended and 280 papers presented in 90 sessions, covering 30 different areas of research and practices were presented … 

Click here to read the full article.

Robert Fildes, ex-president of the IIF and Distinguished Professor of Management Science at Lancaster University Management School, has been awarded the Beale Medal, the Operational Research Society’s highest accolade. The award was presented at the Society’s annual Awards Ceremony in London on 26 November.

The award recognises the continuous contribution over many years by one person to the theory, practice or philosophy of Operational Research (OR) in the UK. As a discipline, OR deals with the application of advanced analytical techniques to enhance managerial decision making and of course forecasting plays a major (sometimes unacknowledged) part in this.

Professor Fildes earned the award for his outstanding contribution to the development of OR – most notably in the area of forecasting, in which he is an international expert.
Much of his work has been on research into business forecasting, with some recent research in global climate models (Validation and forecasting accuracy in models of climate change, International Journal of Forecasting, 27, 968-995). He has been particularly concerned with improving forecasting practice in organisations. Both in his research into organisations and his work through the Centre for Forecasting, he has increasingly highlighted the barriers to change, not least the limitations of forecasting software.

He is a past president of the International Institute of Forecasting and was co-founder of the Journal of Forecasting in 1981 and the International Journal of Forecasting in 1985. He took up a Professorial post at Lancaster University in 1990 and established the Lancaster Centre for Forecasting, which has become possibly the largest research unit dedicated to business forecasting internationally.

Professor Fildes said: “Working with colleagues at the Lancaster Centre for Forecasting, I believe we’ve made a major contribution to improving forecasting in practice. What I’ve tried to do throughout my career is to develop novel approaches that integrate forecasting and OR, taking into account the many practical constraints organisations face. I’ve also found it a lot of fun to study the mix of statistics and psychology. The IIF through its symposia around the world has given me this opportunity”.

Professor Fildes has published extensively in top academic journals and is the author or editor of six books, including the Sage Handbook of Forecasting.

Foresight kicks off its 10th year with the publication of a new survey of business forecasters: Improving Forecast Quality in Practice. This ongoing survey, designed at the Lancaster Centre for Forecasting in the UK, seeks to gain insights on where the emphasis should be put to further upgrade the quality of our forecasting practices. Initial survey results, presented by Robert Fildes, Director of the Lancaster Centre, and Fotios Petropoulos, former member of the Centre, examine these key aspects of forecasting practice: organizational constraints, the flow of information, forecasting software, organizational resources, forecasting techniques employed, and the monitoring and evaluation of forecast accuracy.

The survey is an important update to that conducted more than a decade ago by Mark Moon, Tom Mentzer, and Carlo Smith of the University of Tennessee. In his Commentary on the Lancaster survey, Mark Moon applauds the broad focus of the survey but raises the issue of whether the “practicing forecasters” surveyed are “developers” or “customers” of the forecasts.

We often find a significant difference in perception between those who are responsible for creating a forecast and those that use the forecast to create business plans.

In our section on Collaborative Forecasting and Planning, Foresight S&OP Editor John Mello writes that S&OP can not only improve collaboration within an organization, but also “change the company’s operational culture from one that is internally focused to one that better understands the potential benefits of working with other companies in the supply chain.” His article, Internal and External Collaboration: The Keys to Demand-Supply Integration, identifies and compares several promising avenues of external collaboration, including vendor-managed inventory (VMI); collaborative planning, forecasting, and replenishment (CPFR); retail-event collaboration; and various stock-replenishment methods currently in use by major manufacturers and retailers. The critical factor, John finds, is trust:

These processes all require the sharing of information between companies, joint agreement on the responsibilities of the individual companies, and a good deal of trust between the parties, since the responsibility for integrating supply and demand is often delegated to the supplier.

In a Commentary on the Mello article, Ram Ganeshan and Tonya Boone point out that the challenges of external collaboration arrangements are much greater when we consider their Extension beyond Fast-Moving Consumer Goods, especially those goods with short life cycles. For these products, they argue, a different mind-set is required to achieve demand-supply integration.

Financial Forecasting Editor Roy Batchelor distills the lessons forecasters should learn from the failures to predict and control our recent global financial meltdown. A 2014 International Monetary Fund (IMF) report, Financial Crises: Causes, Consequences, and Policy Responses, examined the world economies’ 2007-09 financial crises to establish their causes and impacts, as well as the initiatives governments and central banks undertook to deal with them. The overall impression from this report, Roy writes in his review, entitled Financial Crises and Forecasting Failures, is that the authorities could have been speedier and more imaginative in their interventions in the financial sector. Importantly, however, our forecasting models could have given a clearer picture of how economies might emerge from these crises. Roy probes into why the models didn’t see the crisis coming, and what upgrades to the models’ financial sectors might improve predictive performance in the future.

Jeffrey Mishlove’s Commentary on Roy’s review article argues that the real problem did not emanate from predictive failures, but rather from the inclination toward austerity that pervaded economic thinking, especially in Western Europe. Jeff says that, while he can’t argue with Roy’s conclusions that refinements in the scientific method and the gathering of empirical data are appropriate responses to financial crises, forecasts will always be vulnerable to confounding influences from unanticipated variables – no matter how much we refine and improve our methodologies.

Seasonality – repeating intra-year patterns that in turn repeat year after year – is a dominant and pervasive contributor to variations in our economy. But, as Roy Pearson writes in Giving Due Respect to Seasonality in Monthly Forecasting, the seasonal adjustments we make to economic data are poorly understood and lead to confusion in interpreting sales changes. Improved accounting for seasonality for monthly forecasts over 12-24 months can lead to better understanding of the forces behind sales forecasts, and very likely to some reduction in forecast errors.

This article is Roy’s final contribution for Foresight, the capstone of nearly one dozen invaluable examinations – under the rubric of Forecasting Intelligence – of forecasting information sources and forecast credibility.

The International Institute of Forecasters will grant travel awards to enable individuals from all over the world to attend the International Symposium on Forecasting, taking place in Riverside, California, June 21-24th.  Criteria for acceptance include the quality of the submission, how helpful attending the conference might be to the applicant’s research agenda, and whether or not the paper might be publishable in the International Journal of Forecasting.

The deadline for applications is February 20, 2015.  For more information and to apply visit: http://forecasters.org/isf/financial-support/

The ISF Program Committee welcomes the submission of abstracts for presentations to be given at our annual forecasting symposium.  We encourage individuals to organize a session on a specific, unique theme in the field of forecasting. For example, we encourage sessions following the conference theme, Frontiers in Forecasting.  We, of course, encourage sessions on any of the established forecasting themes.

An invited session consists of 3 or 4 talks around a specific, forecasting theme. You are allowed to be one of the speakers in a session you organize (although it is not necessary). The length of all such invited talks will be about 20 minutes.

Invited sessions will be marked as such on the program and carry a slightly higher status than a contributed session. Unfortunately, we can’t offer any financial support for these invited speakers or session organizers.

The deadline for submitting an invited session is January 31, 2015.  For more information or to submit a proposal, contact the .

Demand uncertainty is among the biggest forecasting challenges, causing companies to invest in new software and implement new methods that they may not really need.

Foresight’s new guidebook, Techniques for Forecasting Product and Temporal Hierarchies explores using data’s hierarchical characteristics to reduce supply chain uncertainty.  In addition to a comprehensive overview of the topics at hand by Editor Len Tashman, the guidebook includes:

• Choosing Levels of Aggregation for Supply Chain Forecasts
• Forecasting by Cross-Sectional Aggregation
• The Application of Product-Group Seasonal Indexes to Individual Products
• Forecasting Seasonal Time Series Using Aggregate and Analogous Series
• Optimally Reconciling Forecasts in a Hierarchy
• Resolving a Family Feud: Market-Facing versus Lean Manufacturing Families
• Forecasting by Temporal Aggregation
• Improving Forecasting via Multiple Temporal Aggregation

Use this guidebook to explore in-depth two forecasting approaches – cross-sectional and temporal aggregation – which will almost certainly help you reduce uncertainty.

Published: January 2015
Pages: 56, pdf format
Price:  $70, $35 for Foresight subscribers & IIF members
Available now in the Foresight Document Store

About Carson Analytics Carson Analytics, a division of BioPharm Communications, LLC, provides marketing analytics solutions to the Biopharm industry.

Position Summary:

As a Sr. Analyst you will work on a wide range of quantitative analyses for the BioPharm industry to support our clients measuring, analyzing, and optimizing marketing effectiveness. Typical analyses include forecasting, promotion response analyses, promotion mix and channel optimization, segmentation analyses, etc. The position will provide actionable insights into market behaviors based on advanced analytic techniques.

For the full job description, click here.

The ISF Program Committee looks forward to receiving abstracts and hearing inventive presentations that demonstrate again that the annual forecasting symposium is the only forum where the latest forecasting problems are confronted by new solutions.

The ISF Program Committee invites you to submit abstracts related to the theory and practice of forecasting. Suggested themes and topics and full submission rules are available here.

The deadline date for abstracts is March 16, 2015.  Abstracts can be submitted online at http://forecasters.org/isf/submissions/abstracts/

FOR IMMEDIATE RELEASE 
CONTACT:
Pam Stroud, Business Director
International Institute of Forecasters
+1.781.234.4077
isf@forecasters.org
www.forecasters.org

Frontiers in Forecasting
35^th International Symposium on Forecasting, June 21-24, 2015 in Riverside, California

Boston, MA, March 2, 2015 – Integrating academic research into practical applications is one of the hallmarks of the 35^th annual International Symposium on Forecasting (ISF) being held June 21 – 24 in Riverside, California. The ISF draws the world’s top forecasting professionals and researchers, presenters and participants, to learn and discuss cutting-edge forecasting trends.

The premiere international conference on forecasting, the ISF encompasses a broad range of forecasting sectors. This year’s event includes sessions on climate predictability, forecasting electricity demand, prediction of business cycles in real time, financial market volatility, forecast optimality, early warning signals, tourism forecasting, information technology trends, macroeconomic trends and history of prediction science, among many others.

“The Symposium provides a platform for leading forecasting professionals to reveal their insights into the field. With a stimulating scientific program, plenty of networking opportunities, and a fun social program, ISF 2015 will be a memorable event. The City of Riverside warmly welcomes our participants and extends an invitation to explore the beauty of Southern California,” says Gloria González-Rivera, General Chair of ISF2015, Professor of Economics at the University of California, Riverside.

For the third time, the symposium will present the Clive Granger Memorial Keynote Address in honor of the late Nobel laureate and professor emeritus at the University of California, San Diego. Emeritus Professor Hal Varian, distinguished professor at University of California, Berkeley and Chief Economist at Google, Inc., has been given the honor of delivering the address for ISF 2015.

Other notable speakers at this year’s symposium include Joel E. Cohen, Abby Rockefeller Mauzé Professor of Populations, The Rockefeller and Columbia Universities; Tilmann Gneiting, Professor of Computational Statistics, Karlsruhe Institute of Technology; Dimitris Politis, Professor of Mathematics, University of California, San Diego; and, Barbara Rossi, ICREA Professor, Universitat Pompeu Fabra, Barcelona GSE and CREI.

New in 2015: Forecasting in Practice. The editors of Foresight: The International Journal of Applied Forecasting have created The Foresight Practitioner Track – a full day program designed to meet the professional development needs of business forecasting practitioners. Notable speakers from industry and academia will present this unique program (Program details at http://forecasters.org/isf/program/speakers/).

Event sponsors include University of California, Riverside’s Department of Economics, Elsevier, EView, SAS, the City of Riverside, Office of Economic Development, and the County of Riverside, Economic Development Agency. For more information on sponsorship opportunities, contact the IIF directly (see contact information below).

Research conducted through the SAS Forecasting Research Grant program will also be presented at this year’s conference. Awarded by the IIF with support from SAS, grants totaling $10,000 are given annually for research that advances the field of forecasting. The program is now in its thirteenth year.

Individuals or organizations are invited to submit abstracts for the conference through March 16. Discounted early registration rates for the ISF conference are available through May 15 for both IIF members and non-members. Special student rates are also available. Access online registration at http://forecasters.org/isf.

For more information about the 2015 ISF, see www.forecasters.org/isf or contact Pam Stroud, IIF Business Director at isf@forecasters.org, +1.781.234.4077.

About the International Institute of Forecasters (IIF) – The International Institute of Forecasters, founded in 1981, is the preeminent organization for forecasting scholars and practitioners across the globe. The IIF is widely recognized for promoting best practices and advancing the field of forecasting through its workshops, its annual International Symposium on Forecasting, and its two publications, The International Journal of Forecasting and its journal for forecasting practitioner’s Foresight: The International Journal of Applied Forecasting.

Forecasts have traditionally served as the basis for planning and executing supply chain activities – sourcing, making, and distributing products and services to customers. Forecasts drive all supply chain decisions and their importance has become critical with increasing customer expectations, shortening lead times, and scarcity of resources. Few areas have been as transformed by big data as forecasting given new and rapid access to data.

Digital technologies (such as digital clickstreams, sensors, tags, beacons, and other smart devices), have enabled firms to collect vast amounts of data in real-time. On the other hand, significant but relevant data is also collected in the public domain – social media traffic on the firm’s products and services, photo and video streams, blog and forum entries, and trend spotting data — that are free and fine-grained. We use the term “big data” for data sets that are large (“volume”); that is collected in near real-time (high “velocity”), and present in myriad forms (“variety”). Big data-driven forecasting holds tremendous promise for supply chain planners. The vast amounts of data collected and analyzed in near real-time can be used to better understand customer behavior, improve forecast accuracy, assess systemic and idiosyncratic risk, and improve supply chain execution. The challenge for both researchers and practitioners of forecasting is to effectively integrate this data into supply chain planning activities; and to develop innovative tools, techniques, and models that can use these big data sets unlock deep insights and value.

This opens up an opportunity to significantly impact the practice of forecasting through fundamental research on: i) how big data can be used to leverage the forecasting process in the supply chain; ii) provide supply chain insights by developing innovative and scalable forecasting techniques to manipulate and analyze large data sets; and iii) finally, explore how such forecasting best practices can be developed, structured, and deployed in organizations and across the supply chain.

Special Issue Goals and Topics

This Special Issue draws upon advances in computing and statistics to improve and deepen our understanding on how big data has impacted the practice of forecasting, especially in supply chain contexts. We welcome a wide variety of topics that address big data-driven forecasting in the supply chain. This could, planning production and distribution, and managing the supply base. Data include predicting customer behavior, forecasting or nowcasting demand for products sets used (real or simulated) should have characteristics of big data (volume, velocity, variety); and the insights that are generated should leverage such newly available data.

We are also interested in papers that describe new forecasting models and techniques to analyze large and unstructured data sets that are collected in a supply chain context. These can include statistical techniques (including modifications of traditional forecasting models), adaptive regression, data mining heuristics, machine learning algorithms, video and text processing, etc. Of particular interest are those methods that scale well with large data sets. New techniques should also be rigorously verified. One example is forecasting performance on out-of-sample data. Empirical evaluations of forecasts should be out-of-sample and include established benchmark comparisons, and be subject to tests of statistical significance. This area is especially important in supply chain research where forecasts are often not evaluated as rigorously as they should be, are not compared against established benchmarks or over a large enough sample to draw general conclusions. Big data offers an opportunity for this.

Finally, we are also interested in papers that rigorously explore how big data-driven forecasting capability can be developed, structured, integrated, and deployed across the supply chain and organization. This includes the process of formulating the big data-driven forecasting strategy, investigating the factors for successful deployment, and the identification of potential pitfalls to implementation.

Sample topics of interest:

Value generation in the supply chain

• Forecasting/Nowcasting demand for products and services
• Forecasting consumer behavior (through digital click streams, beacons, sensors, etc.)
• Trend spotting (using Google Trends for example)
• Demand and production planning
• Forecasting and planning for supply chain risk (both systemic and rare events)

Tools and techniques

• Methods to collect and visualize data that will aid forecasting
• Methods to codify and incorporate unstructured data into traditional forecasting models
• Scalable techniques for forecasting in the supply chain context (this could include machine learning algorithms, A/B testing, etc.)
• Techniques to analyze large and/or unstructured data (geographic, sensor, or near real-time data streams)

Organization & Outlook

• How best to integrate big-data driven forecasting into the organization?
• Future outlook for using big data-driven forecasting in the supply chain

Submission Guidelines

To submit a paper for consideration for the Special Issue, please upload your paper online and include a cover letter clearly indicating that the paper is for the special issue on “Big data-driven Forecasting in the supply chain”. The webpage for online submissions is mc.manuscriptcentral.com/ijf. The deadline for receipt of papers is 1 June 2016. All papers will follow IJF’s refereeing process.
Instructions for authors are provided at www.forecasters.org/ijf/authors

For further information about the Special Issue, please contact one of the guest editors.

Guest Editors

Nada R. Sanders
Nada Sanders (n.sanders@neu.edu)
Distinguished Professor of Supply Chain Management
D’Amore-McKim School of Business, Northeastern University

Tonya Boone
Tonya Boone (tonya.boone@mason.wm.edu)
Associate Professor of Operations & Information Technology
Raymond A. Mason School of Business, The College of William and Mary

Ram Ganeshan
Ram Ganeshan (ram.ganeshan@mason.wm.edu).
D. Hillsdon Ryan Professor of Business
Raymond A. Mason School of Business, The College of William and Mary

BIOS

NADA R. SANDERS
Nada R. Sanders is the Distinguished Professor of Supply Chain Management at the D’Amore-McKim School of Business at Northeastern University in Boston MA. Prior to that, she held the Iacocca Chair at the College of Business and Economics at Lehigh University and as the West Chair at the M.J. Neeley School of Business.

Her research and teaching interests have been in forecasting and the use of data analytics in decision-making within the supply chain context. She has authored over one hundred scholarly works and has served on the editorial boards of prominent journals in her field, including the Journal of Operations Management, Production and Operations Management, Decision Sciences Journal, Journal of Business Logistics, and International Institute of Forecasting. She is a Fellow of the Decision Sciences Institute and was co-founder and Associate Editor of Foresight: The International Journal of Applied Forecasting. She has authored multiple books with the most recent being Big Data Driven Supply Chain Management and has given numerous talks on the subject including a recent HBR webinar. She currently serves on the Board of POMS, having served as both Program and General Chair.

She holds a Ph.D. in Operations Management and Logistics, and an MBA, from the Fisher College of Business at The Ohio State University, as well as a B.S. in Mechanical Engineering.

TONYA BOONE
Tonya Boone is an Associate Professor at the Raymond A. Mason School of Business, The College of William & Mary. Prior to joining the faculty of the College of William and Mary, she was a faculty member at the Fischer College of Business at Ohio State University.

Her research and teaching interests include sustainable operations, knowledge management in professional service organizations, and the management of supply chains in data rich environments. Tonya’s research has been published in the top academic management journals, including Management Science, Journal of Operations Management, POMS Journal, and Decision Sciences. She is also a co-editor of the recent book Sustainable Supply Chain Management: Methods, Models, and Policy Implications.

Tonya is active in her community, serving on the Board of the Williamsburg Economic Development Authority, the Board of the Hampton Roads Incubator, and the Board of the Williamsburg Regional Library. She is a sought-after expert in the local community in the areas of sustainability, public service, and supply chain management.

Tonya Boone has a Ph.D. in Operations and Technology Management from the University of North Carolina at Chapel Hill’s Kenan-Flagler School of Business; a MBA from the College of William and Mary; and a BS in Electrical & Electronics Engineering from the University of Kansas.

RAM GANESHAN
Ram Ganeshan is the D. Hillsdon Ryan Professor of Business at the Raymond A. Mason School of Business, The College of William and Mary, Williamsburg, VA.

Ram’s teaching, research and consulting interests are in the areas of supply chain management, data analytics, and logistics strategy, primarily in the chemical, hi-tech, and retail industries.  He is a regular contributor to academic and trade journals and is the co-editor of three books including Quantitative Models for Supply Chain Management which is one of the most highly cited books in supply chain management. In 2001, the Production & Operations Management Society (POMS) awarded him the prestigious Wickham Skinner Award for his research on how supply chains can be efficiently managed. His current research projects extensively rely on big-data techniques to provide insights into making sound decisions for managing both manufacturing and service supply chains. They include: (1) work with online retailers to harness and interpret clickstream data from customer browsing behavior; (2) working with carriers in the transportation sector to reduce cost and carbon footprint; and (3) analyzing large scale project data in professional services to provide strategies for productivity improvement.

He received a Doctorate in Operations and Logistics Management from Penn State; a MSOR degree in Operations Research from the University of North Carolina at Chapel Hill; and an undergraduate degree in Industrial Management from the Birla Institute of Technology & Science in India.

For the thirteenth year, the International Institute of Forecasters, in collaboration with SAS, is proud to announce financial support for research on how to improve forecasting methods and business forecasting practice. The award for the 2015-2016 year will be (2) $5,000 grants. The deadline for applications is September 30, 2015.  For more information on the grant click here.

(Crossposted from Hyndsight)

Today at the International Symposium on Forecasting, I announced the awards for the best paper published in the International Journal of Forecasting in the period 2012-2013.

We make an award every two years to the best paper(s) published in the journal. There is always about 18 months delay after the publication period to allow time for reflection, citations, etc. The selected papers are selected by vote of the editorial board. The best paper wins an engraved bronze plaque and US$1000. Any other awards are in the form of certificates.

For 2012-2013, 11 papers nominated of which five were short-listed for the award. The five short-listed papers were:

• Diebold, F. X., & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. IJF, 28(1), 57–66.
• Galvão, A. B. (2013). Changes in predictive ability with mixed frequency data. IJF, 29(3), 395–410.
• Genre, V., Kenny, G., Meyler, A., & Timmermann, A. (2013). Combining expert forecasts: Can anything beat the simple average?. IJF, 29(1), 108-121.
• Jordà, Ò., Knüppel, M., & Marcellino, M. (2013). Empirical simultaneous prediction regions for path-forecasts. IJF, 29(3), 456–468.
• Soyer, E., & Hogarth, R. M. (2012). The illusion of predictability: How regression statistics mislead experts. IJF, 28(3), 695–711.

This year, we have made two awards. The best paper award goes to Francis Diebold and Kamil Yilmaz for their 2012 paper on estimating spillovers between markets. The nomination of the paper included the following citation.

This is a methodological paper developing ways to estimate spillovers from one market to others. Diebold and Yilmaz use a generalized vector autoregressive framework in which forecast error variance decompositions are invariant to the variable ordering. Even though they used the method to look at volatility spillovers internationally in the time domain, the procedure is usable more generally including with cross-sectional data having spatial interconnections. This is an important contribution with significant repercussions across financial markets.

An “outstanding paper award” goes to Véronique Genre, Geoff Kenny, Aidan Meyler and Allan Timmermann for their 2013 paper on combining expert forecasts. The following citation explains why the paper was nominated.

This is a topic that has been of fundamental interest to forecasters in all fields: can one beat the simple average when combining forecasts. The authors do an excellent job exploring that issue in a data set that had not previously been fully exploited.

The authors explore an extensive set of methods to show that, on aggregating forecasts, a simple average is a benchmark that is very difficult to beat by more sophisticated aggregation schemes. Although the finding per~se is not new (we have numerous studies examining the “forecast combination puzzle”), the rigorous approach to comparison of methods makes this manuscript very relevant.