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Forecasting and risk taking

This research project is investigating the relationship between the accuracy of judgmental forecasting and risk-taking behaviour. Your participation is entirely voluntary and all responses will be treated in the strictest confidence.

The experiment has two separate parts followed by a short questionnaire at the end.

In the first part you will be asked to choose which of five forecasts you think will…

IJF Special Issue on Judgmental Forecasting

The International Journal of Forecasting (IJF) has announced a Special Issue on judgmental forecasting, and more specifically on elicitation, structuring and evaluation of expert judgment. The Special Issue will be edited by George Wright (Strathclyde University, UK), Gene Rowe (Gene Rowe Evaluations, Norwich, UK), and Fergus Bolger (University of Durham, UK).

This is of great interest and relevance with the scope…

Can you identify additive and multiplicative seasonality?

In business forecasting it is quite common to deal with seasonal time series. Although several methodologies have been developed to identify when to use a seasonal model, less effort has been invested in identifying whether a time series exhibits additive or multiplicative seasonality. Perhaps here it is useful to remember the distinction between the two. Assuming a time series with…

Judgmental model selection: results and winners!

The “Judgmental model selection for time series forecasting” experiment is now successfully completed! In total, 905 people started the experiment, from which 693 completed the task. Thank you all for your participation in this judgmental experiment. Your contribution to this research is much appreciated.

The experiment itself completed by two approaches:

Judgmental model selection, where given 4 unnamed models the participant was…

Forecasting Society goes ISF2014

The founders of the Forecasting Society (Fotios Petropoulos and Nikolaos Kourentzes) attended the International Symposium of Forecasting 2014 (ISF2014) that was organised by the International Institute of Forecasters and held at Rotterdam, Netherlands (June 29 – July 2, 2014).

We had the opportunity to promote the Forecasting Society and discuss with leading researchers in the field of judgmental forecasting regarding the…

The Golden Rule of Forecasting

The Golden Rule of Forecasting is, “be conservative” when forecasting by relying on cummulative knowledge about the situation and about forecasting. The working paper by J. Scott Armstrong, Kesten C. Green, and Andreas Graefe is available here.

This experiment provides access to the online tool Golden Rule for Forecasting Checklist software.

Purpose and instructions:
1. Even if you are unfamiliar with forecasting, you…

Value of judgemental adjustments to promotional forecasting

Sales forecasting is becoming increasingly complex, due to a range of factors, such as the shortening of product life cycles, increasingly competitive markets, and aggressive marketing. Companies often use some form of Forecasting Support System (FSS) to integrate univariate statistical baseline forecasts with expert judgement from demand planners, essentially adding information from additional factors to the statistical forecasts. Promotional and…

Judgmental reconciliation of hierarchical forecasts

Producing forecasts at different hierarchical levels (company-level, sector-level, SKU-level) using different aggregations of the data can lead to substantial differences. Various statistical reconciliation approaches have been considered. The bottom-up approach suggests that forecasts should be produced at the lowest level of aggregation (SKU-level) and forecasts at higher levels are derived by simply aggregating the lower-level forecasts. On the other hand,…

Can we rely on judgment to select the best forecasting model?

Model selection for forecasting problems has attracted much attention during the last 30 years. Many research studies have examined theoretically and empirically different statistical selection methodologies to identify the ‘optimal’ model. The model selection problem is of major practical importance, because if selections are to be done perfectly, substantial gains will achieved in terms of forecasting performance, usually up to 25-30%,…

Judgmental model selection for time series forecasting

We are inviting you to participate in a web-based judgmental forecasting exercise. You are asked to select the best model, based on your judgment, for 32 time series.

The exercise consists of four rounds. Each round will contain 8 series and will be followed by a short questionnaire, while different types of information will be provided on top of the estimated…