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Rule-Based Forecasting: Development and Validation of an Expert Systems Approach to Combining Time Series Extrapolations

Citations

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Cited by:

  1. Edward J. Lusk, 2019. "A Benchmarked Evaluation of a Selected CapitalCube Interval-Scaled Market Performance Variable," Accounting and Finance Research, Sciedu Press, vol. 8(2), pages 1-1, May.
  2. JS Armstrong & Fred Collopy, 2004. "Causal Forces: Structuring Knowledge for Time-series Extrapolation," General Economics and Teaching 0412003, University Library of Munich, Germany.
  3. Michael S. McPherson & Morton Owen Schapiro & Dennis Ahlburg, 1994. "Predicting Higher Education Enrollment in the United States: An Evaluation of Different Modelling Approaches," Williams Project on the Economics of Higher Education DP-26, Department of Economics, Williams College.
  4. Edward J. Lusk & Michael Halperin & Atanas Tetikov & Niya Stefanova, 2010. "Forecasting Financial Market Annual Performance Measures: Further Evidence +," American Journal of Economics and Business Administration, Science Publications, vol. 2(3), pages 300-306, September.
  5. Evangelos Spiliotis & Fotios Petropoulos & Vassilios Assimakopoulos, 2023. "On the Disagreement of Forecasting Model Selection Criteria," Forecasting, MDPI, vol. 5(2), pages 1-12, June.
  6. Armstrong, J. Scott, 1996. "Heuristics, biases and improvement strategies in judgmental time series : P. Goodwin and G. Wright, 1994, Omega, 22, 553-568," International Journal of Forecasting, Elsevier, vol. 12(2), pages 319-321, June.
  7. Everette S. Gardner, 1999. "Note: Rule-Based Forecasting vs. Damped-Trend Exponential Smoothing," Management Science, INFORMS, vol. 45(8), pages 1169-1176, August.
  8. Yuehjen Shao & Yue-Fa Lin & Soe-Tsyr Yuan, 1999. "Integrated application of time series multiple-interventions analysis and knowledge-based reasoning," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(6), pages 755-766.
  9. Ord, Keith & Hibon, Michele & Makridakis, Spyros, 2000. "The M3-Competition1," International Journal of Forecasting, Elsevier, vol. 16(4), pages 433-436.
  10. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2015. "Golden rule of forecasting: Be conservative," Journal of Business Research, Elsevier, vol. 68(8), pages 1717-1731.
  11. Robert Fildes & Gary Madden & Joachim Tan, 2007. "Optimal forecasting model selection and data characteristics," Applied Financial Economics, Taylor & Francis Journals, vol. 17(15), pages 1251-1264.
  12. Goodwin, Paul, 2002. "Integrating management judgment and statistical methods to improve short-term forecasts," Omega, Elsevier, vol. 30(2), pages 127-135, April.
  13. de Menezes, Lilian M. & W. Bunn, Derek & Taylor, James W., 2000. "Review of guidelines for the use of combined forecasts," European Journal of Operational Research, Elsevier, vol. 120(1), pages 190-204, January.
  14. Bunn, Derek W., 1996. "Non-traditional methods of forecasting," European Journal of Operational Research, Elsevier, vol. 92(3), pages 528-536, August.
  15. Lawrence, M. & O'Connor, M., 1996. "Judgement or models: The importance of task differences," Omega, Elsevier, vol. 24(3), pages 245-254, June.
  16. Assimakopoulos, V. & Nikolopoulos, K., 2000. "The theta model: a decomposition approach to forecasting," International Journal of Forecasting, Elsevier, vol. 16(4), pages 521-530.
  17. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
  18. Armstrong, J. Scott & Collopy, Fred & Yokum, J. Thomas, 2005. "Decomposition by causal forces: a procedure for forecasting complex time series," International Journal of Forecasting, Elsevier, vol. 21(1), pages 25-36.
  19. R Fildes & K Nikolopoulos & S F Crone & A A Syntetos, 2008. "Forecasting and operational research: a review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1150-1172, September.
  20. Song, Haiyan & Gao, Bastian Z. & Lin, Vera S., 2013. "Combining statistical and judgmental forecasts via a web-based tourism demand forecasting system," International Journal of Forecasting, Elsevier, vol. 29(2), pages 295-310.
  21. Vokurka, Robert J. & Flores, Benito E. & Pearce, Stephen L., 1996. "Automatic feature identification and graphical support in rule-based forecasting: a comparison," International Journal of Forecasting, Elsevier, vol. 12(4), pages 495-512, December.
  22. Anqiang Huang & Kin Keung Lai & Han Qiao & Shouyang Wang & Zhenji Zhang, 2018. "Does Interval Knowledge Sharpen Forecasting Models? Evidence from China’s Typical Ports," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(02), pages 467-483, March.
  23. Rakesh K. Sarin, 2013. "From the Editor ---Median Aggregation, Scoring Rules, Expert Forecasts, Choices with Binary Attributes, Portfolio with Dependent Projects, and Information Security," Decision Analysis, INFORMS, vol. 10(4), pages 277-278, December.
  24. Armstrong, J. Scott, 2006. "Findings from evidence-based forecasting: Methods for reducing forecast error," International Journal of Forecasting, Elsevier, vol. 22(3), pages 583-598.
  25. Kang, Yanfei & Cao, Wei & Petropoulos, Fotios & Li, Feng, 2022. "Forecast with forecasts: Diversity matters," European Journal of Operational Research, Elsevier, vol. 301(1), pages 180-190.
  26. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
  27. Thiyanga S. Talagala & Feng Li & Yanfei Kang, 2019. "Feature-based Forecast-Model Performance Prediction," Monash Econometrics and Business Statistics Working Papers 21/19, Monash University, Department of Econometrics and Business Statistics.
  28. Armstrong, J. Scott & Brodie, Roderick J., 1999. "Forecasting for Marketing," MPRA Paper 81690, University Library of Munich, Germany.
  29. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
  30. Fildes, Robert & Petropoulos, Fotios, 2015. "Simple versus complex selection rules for forecasting many time series," Journal of Business Research, Elsevier, vol. 68(8), pages 1692-1701.
  31. Francisco Martínez-Álvarez & Alicia Troncoso & Gualberto Asencio-Cortés & José C. Riquelme, 2015. "A Survey on Data Mining Techniques Applied to Electricity-Related Time Series Forecasting," Energies, MDPI, vol. 8(11), pages 1-32, November.
  32. Fildes, Robert & Petropoulos, Fotios, 2013. "An evaluation of simple forecasting model selection rules," MPRA Paper 51772, University Library of Munich, Germany.
  33. Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.
  34. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
  35. Adya, Monica & Armstrong, J. Scott & Collopy, Fred & Kennedy, Miles, 2000. "An application of rule-based forecasting to a situation lacking domain knowledge," International Journal of Forecasting, Elsevier, vol. 16(4), pages 477-484.
  36. Mohamed Gaber & Edward J. Lusk, 2019. "A Vetting Protocol for the Analytical Procedures Platform for the AP-Phase of PCAOB Audits," Accounting and Finance Research, Sciedu Press, vol. 8(4), pages 1-43, November.
  37. Cui, Can & Wu, Teresa & Hu, Mengqi & Weir, Jeffery D. & Li, Xiwang, 2016. "Short-term building energy model recommendation system: A meta-learning approach," Applied Energy, Elsevier, vol. 172(C), pages 251-263.
  38. Edward J. Lusk, 2019. "Time Series Forecasting in Stock Trading Markets: The Turning Point Curiosity," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 8(4), pages 01-16, July.
  39. Sanders, N. R., 1997. "The impact of task properties feedback on time series judgmental forecasting tasks," Omega, Elsevier, vol. 25(2), pages 135-144, April.
  40. Petropoulos, Fotios & Makridakis, Spyros & Assimakopoulos, Vassilios & Nikolopoulos, Konstantinos, 2014. "‘Horses for Courses’ in demand forecasting," European Journal of Operational Research, Elsevier, vol. 237(1), pages 152-163.
  41. JS Armstrong, 2004. "Should We Redesign Forecasting Competitions?," General Economics and Teaching 0412001, University Library of Munich, Germany.
  42. Welch, Eric & Bretschneider, Stuart & Rohrbaugh, John, 1998. "Accuracy of judgmental extrapolation of time series data: Characteristics, causes, and remediation strategies for forecasting," International Journal of Forecasting, Elsevier, vol. 14(1), pages 95-110, March.
  43. Zvi Schwartz & Timothy Webb & Jean-Pierre I van der Rest & Larissa Koupriouchina, 2021. "Enhancing the accuracy of revenue management system forecasts: The impact of machine and human learning on the effectiveness of hotel occupancy forecast combinations across multiple forecasting horizo," Tourism Economics, , vol. 27(2), pages 273-291, March.
  44. Petropoulos, Fotios & Spiliotis, Evangelos & Panagiotelis, Anastasios, 2023. "Model combinations through revised base rates," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1477-1492.
  45. Dinesh Reddy Vangumalli & Konstantinos Nikolopoulos & Konstantia Litsiou, 2019. "Clustering, Forecasting and Cluster Forecasting: using k-medoids, k-NNs and random forests for cluster selection," Working Papers 19016, Bangor Business School, Prifysgol Bangor University (Cymru / Wales).
  46. Talagala, Thiyanga S. & Li, Feng & Kang, Yanfei, 2022. "FFORMPP: Feature-based forecast model performance prediction," International Journal of Forecasting, Elsevier, vol. 38(3), pages 920-943.
  47. Thomson, Mary E. & Pollock, Andrew C. & Gönül, M. Sinan & Önkal, Dilek, 2013. "Effects of trend strength and direction on performance and consistency in judgmental exchange rate forecasting," International Journal of Forecasting, Elsevier, vol. 29(2), pages 337-353.
  48. Vicki G. Morwitz & David C. Schmittlein, 1998. "Testing New Direct Marketing Offerings: The Interplay of Management Judgment and Statistical Models," Management Science, INFORMS, vol. 44(5), pages 610-628, May.
  49. Webby, Richard & O'Connor, Marcus, 1996. "Judgemental and statistical time series forecasting: a review of the literature," International Journal of Forecasting, Elsevier, vol. 12(1), pages 91-118, March.
  50. Arvan, Meysam & Fahimnia, Behnam & Reisi, Mohsen & Siemsen, Enno, 2019. "Integrating human judgement into quantitative forecasting methods: A review," Omega, Elsevier, vol. 86(C), pages 237-252.
  51. Adya, Monica, 2000. "Corrections to rule-based forecasting: findings from a replication," International Journal of Forecasting, Elsevier, vol. 16(1), pages 125-127.
  52. Mohamed Gaber & Edward J. Lusk, 2018. "Analytical Procedures Phase of PCAOB Audits: A Note of Caution in Selecting the Forecasting Model," Applied Finance and Accounting, Redfame publishing, vol. 4(1), pages 73-81, February.
  53. JS Armstrong, 2004. "Forecasting for Environmental Decision Making," General Economics and Teaching 0412023, University Library of Munich, Germany.
  54. Scott Moss & Bruce Edmonds & Steve Wallis, 1997. "Validation and Verification of Computational Models with Multiple Cognitive Agents," Discussion Papers 97-25, Manchester Metropolitan University, Centre for Policy Modelling.
  55. Arora, Siddharth & Taylor, James W., 2018. "Rule-based autoregressive moving average models for forecasting load on special days: A case study for France," European Journal of Operational Research, Elsevier, vol. 266(1), pages 259-268.
  56. Thiyanga S Talagala & Rob J Hyndman & George Athanasopoulos, 2018. "Meta-learning how to forecast time series," Monash Econometrics and Business Statistics Working Papers 6/18, Monash University, Department of Econometrics and Business Statistics.
  57. Kusters, Ulrich & McCullough, B.D. & Bell, Michael, 2006. "Forecasting software: Past, present and future," International Journal of Forecasting, Elsevier, vol. 22(3), pages 599-615.
  58. Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzán, Alfred G., 2014. "Combining forecasts: An application to elections," International Journal of Forecasting, Elsevier, vol. 30(1), pages 43-54.
  59. JS Armstrong & Fred Collopy, 2004. "Integration of Statistical Methods and Judgment for Time Series," General Economics and Teaching 0412024, University Library of Munich, Germany.
  60. Adrian Gepp & Kuldeep Kumar & Sukanto Bhattacharya, 2010. "Business failure prediction using decision trees," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(6), pages 536-555.
  61. Gardner Jr., Everette S. & Diaz-Saiz, Joaquin, 2008. "Exponential smoothing in the telecommunications data," International Journal of Forecasting, Elsevier, vol. 24(1), pages 170-174.
  62. Gardner, Everette S. & Anderson, Elizabeth A., 1997. "Focus forecasting reconsidered," International Journal of Forecasting, Elsevier, vol. 13(4), pages 501-508, December.
  63. Han, Weiwei & Wang, Xun & Petropoulos, Fotios & Wang, Jing, 2019. "Brain imaging and forecasting: Insights from judgmental model selection," Omega, Elsevier, vol. 87(C), pages 1-9.
  64. Qi, Lingzhi & Li, Xixi & Wang, Qiang & Jia, Suling, 2023. "fETSmcs: Feature-based ETS model component selection," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1303-1317.
  65. Remus, William & O'Connor, Marcus & Griggs, Kenneth, 1995. "Does reliable information improve the accuracy of judgmental forecasts?," International Journal of Forecasting, Elsevier, vol. 11(2), pages 285-293, June.
  66. Adya, Monica & Collopy, Fred & Armstrong, J. Scott & Kennedy, Miles, 2001. "Automatic identification of time series features for rule-based forecasting," International Journal of Forecasting, Elsevier, vol. 17(2), pages 143-157.
  67. Graff, Mario & Peña, Rafael & Medina, Aurelio & Escalante, Hugo Jair, 2014. "Wind speed forecasting using a portfolio of forecasters," Renewable Energy, Elsevier, vol. 68(C), pages 550-559.
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