On the predictability of firm performance via simple time-series and econometric models: evidence from UK SMEs
AbstractThis article examines the predictive accuracy of simple time-series and econometric models on forecasting firm performance in terms of sales turnover. Evidence from Small and Medium sized Enterprises (SMEs) in the United Kingdom are presented. The study identifies operational rules under which the class of simple econometric regression models is more accurate than simple time-series forecasting alternatives, thus more appropriate to back-up multiple investment decisions.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Taylor and Francis Journals in its journal Applied Economics Letters.
Volume (Year): 17 (2010)
Issue (Month): 3 ()
Contact details of provider:
Web page: http://www.tandf.co.uk/journals/routledge/13504851.html
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Assimakopoulos, V. & Nikolopoulos, K., 2000. "The theta model: a decomposition approach to forecasting," International Journal of Forecasting, Elsevier, vol. 16(4), pages 521-530.
- K. Maris & G. Pantou & K. Nikolopoulos & E. PagourtzI & V. Assimakopoulos, 2004. "A study of financial volatility forecasting techniques in the FTSE/ASE 20 index," Applied Economics Letters, Taylor and Francis Journals, vol. 11(7), pages 453-457.
- Perry Sadorsky, 2005. "Stochastic volatility forecasting and risk management," Applied Financial Economics, Taylor and Francis Journals, vol. 15(2), pages 121-135.
- C. Petropoulos & K. Nikolopoulos & A. Patelis & V. Assimakopoulos, 2005. "A technical analysis approach to tourism demand forecasting," Applied Economics Letters, Taylor and Francis Journals, vol. 12(6), pages 327-333.
- Makridakis, Spyros & Hibon, Michele, 2000. "The M3-Competition: results, conclusions and implications," International Journal of Forecasting, Elsevier, vol. 16(4), pages 451-476.
- Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
- D. E. Allen & H. M. Salim, 2005. "Forecasting profitability and earnings: a study of the UK market (1982-2000)," Applied Economics, Taylor and Francis Journals, vol. 37(17), pages 2009-2018.
- Gabriel Hawawini & Venkat Subramanian & Paul Verdin, 2003. "Is performance driven by industry or firm-specific factors? A new look at the evidence," ULB Institutional Repository 2013/14188, ULB -- Universite Libre de Bruxelles.
- George Halkos & Ilias Kevork, 2006. "Forecasting the stationary AR(1) with an almost unit root," Applied Economics Letters, Taylor and Francis Journals, vol. 13(12), pages 789-793.
- K. Maris & K. Nikolopoulos & K. Giannelos & V. Assimakopoulos, 2007. "Options trading driven by volatility directional accuracy," Applied Economics, Taylor and Francis Journals, vol. 39(2), pages 253-260.
- Varum, Celeste Amorim & Rocha, Vera Catarina Barros, 2011. "Do foreign and domestic firms behave any different during economic slowdowns?," International Business Review, Elsevier, vol. 20(1), pages 48-59, February.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty).
If references are entirely missing, you can add them using this form.