On the predictability of firm performance via simple time-series and econometric models: evidence from UK SMEs
This 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.
If 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.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 17 (2010)
Issue (Month): 3 (February)
|Contact details of provider:|| Web page: http://www.tandfonline.com/RAEL20|
|Order Information:||Web: http://www.tandfonline.com/pricing/journal/RAEL20|
References listed on IDEAS
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.
- D. E. Allen & H. M. Salim, 2005. "Forecasting profitability and earnings: a study of the UK market (1982-2000)," Applied Economics, Taylor & 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.
- 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.
- C. Petropoulos & K. Nikolopoulos & A. Patelis & V. Assimakopoulos, 2005. "A technical analysis approach to tourism demand forecasting," Applied Economics Letters, Taylor & Francis Journals, vol. 12(6), pages 327-333.
- George Halkos & Ilias Kevork, 2006. "Forecasting the stationary AR(1) with an almost unit root," Applied Economics Letters, Taylor & Francis Journals, vol. 13(12), pages 789-793.
- Perry Sadorsky, 2005. "Stochastic volatility forecasting and risk management," Applied Financial Economics, Taylor & Francis Journals, vol. 15(2), pages 121-135.
- K. Maris & K. Nikolopoulos & K. Giannelos & V. Assimakopoulos, 2007. "Options trading driven by volatility directional accuracy," Applied Economics, Taylor & Francis Journals, vol. 39(2), pages 253-260.
- 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 & Francis Journals, vol. 11(7), pages 453-457.
When requesting a correction, please mention this item's handle: RePEc:taf:apeclt:v:17:y:2010:i:3:p:279-282. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Chris Longhurst)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.