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Kauppakorkeakoulu | Laskentatoimen laitos | Laskentatoimi | 2011
Tutkielman numero: 12549
Profit Driver Based Forecasting, Case Rautaruukki Oyj
Tekijä: Nikkola, Janne
Otsikko: Profit Driver Based Forecasting, Case Rautaruukki Oyj
Vuosi: 2011  Kieli: eng
Laitos: Laskentatoimen laitos
Aine: Laskentatoimi
Asiasanat: laskentatoimi; accounting; ennusteet; forecasts; tutkimusmenetelmät; research methods; tilastot; statistics; mittarit; ratings
Sivumäärä: 103
Kokoteksti:
» hse_ethesis_12549.pdf pdf  koko: 2 MB (1099040)
Avainsanat: forecasts; ennusteet
Tiivistelmä:
AALTO UNIVERSITY SCHOOL OF ECONOMICS ABSTRACT Research on Accounting Janne Nikkola

PROFIT DRIVER BASED FORECASTING, Case Rautaruukki Oyj

Purpose of the thesis The purpose of this thesis is to find suitable forecasting methods and possible profit-loss drivers for profit-loss forecasting. The second purpose of the thesis is to review the profit forecasting process of a case company and propose actions to improve the performance of the forecasting.

Research material In the empirical part of the thesis, a case company’s profit forecasting accuracy is examined. The selected data consists of statistical forecasts for case company’s profit-loss statement items (net sales, cost of goods sold and operating income) for year 2009. The drivers used in this thesis were selected from company’s possible market drivers list.

Research Methods Forecasting accuracy is studied by using different forecasting methods which are selected from the literature of statistical forecasting. In addition, different time series methods are used to simulate profit-loss forecasting processes and behaviour of selected drivers in profit forecasting process.

Results The results showed that there are not unambiguous number of drivers in profit forecasting, which could improve by themselves the profit forecasting accuracy. Furthermore, better forecasting accuracy is achieved when combining several methods. The result for the case company is the numbers of drivers to be used in profit forecasting are dependent on the market segments that the divisions operate.

Keywords Forecasting, judgemental forecasting methods, statistical forecasting methods, forecast error measures, drivers
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