| dc.description.abstract | How accurate financial analysts are in their earnings forecasts, and how share prices are affected by whether a company is able to outperform market expectations or not, has been researched extensively in the US. This thesis aims to analyze these questions as well, but by comparing firms with the highest market capitalizations from the US and Norway, as well as across the respective industries within the samples. The largest sample is of the Norwegian companies, which is the main focus, covering 22 large firms in many different industries. The US sample covers 8 large companies, and provides a meaningful comparison to the Norwegian sample, like a benchmark or control group. Historical data, for each company, stretches back at least 7 to 8 years, with a goal of 10 years, where the historical data covers daily share prices and quarterly earnings (EPS) estimates and reported values.
The data show that US financial analysts are on average significantly more accurate in their earnings forecasts, than their Norwegian counterparts, where the comparison is made using the Mean Absolute Percentage Error statistical technique. The high accuracy of US analysts is shown to have a connection with the number of estimates per quarter. US sample firms were also significantly more consistent in beating earnings estimates, but although the hypothesis was that an earnings surprise would lead to an increase in share prices and vice versa, no strong correlation can be implied and the effect of an earnings surprise, or vice versa, on share prices is shown to be negligible. The rest of the paper poses views and explanations on why US sample companies outperform Norwegian sample companies so consistently, and how this extrapolates to the broader market. | nb_NO |
