The lately observed distress in macroeconomic conditions around the world has shown that fiscal and monetary policymakers would benefit from an early and accurate prediction of changes in economic activity. Per today GDP is a commonly used proxy for this. This paper attempts to provide this through stock indices weighted on various fundamental data, rather than the usual market capitalization weighting. The intuition behind this is that an index weighted on fundamental data is more representative of the real economy than an index weighted on market capitalization. In general there are few leading indicators for the Norwegian GDP and our methodology has not been tested for the Norwegian GDP or internationally. In this thesis we start by presenting fundamental indexing as pioneered by the research agency Research Affiliates. Following is the basics of Gross Domestic Product and its shortcomings, as well as an overview of leading indicators in Norway. Next we perform a thorough analysis of the developed fundamental indices (FI), and the different comparable indicators. We found that leading indicators based on fundamental metrics in general perform well compared to the peer indicators chosen in this thesis. Among all the 14 indicators examined, the fundamentally based indices are ranked 2-4 and 6-8 when ranked by both Root Mean Squared Errors and Root Mean Squared Forecasting Errors. The thesis concludes that leading indicators based on the methods presented in this paper are well suited as single leading indicators for Norwegian GDP. However, only three out of six FI based indicators perform better than the indicator based on the market capitalization weighted OBX index. The FI based indicators that performed best includes averages of different fundamental data. We believe that for this methodology to perform better than a regular market capitalization based indicator, the Fundamental Indices must be weighted in such a way that it represents the companies in more than one fundamental metric.
|Educations||MSc in Applied Economics and Finance, (Graduate Programme) Final Thesis|
|Number of pages||127|