Proximity to Hubs of Expertise in Financial Analyst Forecast Accuracy

This paper investigates whether the geographical proximity of financial analysts to hubs of information and expertise can influence their forecasting accuracy. Recent studies show that the financial analyst forecasting process show a systematic difference in earnings forecast accuracy dependent on the geographical distance of analysts from the companies which they follow. The literature argues that local analysts issue more accurate forecasts because they have an informational advantage over analysts who are further away. Industrial centres can constitute important knowledge spillovers by creating formal and informal networks amongst firms and higher education and research institutions. In such a hub, information can easily flow and propagate. Our hypothesis is that physical proximity to these hubs, and not to the companies they follow, is an advantage for financial analysts, leading to the issue of more accurate forecasts. Using a sample of 205 observations related to 33 firms, across seven countries and ten sectors, our results are consistent with the hypothesis. Even though preliminary, and probably in part biased by sample selection issues, overall, the empirical evidence confirms the benefit of being part of a network, formal or informal, in which information, knowledge and expertise sharing can flow easily. We try to give some new evidence on what can cause variations in financial analyst accuracy by exploring these concepts, well known and analysed in other fields, but new in the context of financial analysts.