Home court advantage

Does distance reduce the quality of the information for investors? There is a large body of literature that investigates the role of distance in investors’ portfolio decisions and investment performance. Most of it focuses on investors who are separated by borders, but a growing number of studies investigate the role of distance within countries. Some of the literature concludes that local investors have an advantage and much of the international finance literature concludes that at least part of the home bias can be accounted for by the information advantage of local investors.

However, there are studies arguing that foreign investors are better informed than local ones. Contrary to most studies focusing on investor choices and performance, my colleagues and I have directly investigated the question of whether distance affects the quality of information possessed by one group of market participants: the analysts. It is known that, in the U.S., analysts who are closer to the headquarters of a firm have an information advantage. Our study found that these local analysts have a significant information advantage over foreign analysts in a large sample of countries.

Home advantage
We investigated the relationship between the precision of earnings forecasts of local analysts and that of foreign analysts for 32 countries from 2001 to 2003. We defined an analyst as local if his country location is the same as that of the firm he covers, regardless of whether he is working for a local research firm or a research firm from a foreign country. Our main measure of accuracy for an analyst is his price-scaled absolute forecast error minus the average price-scaled absolute forecast error across analysts for the earnings forecasted.

We also defined the local analyst advantage as the difference between the accuracy of local analysts and the accuracy of foreign ones. We found that the local analysts have better information, and predict earnings with more precision. The difference in the average forecast error in univariate comparison between local and foreign analysts corresponds to 7.8% of the average price-scaled forecast error. When we controlled for various determinants of the forecast error, the local advantage falls slightly in most cases.

Our dataset made it possible to investigate whether the advantage of local analysts arises because they belong to local brokerage houses that might have established relationships with the local firms they follow or because local analysts are located close to the firms they follow. We considered separately local analysts belonging to local firms and local analysts belonging to foreign firms. We found that there is no difference between the two groups of analysts.

A plausible explanation for the local advantage is that local analysts have access to information because they are on the spot. They can talk to firm representatives in person and they have access to information by observing what goes on in firms directly. For instance, if a firm is unusually busy, they might observe lots of trucks being loaded. Alternatively, they might talk to employees, customers, and competitors. With this explanation, we would expect the local advantage to be inversely related to the quality of the information put forward by the firm. We found that this is strongly the case.

Using the Standard & Poor’s Transparency and Disclosure index, we found a smaller local advantage for analyst with firms that have an index value above the sample median. Similarly, the analysts’ local advantage is significantly lower in countries with above-median accounting transparency. There is no local advantage for analysts in countries where earnings management is less prevalent. Further, the local advantage is significantly lower in countries where stock returns incorporate more idiosyncratic information. More precisely, the local advantage is strong in countries where the aggregate stock market return has much explanatory power for individual stock returns as measured by the R2 measure of Morck, Yeung, and Yu (2000).

—Kee-Hong Bae, Bank of Montreal associate professor of Finance, Queen’s School of Business

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