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Executive SummaryThis article assesses the extent to which non-financial measures of Internet usage are incrementally value-relevant over and above basic financial information across four Internet industry sectors. Using ordinary least squares (OLS) regression analysis we test the extent to which net income, book value, unique users, page views, and hours per user are able to explain stock prices for a sample of 341 firm quarters for the period Q1: 1999-Q1: 2000. Our results indicate that net income has no ability to explain market values for the pooled sample or for any of the Internet sectors examined. With respect to the non-financial variables, we find that for e-tailers and content/community firms, page views have the greatest explanatory power. For service companies, unique users have the greatest ability to explain market values, and for infrastructure companies, none of our non-financial variables are significant.

In this paper we show that not taking into account the fact that fund managers “deviate” from their stated categories biases upward their alphas. When evaluating fund managers most studies compare managers against the S&P 500 regardless of the sectors managers actually invest in. This procedure does not take into account that an important proportion of US stock managers invest in medium and small companies. This neglect biases performance results. In the international stock arena, not only do studies use the incorrect benchmark but they also neglect to take into account the fact that managers deviate from their stated sector. In this paper we not only employ the correct category the managers invest in but we also take into account the fact that managers systematically drift away from their stated category. This drift occurs for approximately half the funds examined and causes the estimated alpha of managers to be on average 45 basis points higher than it should be if we were to undertake the multiple regression that fund drift demands. In addition to using the right benchmarks, adjusting for “drift” in this paper we chose to use as “benchmarks” the ETF’s in each category so as to compare managers not against theoretical constructs, but against an actual investable vehicle in the corresponding category.

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