Intangibles-intensive firms, which are often founded on innovation and human capital, tend to offer higher returns relative to physical assets–intensive firms. But the author shows that the risk-adjusted returns of actively managed mutual funds decrease (increase) proportionately to their exposure to intangibles-intensive (physical assets–intensive) firms. The negative impact of intangibles-intensive assets on fund performance seems to be attributable to extrapolation bias and decreases in experiential learning.

The last two decades have been marked by spectacular growth in firms with intangibles-intensive assets. Firms with intangibles-intensive assets offer ample opportunities for higher returns to investors. The impact of the nature of the firm (physical versus intangible assets) on actual fund returns is increasingly important for both investors and fund managers because intangibles-intensive firms now form a sizable segment of the capital markets.

The author concludes that fund managers exhibit considerably inferior (superior) skills when their portfolios are heavily weighted in intangibles-intensive (physical assets–intensive) assets. Inferior fund performance can be attributed to the extrapolation bias, which increases with the increase in tilt toward intangibles-intensive firms. Extrapolation bias (trend-chasing strategies) and the negative impact on returns of investments in intangibles-intensive firms decrease as funds gain experience. The author suggests that fund managers exhibit superior skill when focusing on companies that are difficult to value—except when they are intangibles-intensive firms.

The data for the study are from the CRSP Survivor-Bias-Free US Mutual Fund database and the Thomson Reuters financial holdings database. The sample includes 3,165 unique actively managed US equity mutual funds from 1980 to 2009. The fund composition results in 98,231 unique fund-quarter observations for portfolio holdings and 285,419 monthly return observations.

Funds with a tilt toward intangibles-intensive firms are identified by using the value-weighted ratio of research and development (R&D) expenses to property, plant, and equipment (PP&E) expenses of the firms held in the portfolio. Portfolio performance is calculated by using multifactor models adjusted for potential omitted systematic factors associated with the nature of the firm.

The ratio of R&D expense to PP&E expense defines the concentration of intangibles-intensive versus physical assets–intensive firms in the fund; the higher the ratio, the higher the fund’s concentration in intangibles-intensive firms. Fund performance is evaluated based on various factor adjustment models. The funds with a high ratio underperform the funds with a low ratio.

The author suggests that mutual funds tilted toward intangibles-intensive firms have inferior mean–variance properties but higher maximum payoffs and volatility than those tilted toward physical assets–intensive firms, which affects the returns to the fund’s investors. The author also conducts a number of robustness tests and notes that the conclusions are still the same.

The valuation of intangibles-intensive firms is a challenge because of the difficulty in valuing intangible assets. Using fund holdings of actively managed US mutual funds, the author shows a significant link between the value created by fund managers’ skill and the nature of the firms they invest in. The author brings attention to the possibility that the cost of active management may not be justified when considering investments in a segment of the “new economy.” Further research along these lines could provide interesting insights into the active versus passive management debate.