Investment performance and market share : a study of the German mutual fund industry

We study a set of German open-end mutual funds for a time period during which this industry emerged from its infancy. In those years, the distribution channel for mutual funds was dominated by the brick-and-mortar retail networks of the large universal banks. Using monthly observations from 12/1986 through 12/1998, we investigate if cross-sectional return differences across mutual funds affect their market shares. Although such a causal relation has been established in highly competitive markets, such as the United States, the rigid distribution system in place in Germany at the time may have caused retail performance and investment performance to uncouple. In fact, although we observe stark differences in investment performance across mutual funds (and over time), we find no evidence that cross-sectional performance differences affect the market shares of these funds. Klassifikation: G 2

Performance and market share: evidence from the German mutual fund industry

In this paper we analyze the relation between fund performance and market share. Using three performance measures we first establish that significant differences in the risk-adjusted returns of the funds in the sample exist. Thus, investors may react to past fund performance when making their investment decisions. We estimated a model relating past performance to changes in market share and found that past performance has a significant positive effect on market share. The results of a specification test indicate that investors react to risk-adjusted returns rather than to raw returns. This suggests that investors may be more sophisticated than is often assumed

Identification of WISE J000100.45+065259.6 as an M8.5+T5 Spectral Binary Candidate

[not part of RNAAS note] We report the discovery of WISE J000100.45+065259.6 as a very low mass star/brown dwarf spectral binary candidate, on the basis of low resolution near-infrared spectroscopy obtained with IRTF/SpeX. Decomposition of the spectrum indicates component types of M8.5+T5 with a predicted $\Delta{J}$ = 3.5. As the majority of confirmed spectral binary candidates to date are very closely-separated systems ($\rho$ $\lesssim$ 3 AU; $P$ $\lesssim$ 15~yr), this source may provide mass measurements across the hydrogen burning limit within the decade.Comment: 3 pages, 1 figure, accepted to Research Notes of the AA

Magnetic inflation and stellar mass. V. Intensification and saturation of M-dwarf absorption lines with Rossby number

In young Sun-like stars and field M-dwarf stars, chromospheric and coronal magnetic activity indicators such as Hα, X-ray, and radio emission are known to saturate with low Rossby number (Ro lesssim 0.1), defined as the ratio of rotation period to convective turnover time. The mechanism for the saturation is unclear. In this paper, we use photospheric Ti i and Ca i absorption lines in the Y band to investigate magnetic field strength in M dwarfs for Rossby numbers between 0.01 and 1.0. The equivalent widths of the lines are magnetically enhanced by photospheric spots, a global field, or a combination of the two. The equivalent widths behave qualitatively similar to the chromospheric and coronal indicators: we see increasing equivalent widths (increasing absorption) with decreasing Ro and saturation of the equivalent widths for Ro lesssim 0.1. The majority of M dwarfs in this study are fully convective. The results add to mounting evidence that the magnetic saturation mechanism occurs at or beneath the stellar photosphere.Published versio

GDP mimicking portfolios and the cross-section of stock returns

The components of GDP (residential investment, durables, nondurables, equipment and software, and business structures) display a pronounced lead-lag structure. We investigate the implications of this lead-lag structure for the cross-section of asset returns. We find that the leading GDP components perform well in explaining the returns of 25 size and book-to-market portfolios and do reasonably well in explaining the returns of 10 momentum portfolios. The lagging components do a poor job at explaining the returns of 25 size and book-to-market portfolios but explain the return of momentum portfolios very well. A three-factor model with the market risk premium, one leading and one lagging GDP component compares very favorably with the Carhart four-factor model in jointly explaining the returns on 25 size/book-to-market portfolios, 10 momentum portfolios and 30 industry portfolios