Open Access

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.

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 23

We reconsider the issue of price discovery in spot and futures markets. We use a threshold error correction model to allow for arbitrage operations to have an impact on the return dynamics. We estimate the model using quote midpoints, and we modify the model to account for time-varying transaction costs. We find that the futures market leads in the process of price discovery. The lead of the futures market is more pronounced in the presence of arbitrage signals. Thus, when the deviation between the spot and the futures market is large, the spot market tends to adjust to the futures market.

This paper studies the market quality of an internalization system which is designed as part of an open limit order book (the Xetra system operated by Deutsche Börse AG). The internalization sys-tem (Xetra BEST) guarantees a price improvement over the inside spread in the Xetra order book. We develop a structural model of this unique dual market environment and show that, while adverse selection costs of internalized trades are significantly lower than those of regular order book trades, the realized spreads (the revenue earned by the suppliers of liquidity) is significantly larger. The cost savings of the internalizer are larger than the mandatory price improvement. This suggests that internalization can be profitable both for the customer and the internalizer. JEL Classification: G10

Exchanges in Europe are in a process of consolidation. After the failure of the proposed merger between Deutsche Börse and Euronext, these two groups are likely to become the nuclei for further mergers and co-operation with currently independent exchanges. A decision for one of the groups entails a decision for the respective trading platform. Against that background we evaluate the attractiveness of the two dominant continental European trading systems. Though both are anonymous electronic limit order books, there are important differences in the trading protocols. We use a matched-sample approach to compare execution costs in Euronext Paris and Xetra. We find that both quoted and effective spreads are lower in Xetra. When decomposing the spread we find no systematic differences in the adverse selection component. Realized spreads, on the other hand, are significantly higher in Euronext. Neither differences in the number of liquidity provision agreements nor differences in the minimum tick size or in the degree of domestic competition for order flow explain the different spread levels. We thus conclude that Xetra is the more efficient trading system. JEL Classification: G10, G15