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In this paper, we propose measures for characterizing the expected and unexpected cost of trading that can be applied to analyze automated electronic auction markets. Using a unique database which contains the full state of the order book for three stocks (Daimler-Chrysler, Deutsche Telekom and SAP) traded on the XETRA platform, we show that the unexpected cost of trading, but not the expected cost of trading, can depend on international linkages of stock markets. Both measures also depend on structural characteristics of the exchange (time of day patterns). More precisely, the expected cost of trading increases strongly with the traded volume and is much higher at the start of the day. The unexpected cost of trading increases moderately with the traded volume, is much higher at the start of the day and increases sharply when pre-trading starts in the US markets. |
