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We analyze the role of different kinds of primary and secondary market interventions for the government's goal to maximize its revenues from public bond issuances. Some of these interventions can be thought of as characteristics of a "primary dealer system". After all, we see that a primary dealer system with a restricted number of participants may be useful in case of only restricted competition among sufficiently heterogeneous market makers. We further show that minimum secondary market turnover requirements for primary dealers with respect to bond sales seem to be in general more adequate than the definition of maximum bid-ask-spreads or minimum turnover requirements with respect to bond purchases. Moreover, official price management operations are not able to completely substitute for a system of primary dealers. Finally it should be noted that there is in general no reason for monetary compensations to primary dealers since they already possess some privileges with respect to public bond auction.
Die Betreuer am neuen Markt sollen die Effizienz des Handels durch Bereitstellung zusätzlicher Liquidität erhöhen. Die vorliegende Studie untersucht den Liquiditätsbeitrag der Betreuer in zwei aufeinanderfolgenden Jahren. Die Beteiligung der Betreuer am Umsatz des Marktes hat im beobachteten Zeitraum deutlich abgenommen. Ihre Orderlimits und -volumina hingegen haben die Markttiefe erhöht. Weiterhin zeigt sich, daß die Betreuer sowohl in liquiditätsschwachen Titeln als auch in liquiditätsschwachen Marktphasen zur Steigerung der Liquidität beigetragen haben.
Algorithmic trading engines versus human traders – do they behave different in securities markets?
(2009)
After exchanges and alternative trading venues have introduced electronic execution mechanisms worldwide, the focus of the securities trading industry shifted to the use of fully electronic trading engines by banks, brokers and their institutional customers. These Algorithmic Trading engines enable order submissions without human intervention based on quantitative models applying historical and real-time market data. Although there is a widespread discussion on the pros and cons of Algorithmic Trading and on its impact on market volatility and market quality, little is known on how algorithms actually place their orders in the market and whether and in which respect this differs form other order submissions. Based on a dataset that – for the first time – includes a specific flag to enable the identification of orders submitted by Algorithmic Trading engines, the paper investigates the extent of Algorithmic Trading activity and specifically their order placement strategies in comparison to human traders in the Xetra trading system. It is shown that Algorithmic Trading has become a relevant part of overall market activity and that Algorithmic Trading engines fundamentally differ from human traders in their order submission, modification and deletion behavior as they exploit real-time market data and latest market movements.