Technological innovations are altering the traditional value chain in securities trading. Hitherto the order handling, i.e. the appropriate implementation of a general trading decision into particular orders, has been a core competence of brokers. Labeled as Algorithmic Trading, the automation of this task recently found its way both into the brokers’ portfolio of service offerings as well as to their customers’ trading desks. The software performing the order handling thereby constantly monitors the market(s) in real-time and further evaluates historical data to dynamically determine appropriate points in time for trading. Within only a few years, this technology propagated itself among market participants along the entire value chain and has nowadays gained a significant market share on securities markets worldwide. Up to now, there has been only little research analyzing the impact of this special type of trading on markets. Markus Gsell's study aims at closing this gap by analyzing the drivers for adoption of this technology, the impact the application of this technology has on markets on a macro level, i.e. how the market outcome is affected, as well as on a micro level, i.e. how the exhibited trading behavior of these automated traders differs from normal traders’ behavior.
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