Abstract
Being provided with a unique high-frequency dataset, we are able to show by means of an empirical analysis that computer-based traders, i.e. Algorithmic Trading (AT) engines, behave significantly different from human traders with regard to their order cancellation behaviour. Furthermore, given exactly this difference we point out that the application of well-established “traditional” liquidity measurement methods may no longer be unequivocally applicable in today’s electronic markets. At least those liquidity measures that are based on committed liquidity need to be questioned.
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Groth, S.S. (2009). Algorithmic Trading Engines and Liquidity Contribution: The Blurring of “Traditional” Definitions. In: Godart, C., Gronau, N., Sharma, S., Canals, G. (eds) Software Services for e-Business and e-Society. I3E 2009. IFIP Advances in Information and Communication Technology, vol 305. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04280-5_18
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DOI: https://doi.org/10.1007/978-3-642-04280-5_18
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