By Michael Kearns, Alex Kulesza, Yuriy Nevmyvaka
Abstract:
Addressing the ongoing controversy over aggressive high-frequency trading practices in financial markets, we report the results of an extensive empirical study estimating the maximum possible profitability of such practices, and arrive at figures that are surprisingly modest. Our findings highlight the tension between execution costs and trading horizon confronted by high-frequency traders, and provide a controlled and large-scale empirical perspective on the high-frequency debate that has heretofore been absent. Our study employs a number of novel empirical methods, including the simulation of an "omniscient" high-frequency trader who can see the future and act accordingly.
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Random portfolios select a sample of portfolios that obey a given set of constraints.
They have many uses -- measuring performance is one of the most important.
Performance can be measured much more accurately with random portfolios than
with other methods. The measurement can be on hypothetical strategies in backtests
as well as traditional performance measurement.