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Automated Finance: The Assumptions and Behavioral Aspects of Algorithmic Trading

Automated trading now dominates the financial markets. Yet no philosophy of academic research into the topic exists. As the growth in automated trading suggests their greater returns and predictability, this paper examines stability and statistical control of trading process outputs as method of justifying predictions of future performance. New assumptions presented can form a foundation for positive research under this revolutionary paradigm, one almost completely ignored in the financial literature. The traditional financial literature rests on the assumption of normality of inputs, while trading systems aspire to the more rigorous engineering standard of justification. The end game is that now behavioral aspects, not of traders but of trading system research and development projects, drive market returns.