From decision optimization to satisficing: Regulation of automated trading in the US financial markets

Market fragmentation, technical complexity and information asymmetry drive the regulation of financial markets. We examine how government bodies develop and implement policy mandates for regulatory oversight of automated trading. Simon's theory of bounded rationality guides the research enquiry on regulatory decision choices and outcomes. Primary and secondary data reveal four phases of evolutionary technological change in financial markets. Each phase presents financial regulators with unprecedented policy challenges in preventing systemic and firm-specific risk in financial markets. Findings show regulatory mandates eschew ex-ante for ex-post decision criteria, as constrained optimization results in regulators’ seeking satisfactory solutions to mitigate financial market risk.