Regulators attempt to act on a financial market based on the intelligent and reasonable formulation of rules. For example, changing the market micro-structure at the lowest level in the hierarchy, can change the way that asset prices assimilate changes in information variables Zk,t or θi,m,t. Similarly, changes in accounting rules could change the meaning and behaviour of bottom-up information variables θi,m,t and changes in economic policy and policy implementation can change the meaning of top-down information variables Zk,t and influence shared risk factors rp,t.
In hierarchical analysis, theories and plans may be embodied in a symbolic system to build effective and robust models to be used for detecting deeper dependencies and emergent phenomena. Mechanisms for the transmission of information and asymmetric information information have impacts on market quality. Thus, Regulators can impact the activity and success of all the other actors, either directly or indirectly through knock-on effects. Examples include the following: Investor behaviour could change the goal selection of Traders; change in the latter could in turn impact variables coupled to Traders activity in such a way that Profiteers are able to benefit from change in liquidity or use leverage as a mean to achieve profit targets and overcome noise.
Idealistically, Regulators may aim for increasing productivity, managing inflation, reducing unemployment and eliminating malfeasance. However, the circumvention of rules, usually in the name of innovation or by claims of greater insight on optimality, is as much part of a complex system in which participants can respond to rules. Tax arbitrages are examples of actions which manipulate reporting to reduce levies paid to a profit- facilitating system. In regulatory arbitrage, rules may be followed technically, but nevertheless use relevant new information which has not been accounted for in system rules. Such activities are consistent with goals of profiteering but are not necessarily in agreement with longer term optimality of reliable and fair markets.
Rulers, i.e. agencies which control populations more generally, also impact markets and economies. Examples of top-down causation here include segregation of workers and differential assignment of economic rights to market participants, as in the evolution of local miners’ rights in the late 1800’s in South Africa and the national Native Land act of 1913 in South Africa, international agreements such as the Bretton Woods system, the Marshall plan of 1948, the lifting of the gold standard in 1973 and the regulation of capital allocations and capital flows between individual and aggregated participants. Ideas on target-based goal selection are already in circulation in the literature on applications of viability theory and stochastic control in economics. Such approaches provide alternatives to the Laplacian ideal of attaining perfect prediction by offering analysable future expectations to regulators and rulers.