TY - JOUR

T1 - Dynamic Robustification of Trading Management Strategies for Unstable Immersion Environments

AU - Musaev, Alexander

AU - Makshanov, Andrey

AU - Grigoriev, Dmitry

PY - 2023

Y1 - 2023

N2 - The paper considers the problem of constructing channel managementstrategies for market chaos conditions. The nature of dynamic chaos violates the probabilistic-statistical paradigm's fundamental principle of experiment repeatability. Under these conditions, the traditional statistical methods of evaluation are not effective, and the generated management decisions are unstable. There is a need to create management strategies thatproduce effective decisions for a wide variety of dynamic characteristics ofobservation series generated by market chaos. In this article, we have considered two variants of such robustification using channel managementstrategies as an ex-ample. The first approach is based on the assumptionthat the optimal solution for the observation interval with the least favorabledynamics for this management strategy will produce solutions that aresatisfactory at other observation sites as well. However, our numerical studydoes not confirm this assumption. Explanation is that optimization of parameters for highly dynamic segments with abrupt changes in the observedprocess produces degenerate decisions. The optimal control parameterscorresponding to them are suitable only for a very narrow range of possiblevariations of the observed process. The second approach to the dynamicrobustification of management strategies is based on searching for optimalparameters of the strategy on large observation intervals. It is assumed thatat such observation intervals, chaos will demonstrate the most variants oflocal dynamics, and the found parameters will be adapted simultaneously tothe most diverse variations in dynamic characteristics of observation series.In general, this approach gives an encouraging result, however, as expected, the decrease in performance in the non-matching data segmentturned out to be significant.

AB - The paper considers the problem of constructing channel managementstrategies for market chaos conditions. The nature of dynamic chaos violates the probabilistic-statistical paradigm's fundamental principle of experiment repeatability. Under these conditions, the traditional statistical methods of evaluation are not effective, and the generated management decisions are unstable. There is a need to create management strategies thatproduce effective decisions for a wide variety of dynamic characteristics ofobservation series generated by market chaos. In this article, we have considered two variants of such robustification using channel managementstrategies as an ex-ample. The first approach is based on the assumptionthat the optimal solution for the observation interval with the least favorabledynamics for this management strategy will produce solutions that aresatisfactory at other observation sites as well. However, our numerical studydoes not confirm this assumption. Explanation is that optimization of parameters for highly dynamic segments with abrupt changes in the observedprocess produces degenerate decisions. The optimal control parameterscorresponding to them are suitable only for a very narrow range of possiblevariations of the observed process. The second approach to the dynamicrobustification of management strategies is based on searching for optimalparameters of the strategy on large observation intervals. It is assumed thatat such observation intervals, chaos will demonstrate the most variants oflocal dynamics, and the found parameters will be adapted simultaneously tothe most diverse variations in dynamic characteristics of observation series.In general, this approach gives an encouraging result, however, as expected, the decrease in performance in the non-matching data segmentturned out to be significant.

KW - chaos processes

KW - unstable immersion environment

KW - observation series

KW - channel strategy

KW - numerical studies

KW - dynamic stability

KW - robustness

M3 - Article

VL - 19

SP - 19

EP - 30

JO - Montenegrin Journal of Economics

JF - Montenegrin Journal of Economics

SN - 1800-5845

IS - 1

ER -