Stabilizing instability‐suboptimality‐and‐chaos‐prone fluctuations at crisis junctures: Stochastic possibilities for crisis management

There is a rich array of ways in which unstable, suboptimal and chaos‐prone fluctuations could appear at crisis junctures. The richness of the patterns associated with such fluctuations presents considerable challenges to the theory of crises as well as the policies targeting various tendencies induced by crises. Dealing with complexly interwoven unstable, suboptimal and potentially chaotic tendencies is not an easy task, which may require new combinations of methods analysing the causal connections and feedback relations embedded in the web of relations characterizing the crisis‐junctures. In this paper, we develop an illustrative dynamic model that takes into account such causally connected feedback relations so as to construct and simulate stochastic policy options, which can influence and help stabilize unstable, suboptimal and chaotic trajectories of exchange rates at financial crisis junctures. For reasons of convenience and practical relevance, we exemplified such policies using taxes. One of the constructed examples makes use a stochastic taxing policy to influence the coefficient of adjustment, which influences the amount of adjustments and hence fluctuations in the market. We incorporate a software‐based optimization setup into the simulation model to find the optimal values of the policy parameter to be used for the purpose of simulating the trajectories of the exchange rates. It turns out that the suggested policies could influence/reduce the fluctuations in the market and hence help stabilize unstable or chaotic exchange rate trajectories. The second example in the paper is concerned with an empirical case relating to a particular financial crisis juncture of Turkey during May–November 2018.