Heuristic Stochastic Controller for Stabilizing Exchange Rate Dynamics Under Uncertainty
Abstract
In this paper, we develop the Stochastic Central Bank Exchange Rate Intervention (SCERI) model, based on two stochastic differential equations represented by two different Arithmetic Brownian Motions. The aim is to mathematically denote the noise from noise traders and the central bank interventios, which is a stochastic controller to assist effective policy decisions. To address SCERI’s challenges, we propose time varying target zones and values in order to support central banks to limit uncertainty. While these interventions can increase stability in the process, they require calibration of the various bounds or they may create instability. Even though there are concerns about intervention risks, our model is certainly feasible to alleviate the complications of stabilizing the currency. The proposed heuristic stochastic controller operates under the influence of noise traders, market participants whose actions cause the random fluctuations. With the use of this model and algorithm, central banks have essential tools to stabilize exchange rate dynamics as the model allows the adjustment of intervention strategies to counteract market uncertainty.