Geometric Brownian Motion on the Prediction of Foreign Exchange Rate: A Study on Indonesian Rupiah Rate

Abstract

Exchange rates wield significant influence on economic stability and activity, exerting considerable effects on overall economic conditions. A comprehensive understanding of the dynamics governing the Rupiah's exchange rate against foreign currencies is essential for accurate prognostication and strategic decision-making across economic and commercial sectors. Geometric Brownian Motion (GBM) emerges as a prevalent tool employed in predictive modelling. This necessitates the acquisition and analysis of data encompassing exchange rates involving three key currencies relative to the Indonesian Rupiah (USD, EUR, SGD). Utilizing GBM facilitates the projection of future exchange rate movements with a notable degree of reliability. Notably, the mean absolute percentage error (MAPE) values derived from six GBM iterations underscore a noteworthy forecasting precision, consistently falling below the 10% threshold. Furthermore, a more exhaustive examination involving 500 iterations reveals even smaller MAPE values, indicative of an enhanced accuracy in predicting exchange rate fluctuations compared to alternative methodologies. These findings offer valuable insights for policymakers, businesses, and investors, empowering them to navigate the complex terrain of global currency markets with heightened confidence and efficacy.