Foreign currency exchange rate prediction using non-linear Schrödinger equations with economic fundamental parameters. (November 2021)

• Record Type: Journal Article
• Authors: Kartono, Agus; Solekha, Siti; Sumaryada, Tony; Irmansyah,
• Is Part Of: Chaos, solitons and fractals. Volume 152(2021)
• Publication Date: 2021-11
• Subjects: Inflation -- Interest rate -- Nonlinear -- Return -- Asset; Chaotic behavior in systems -- Periodicals; Solitons -- Periodicals; Fractals -- Periodicals; Chaotic behavior in systems; Fractals; Solitons; Periodicals; 003.7
• DOI: 10.1016/j.chaos.2021.111320
• Languages: English
• ISSNs: 0960-0779

Abstract

Highlights: The changes in the information of economic variables in the foreign exchange market will cause exchange rate movements to become unstable and tend to fluctuate, the behavior of the exchange rate can be described by the nonlinear Schrödinger equation (NLSE) with economic variables that affect the exchange rate. The fourth-order Runge-Kutta method for solving the numerical solution of NLSE composed of an ordinary differential equation is very easy to apply and has high accuracy. The NLSE model can predict the (IDR/USD) exchange rate with high accuracy in weekly, monthly, and yearly periods so it is hoped that this model can be applied to predict the other foreign exchange rate. Abstract: The exchange rate is the price of the currency from one country against the currency of another country so that the exchange rate can be valued or expressed in the currency of another country. The exchange rate movement is a serious concern by the government as the monetary authority to supervise and control it. The exchange rate system is determined by the market mechanism because the demand and supply of the foreign currency are on the financial market, making its movements more difficult to predict. In this study, the prediction of the exchange rate of the United States Dollar (USD) to the Indonesian Rupiah (IDR) is modeled using the nonlinear Schrödinger equation (NLSE) calculated by the fourth-order Runge-Kutta. The parameters contained in the NLSE can be analogous to economic variables which assume that these variables affect the exchange rate. These economic variables include the inflation rates, the interest rate, the rates of return, and the Gross Domestic Product (GDP). The NLSE model is applied to predict the (IDR/USD) exchange rate. The NLSE model is calculated using the numerical method of the fourth-order Runge-Kutta, then the prediction results of the (IDR/USD) exchange rate are compared with the actual data from the (IDR/USD) exchange rate resulting in an error percentage of under 2.5% per month. The prediction results based on the Mean Absolute Percentage Error (MAPE) value calculation is 0.48%. The MAPE value shows that the smaller the MAPE value, the prediction results of the exchange rate will be closer to the data from the actual exchange rate.