Predicting Exchange Rate under UIRP Framework with Support Vector Regression

Abstract

This study aimed to forecast the exchange rate between the Vietnamese dong and the US dollar for the following month in the context of the COVID-19 pandemic. It used the Support Vector Regression (SVR) algorithm under the Uncovered Interest Rate Parity (UIRP) theoretical framework; the results are compared with the Ordinary Least Square (OLS) regression model and the Random Walk (RW) model under the rolling window method. The data included the VND/USD exchange rate, the bank interest rate for the 1-month term, and the 1-month T-bill from January 01, 2020, to September 11, 2021. The research discovered a linear link between the two nations' exchange rates and interest rate differentials. Interest rate differentials are input variables to forecast interest rate differentials. Furthermore, the connection between the exchange rate and interest rate differentials during this era does not support the UIRP hypothesis; hence, the error for OLS predictions remains large. The study provided a model to forecast future exchange rates by combining the UIRP theoretical framework and the SVR algorithm. The UIRP theoretical framework can anticipate exchange rate differentials using the input variable and the interest rates between two nations. Meanwhile, the SVR algorithm is a robust machine learning technique that enhances prediction accuracy. Doi: 10.28991/ESJ-2022-06-03-014 Full Text: PDF

On the enrichment of time series with textual data for forecasting agricultural commodity prices

“…The cross-validation for time-series was used to evaluate the proposed model in the experimental evaluation. This strategy is mostly used in time-series forecasting contexts [35] . The first training step was performed with 30% of the data ( ), and at each cross-validation iteration, a day is added to the training to predict the next step ahead.…”

Uncovered interest rate parity phenomenon and determinants of domestic interest rates: an analysis of Pakistan and China economies

“…As the expectations regarding the appreciation increase, investors tend to hoard assets in dollars. Shortly, international capital will flow in country, increasing country's supply of capital and causing interest rates to fall [16].…”

Forecasting stock price movement direction by machine learning algorithm

“…However, specific tests have demonstrated that the market is occasionally inefficient, in which predicting SPMD is possible [2], [3]. On the other hand, creating the required and adequate circumstances for an efficient market is challenging, particularly in a developing market like Vietnam [4]- [6]. Thus, predicting SPMD is quite doable for the Vietnam market.…”