Predicting Foreign Exchange Using Digital Signal Processing
Publication Date: 05/09/2021
Author(s): Robinson Mbato, Kabari Ledisi G..
Volume/Issue: Volume 4 , Issue 2 (2021)
Abstract:
The forex market is one associated with so much volatility and can lead to grave financial losses if not properly understood. To understand the market is to study the price patterns from previous years or months and make predictions from the rate of falling and rising. There have been so much researches aimed at developing a predictive model for the FOREX market, however, no model has been able to handle the market volatility while predicting future rates accurately. In this work, we have developed a digital processing model for predicting foreign exchange using ARIMA and Artificial Neural Network algorithms. We used price datasets for five currencies namely: USD, Swiss Pounds, Yen, Euro and Franc, gotten from the Central Bank of Nigeria (CBN) website. The data ranged from a period of 20 years. The model was simulated using MATLAB software. The study performed excellently in terms of time (26 seconds) and minimal errors (0.7). This work could be beneficial to FOREX traders and to the entire research community.
Keywords:
Foreign Exchange, Digital Signal Processing, Forex Traders, Forex Market, CBN
