About Us   |   Contact Us   |  
Submission  

Forecasting United States Dollar to Tanzania Shillings Exchange Rate Using Comparable LSTM and BiLSTM Deep Learning Models

DOI : https://doi.org/10.36349/easjecs.2025.v08i02.001
PDF
HTML
XML

Tanzania heavily depends on United States Dollar (USD) foreign currency to import various goods and services into the country. Failure to correctly forecast exchange rates between USD and Tanzanian Shillings (TZS) may pose risks such as inability to import intended goods and services, possibility of losing money in stock exchange markets and other investment businesses in case of unexpected currency appreciation or depreciation as well as poor investment decisions in foreign exchange markets. To address this, this study has developed and comparatively evaluated performances of LSTM (Long Short-Term Memory) and BiLSTM (Bidirectional LSTM) deep learning models for forecasting daily USD to TZS exchange rates. The findings reveal that, BiLSTM model outperforms LSTM in forecasting daily USD to TZS exchange rates, achieving a MAPE (Mean Absolute Percentage Error) score of 0.363 on test set (unseen data) compared to a MAPE score of 1.471 achieved by LSTM model. This study recommends to the prospective Artificial Intelligence (AI) researchers and software developers to use BiLSTM instead of LSTM model to forecast (predict) USD to TZS exchange rates. Also, this study has developed USD to TZS exchange rates dataset which can be used by AI researchers, saving them time and costs involved with creating datasets from scratch. This study has also developed ready to use BiLSTM and LSTM models which can be used by Tanzanian business men and women involved in stock exchange markets, foreign exchange markets and other businesses, to predict daily USD to TZS exchange rates and make appropriate business and investment decisions.

TOP EDITORS

OPEN ACCESS JOURNALS

Dr. Afroza Begum

Lecturer, Dept. of Pharmacology and Therapeutics, Shaheed Monsur Ali Medical College & Hospital, Uttara, Dhaka-1230, Bangladesh

BEST AUTHOR

Of The Month

TRACK YOUR ARTICLE

Enter the Manuscript Reference Number (MRN)
Get Details

Contact us


EAS Publisher (East African Scholars Publisher)
Nairobi, Kenya


Phone : +91-9365665504
Whatsapp : +91-8724002629
Email : easpublisher@gmail.com

About Us


EAS Publisher (East African Scholars Publisher) is an international scholar’s publisher for open access scientific journals in both print and online publishing from Kenya. Its aim is to provide scholars ... Read More Here

*This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2020, All Rights Reserved | SASPR Edu International Pvt. Ltd.

Developed by JM