The currency exchange rate is a crucial link between all countries related to economic and trade activities. The non-linear and non-stationary nature of financial time series data poses significant challenges for standalone statistical and neural network methods. While modeling in finance often focuses on volatility, there is a notable lack of research on modeling actual prices, particularly in the Kenyan exchange rates. The research used daily USD/KES and EUR/KES exchange rate data from the CBK ranging from November 10, 2008 to March 1, 2024 totaling 5409 entries.The research employs the GARCH model to extract statistical properties, which are then combined with historical daily exchange rate prices and fed into LSTM, and Transformer models leading to GARCH-LSTM, GARCH-Transformer hybrid models. Results indicate that hybrid model GARCH-Transformer, outperform the standalone models.This integration of GARCH with Transformer model offers a more robust framework for modeling actual prices.
| Published in | American Journal of Mathematical and Computer Modelling (Volume 11, Issue 1) |
| DOI | 10.11648/j.ajmcm.20261101.15 |
| Page(s) | 55-66 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2026. Published by Science Publishing Group |
GARCH, LSTM, USD, CBK, KES
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APA Style
Chamakany, J. L., Makumi, N., Mutua, K. (2026). Modelling the Actual Prices of Kenyan Exchange Rates Using GARCH-Transformer Hybrid Model. American Journal of Mathematical and Computer Modelling, 11(1), 55-66. https://doi.org/10.11648/j.ajmcm.20261101.15
ACS Style
Chamakany, J. L.; Makumi, N.; Mutua, K. Modelling the Actual Prices of Kenyan Exchange Rates Using GARCH-Transformer Hybrid Model. Am. J. Math. Comput. Model. 2026, 11(1), 55-66. doi: 10.11648/j.ajmcm.20261101.15
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Download@article{10.11648/j.ajmcm.20261101.15,
author = {Josphat Lesinya Chamakany and Nicholas Makumi and Kilai Mutua},
title = {Modelling the Actual Prices of Kenyan Exchange Rates Using GARCH-Transformer Hybrid Model
},
journal = {American Journal of Mathematical and Computer Modelling},
volume = {11},
number = {1},
pages = {55-66},
doi = {10.11648/j.ajmcm.20261101.15},
url = {https://doi.org/10.11648/j.ajmcm.20261101.15},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajmcm.20261101.15},
abstract = {The currency exchange rate is a crucial link between all countries related to economic and trade activities. The non-linear and non-stationary nature of financial time series data poses significant challenges for standalone statistical and neural network methods. While modeling in finance often focuses on volatility, there is a notable lack of research on modeling actual prices, particularly in the Kenyan exchange rates. The research used daily USD/KES and EUR/KES exchange rate data from the CBK ranging from November 10, 2008 to March 1, 2024 totaling 5409 entries.The research employs the GARCH model to extract statistical properties, which are then combined with historical daily exchange rate prices and fed into LSTM, and Transformer models leading to GARCH-LSTM, GARCH-Transformer hybrid models. Results indicate that hybrid model GARCH-Transformer, outperform the standalone models.This integration of GARCH with Transformer model offers a more robust framework for modeling actual prices.
},
year = {2026}
}
TY - JOUR T1 - Modelling the Actual Prices of Kenyan Exchange Rates Using GARCH-Transformer Hybrid Model AU - Josphat Lesinya Chamakany AU - Nicholas Makumi AU - Kilai Mutua Y1 - 2026/02/26 PY - 2026 N1 - https://doi.org/10.11648/j.ajmcm.20261101.15 DO - 10.11648/j.ajmcm.20261101.15 T2 - American Journal of Mathematical and Computer Modelling JF - American Journal of Mathematical and Computer Modelling JO - American Journal of Mathematical and Computer Modelling SP - 55 EP - 66 PB - Science Publishing Group SN - 2578-8280 UR - https://doi.org/10.11648/j.ajmcm.20261101.15 AB - The currency exchange rate is a crucial link between all countries related to economic and trade activities. The non-linear and non-stationary nature of financial time series data poses significant challenges for standalone statistical and neural network methods. While modeling in finance often focuses on volatility, there is a notable lack of research on modeling actual prices, particularly in the Kenyan exchange rates. The research used daily USD/KES and EUR/KES exchange rate data from the CBK ranging from November 10, 2008 to March 1, 2024 totaling 5409 entries.The research employs the GARCH model to extract statistical properties, which are then combined with historical daily exchange rate prices and fed into LSTM, and Transformer models leading to GARCH-LSTM, GARCH-Transformer hybrid models. Results indicate that hybrid model GARCH-Transformer, outperform the standalone models.This integration of GARCH with Transformer model offers a more robust framework for modeling actual prices. VL - 11 IS - 1 ER -
Department of Statistics and Actuarial Sciences, Jomo Kenyatta University of Agriculture and Technology (JKUAT), Nairobi, Kenya
Department of Statistics and Actuarial Sciences, Jomo Kenyatta University of Agriculture and Technology (JKUAT), Nairobi, Kenya
Department of Statistics and Actuarial Sciences, Jomo Kenyatta University of Agriculture and Technology (JKUAT), Nairobi, Kenya
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