Abstract:
This research investigated the issue of forecasting the yields of treasury bills in the Kenyan financial market which is both volatile and complicated, and which traditional models of forecasting may fail because of non-linear behaviour. The study developed, trained and tested a hybrid machine learning model to improve the predictive power and stability of the model by integrating ARIMA to analyze linear trends, Support Vector Machines (SVM) to capture non-linear interdependencies, and Facebook Prophet (FB Prophet) to capture seasonality and handle missing values.The study employed a longitudinal research design utilizing secondary quantitative data. The target population comprised all Treasury bill tenors issued by the Central Bank of Kenya. A census sampling technique was adopted to select 364-day Treasury bill yields, resulting in a sample of weekly observation points spanning from July 2022 to June 2024. Models were trained and tested on performance measures, namely Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and Mean Absolute Scaled Error (MASE) and cross-validation was used to increase reliability. The findings indicated that Gaussian Copula ensemble model is a more effective model in predicting 364-day Kenyan Treasury bills yields. The hybrid model generated the least Mean Absolute Error (MAE) of 0.1187 compared to best-performing individual model, SVM which had an MAE of 0.1806. Comparatively, the hybrid model reduced the prediction error by approximately 34% against the best-performing individual model (SVM), demonstrating superior capacity in handling the non-linear volatility of the Kenyan financial market. The study concluded that this combination of linear, non-linear, and seasonal-trend models using the specific advantages of each model can offer more reliable and robust forecasts as compared to traditional ones. The model can assist in making intelligent decisions and risk management as well as formulating effective economic policies.
