Time Series Models as a Tool for Forecasting the Performance of Libyan Commercial Banks Based on CAMELS Indicators

Abstract

The study aimed to enhance the role of statistics in evaluating and developing banking performance evaluation models, such as the Camels model, and to explore the possibility of using time series as an input for predicting banking performance indicators according to the Camels model. This was achieved by highlighting the Camels model, analyzing its indicators, and examining the role of time series in predicting its indicators, with an application to the Libyan banking sector. The study used the descriptive inferential approach to collect and analyze data and financial statements related to the evaluation model's indicators, based on the Economic Bulletin of the fourth quarter of 2016 issued by the Central Bank of Libya (Rahil, 2019: 13).

The research uncovered a marked possibility of benefiting from time series in predicting Camels indicators. By comparing the actual results of the indicators for the year( 2016), it was observed that they converge with the predictions made using a time series from the period 2008-(2015), where( 2016) was considered the prediction year. Furthermore, a significant convergence was observed between the actual Camels indicators for( 2016) and the predictive indicators for (2016). Therefore, it can be said that time series play an important role in predicting Camels indicators without waiting for the outcome of the year being predicted

This may serve as a valuable  contribution to the development and enhancement of the camels model .