Modeling the Profitability of Private Banks in Syria Using Asymmetric Conditional Volatility Models

(Case Study of Bank Audi for the Period 2010-2023)

Abstract

The aim of this research was to model the fluctuations in the profitability rates of Bank Audi using Asymmetric Conditional Volatility Models. Statistical analysis and ARIMA time series forecasting models were employed to analyze the trends in profitability rates, with quarterly data collected from 2010 to 2023 from the financial statements of Bank Audi available on the Damascus Securities Exchange website.

Volatility was analyzed using advanced models such as APARCH, TGARCH, and EGARCH to provide accurate estimates of profitability rate fluctuations (return on assets and return on equity).

One of the key findings of the research was that the level of risk and instability in the ROA increases following significant events, with random fluctuations persisting sharply over time. Meanwhile, large shocks lead to inverse changes in the ROE, and the effects of these shocks continue over time, noting that changes in the ROE are significantly affected by negative shocks.

The research also concluded that both positive and negative shocks impact the current fluctuations in ROA in the same manner, while positive shocks differ from negative shocks in their effect on the fluctuations of the ROE.