Generalized non-performing loans ratio (GNPLs) is empirically considered as a key prudential soundness indicator which is computed by the ratio of non-performing loans (overdue loans, arrears, doubtful loans, and rescheduled loans) to the total outstanding loan that also affects banks’,lending capacity. The GNPLs is evidently influenced by the macro systematic shocks (GDP growth, foreign exchange rate, inflation, and lending interest rate) which are statistically examined for a sample bank. In this regard, the impact of four systematic shocks on the GNPLs is estimated by a Vector Autoregressive (VAR) model during 2003-2020. In this context, the Impulse Response Function (IRF) of GNPLs is also examined against four contingent shocks while instantaneously variance decomposition of the GNPLs is estimated for the short and long term. The impact of the first and second moments of the shocks on GNPLs is estimated by the Multivariate Stochastic Volatility Model as well. The IRF output indicates that the GNPLs grows due to the shocks of exchange rate depreciation, GDP reduction, and inflation growth in the short time, while lending rate insignificantly affects the GNPLs owing to low historical volatilities as well as big arbitrages among bank lending rates for different economic sectors. The GNPLs Variance Decomposition highlights that GDP growth and inflation affect the GNPLs deviations in the short run, while the foreign exchange rate constantly motivates the GNPLs in the long run. In other words, the foreign exchange rate has strongly affected the GNPLs deviations in the long run, owing to its role as a nominal anchor and financial stability indicator in the macroeconomic environment. The GNPLs high Volatility which is estimated by conditional variance is also recognized in five different periods (2003, 2007, 2010, 2016, and 2019), mainly because of the foreign exchange rate unification in 2003, monetary expansion for self-employed loans in 2007, international sanctions in 2010, and 2009, as well as assets market recession in 2016 respectively. In this regard, the GNPLs deviations have also strongly correlated with output growth and foreign exchange rate Volatility.