Modeling of financial early warnings in integrating the monitoring processes of financial resources and solvency of insurance companies
نویسندگان
1 Department of Accounting and Finance, South Tehran Branch, Islamic Azad University, Tehran, Iran
2 Department of Accounting and Finance, South Tehran Branch, Islamic Azad University, Tehran, Iran
3 Department of Economics, Central Tehran Branch, Islamic Azad University, Tehran, Iran
4 Department of Accounting and Finance, South Tehran Branch, Islamic Azad University, Tehran, Iran
doi
10.22075/ijnaa.2024.33546.5003چکیده
Several studies have evaluated financial solvency using the stress test and its consequences in insurance companies. This study modelled financial solvency in insurance companies using Bayesian averaging and Wilson's model. This applied and correlational study was conducted on 27 insurance companies admitted to the Tehran Stock Exchange from 2002 to 2006 and 2015 to 2020 to estimate the model. Among the BMA, TVP-DMA, TVP-DMS, BVAR, and OLS models, the BMA model was evaluated as having the highest efficiency in identifying the essential variables affecting financial prosperity. Thus, 40 variables (in 2 categories of early warning indicators and monitoring indicators) affecting financial solvency were included in the Bayesian averaging model, and 13 variables were identified as non-fragile variables based on previous probabilities. These variables included economic growth, inflation uncertainty, exchange rate, sanctions liquidity ratio, capital return ratio, debt ratio, total debt-to-equity ratio, long-term debt-to-equity ratio, surplus contribution (through reinsurance) to surplus, return on investment, and adjusted liabilities to current assets. Out of 13 variables, three variables were in the category of monitoring indicators, and 10 indicators were in the field of early warning variables. Based on the results, the contribution of early warning variables in predicting the crisis of financial prosperity is more important.