Introducing a New Method for Calculating the Market Risk Factor of Solvency Model of Iranian Insurance Industry: The ARDL-GARCH Approach

The main purpose of this paper was to present a more efficient method for measuring the insurance market risk of insurance companies in the model of solvency protocol No. 69 of the Supreme Council of Insurance. The market risk factors of the solvency model address two main issues: firstly, the various methods of calculating these factors and their efficiency have not been properly evaluated and secondly, these factors are for normal conditions and in calculating them, the economic shocks effects are not considered to extract volatility under stress conditions.

We propose a new method that combines two models of Autoregressive Distributed Lags (ARDL) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH). Using the statistical data of Tehran Stock Exchange Index (TEPIX), Economic Growth, Inflation Rate and Exchange Rate in the period of 1999 to 2017 and using the Value at Risk measure (VaR), we modeled the investment market risk in stocks. Three simple variance-covariance methods, AR-GARCH and ARDL-EGARCH models were used. Finally, using the Kupiec back testing, the ARDL-EGARCH model was selected as the best model

Using the method presented in this paper, the risk factor estimation of the market risk of solvency model is more efficient than the other methods

Using the introduced model, the risk factor of investing in the stock market of financial corporations is 39% under normal economic conditions and 86.4% in crisis and stress conditions.