Empirical Testing of Models of Autoregressive Conditional Heteroscedasticity Used for Prediction of the Volatility of Bulgarian Investment Funds

Empirical Testing of Models of Autoregressive Conditional Heteroscedasticity Used for Prediction of the Volatility of Bulgarian Investment Funds The used risk attribution quantification models GARCH (1.1) EGARCH (1.1), GARCH-M (1.1) and TGARCH (1.1) are adapted to predict the volatility of investment funds. The object of the study includes quantitative analysis, estimation and forecasting of daily volatility through the models: GARCH, EGARCH, GARCH-M and TGARCH with specification (1.1). The research covers the net balance sheet value of forty-two investment funds for the period from 2016-2020 and 2020-2023. 1. results of risk forecasting models for the period 2016-2020 2. results of risk forecasting models for the period 2020-2023 3. results of the application of the Dickey Fuller stationarity test for the two periods