Improving Financial Volatility Modeling Using neutrosophic Logic and Applying the GJR-GARCH Model

Abdullah, Hiba H; Noori, Nooruldeen Ayad; Mohammad, Azher A.; Khaleel, Mundher A.; Khalaf, Nihad S.

doi:10.24271/psr.2025.508072.1961

Improving Financial Volatility Modeling Using neutrosophic Logic and Applying the GJR-GARCH Model

Document Type : Original Article

Authors

Hiba H Abdullah ¹

nooruldeen Ayad Noori ²

Azher A. Mohammad ³

Mundher A. Khaleel

Nihad S. Khalaf

¹ Department of Mathematics, College of Education for Women, Tikrit University, Tikrit 34001, Iraq.

² Mathematic, Anbar Education Directorate, Ramadi 31001, Iraq.

³ Mathematics Department, College of Computer Science and mathematics, Tikrit University, Tikrit 34001, Iraq.

10.24271/psr.2025.508072.1961

Abstract

This study adopts an innovative approach based on incorporating neutrosophic logic (NG) into the Glosten, Jagannathan, and Runkle generalized autoregressive conditional heteroskedasticity (GJR-GARCH) model to improve the estimation of conditional volatility in financial markets. It focuses on the analysis of time-varying financial volatility, considering account the effects of asymmetric shocks on variance. It suffers from difficulty in dealing with ambiguity and uncertainty in financial data. The incorporation of NG, which is based on three main elements: truth, error, and indeterminacy, allows for improving the accuracy of estimating unexpected and uncertain sharp volatility in markets. This new model provides a comprehensive framework that can better deal with the complexity and ambiguity of financial data. The results show that this methodology contributes to improves the model’s ability to predict conditional volatility and provide evidence-based financial decisions, especially in complex financial environments. The suggested model in significant steps in enhancing the capacity to handle unforeseen financial shocks and gaining a greater knowledge of the complex behavior of financial data. As a result, it is a helpful tool to help decision-makers and investors make better, more accurate financial judgments.

Keywords

Financial Volatility

Neutrosophic Logic

Conditional Variance Models

Asymmetric Shocks

and Financial Forecasting