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The prevalent incoherent risk measures are not always adequate for effectively controlling portfolio risk under the circumstances of high volatility. This paper calculates both non-coherent and coherent risk measures for an exponential distribution. The risk measures are then employed under the Glosten-Jagannathan-Runkle (GJR-GARCH) model for forecasting. The risk values derived from the EVaR are fitted into the forecast model to anticipate the risk values for the next 25 trading days. To validate the theoretical considerations of this study, the daily returns of APPLE and TESLA stocks are examined. The simulation results confirm the supremacy of the proposed model.

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Use of GJR-GARCH Model for Forecasting of Financial Risk

  • 会议论文

  • 发表日期：

    2026年

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  • Pankaj Kumar,
  • Vivek Vijay

摘要

The prevalent incoherent risk measures are not always adequate for effectively controlling portfolio risk under the circumstances of high volatility. This paper calculates both non-coherent and coherent risk measures for an exponential distribution. The risk measures are then employed under the Glosten-Jagannathan-Runkle (GJR-GARCH) model for forecasting. The risk values derived from the EVaR are fitted into the forecast model to anticipate the risk values for the next 25 trading days. To validate the theoretical considerations of this study, the daily returns of APPLE and TESLA stocks are examined. The simulation results confirm the supremacy of the proposed model.