Volatility Dynamics and Forecasting of the Nepal Stock Exchange Index: A Comparative Analysis of GARCH and EGARCH Models

Volatility is a fundamental characteristic of financial markets and plays a crucial role in investment decision-making, portfolio management, and financial risk assessment. Understanding the behaviour of stock market volatility is particularly important for frontier markets such as the Nepal Stock Exchange (NEPSE), where market fluctuations may differ from those observed in developed economies. This study investigates the volatility dynamics and forecasting performance of the NEPSE Index using daily closing prices from March 2021 to March 2026. Daily logarithmic returns were analysed following tests for stationarity and conditional heteroskedasticity. The volatility process was modelled using the symmetric GARCH(1,1) and asymmetric EGARCH(1,1) models, while model adequacy and forecasting performance were evaluated through diagnostic tests, information criteria, rolling-window out-of-sample forecasting, the News Impact Curve, volatility half-life estimation, and structural break analysis. The empirical findings confirm that NEPSE returns exhibit the stylized characteristics of financial time series, including volatility clustering, leptokurtosis, and persistent conditional volatility. The EGARCH model provides a marginally better in-sample fit and identifies significant asymmetric volatility, with negative market shocks producing stronger increases in future volatility than positive shocks of similar magnitude. However, the GARCH(1,1) model demonstrates slightly superior out-of-sample forecasting performance, indicating that the simpler specification remains more reliable for short-term volatility prediction. The analysis also identifies a structural break in July 2022, suggesting that volatility dynamics changed during the study period and that persistence estimates should be interpreted with caution. By integrating model comparison, forecasting evaluation, News Impact Curve analysis, volatility persistence, and structural break testing within a single analytical framework, this study provides a comprehensive assessment of NEPSE volatility and offers practical insights for investors, portfolio managers, policymakers, and future researchers interested in frontier equity markets.