Skip to content
Open access

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

Aug 2026 · Economics · 0 citations · 26 references

Abstract

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.

Read PDF

Similar papers

Open access Aug 2026

A Comparative Study of Stock Return and Volatility Across Major Indian Sectors Using ARIMA and GARCH Model

Forecasting stock returns and analyzing market volatility are important aspects of financial research, as they help investors and financial analysts make informed decisions while managing investment risk. This study examines the return and volatility behaviour of five major sectors of the Indian economy: Banking, FMCG,...

Dr Tanvi Pathak, Dr Anamika Sharma, Dr Devrshi Upadhayay et al. · 0 citations
Open access Sep 2026

Volatility Modelling of the BSE SENSEX Using the ARCH Model: An Empirical Study of Select Large-Cap Constituent Stocks (2021–2026)

Stock market volatility is of continuing interest to investors, portfolio managers, corporates and policymakers because it directly influences risk assessment, asset pricing and capital allocation decisions. This paper examines the return-generating and volatility process of the Bombay Stock Exchange Sensitive Index (B...

C. Parmar, Sandip Raithathatha, Kashish Jayesh Ramani et al. · 0 citations
Open access Aug 2026

Unraveling the Dynamics of Nigerian Stock Market: A Deep Dive into Volatility and Daily Stock Returns

This study investigates the volatility dynamics of daily stock market returns in Nigeria through advanced econometric models, specifically the Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) model. Daily closing price data from the Nigerian Exchange Group (NGX), covering the period from J...

Chinwendu Amblessed Wogu · 0 citations
Open access 2026

Macroeconomic risk, asymmetric volatility and long-memory dynamics in Indian equity markets: Implications for financial project and risk management

This study tries to assess whether aggregated domestic and global macro-financial conditions can assist to explicate daily equity-market returns and volatility in India and considers the implications for financial risk and project-related decision making. Daily BSE and NSE index returns are analysed for January 2000–Ma...

Arshi Firdous, Sarbapriya Ray · 0 citations
Open access Sep 2026

The Role of Innovation Distributions in Forecasting Brent Crude Oil Volatility Using Univariate GARCH Models

This study investigates the impact of different error distributions on the performance of univariate GARCH-family models in modeling and forecasting the volatility of Brent crude oil returns from January 2014 to May 2025. Descriptive analysis reveals pronounced fluctuations, volatility clustering, and asymmetric beh...

Godsgift Chilaka Njoku · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.