MODELING STOCK MARKET DAILY RETURNS VOLATILITY USING SYMMETRIC AND ASYMMETRIC GARCH MODELS WITH THREE DIFFERENT DISTRIBUTIONS

2020 ◽  
Vol 63 (2) ◽  
pp. 119-140
Author(s):  
Rama Krishna Yelamanchili
Keyword(s):  
Stock Market ◽  
Garch Models ◽  
Asymmetric Garch ◽  
Daily Returns

scholarly journals Estimating stock market volatility using asymmetric GARCH models

2008 ◽  
Vol 18 (15) ◽  
pp. 1201-1208 ◽  
Author(s):  
Dima Alberg ◽  
Haim Shalit ◽  
Rami Yosef
Keyword(s):  
Stock Market ◽  
Market Volatility ◽  
Garch Models ◽  
Stock Market Volatility ◽  
Asymmetric Garch

scholarly journals INVESTIGATING ABNORMAL VOLATILITY TRANSMISSION PATTERNS BETWEEN EMERGING AND DEVELOPED STOCK MARKETS: A CASE STUDY

2020 ◽  
Vol 21 (6) ◽  
pp. 1561-1592
Author(s):  
Cristi Spulbar ◽  
Jatin Trivedi ◽  
Ramona Birau
Keyword(s):  
Stock Market ◽  
Financial Markets ◽  
Stock Markets ◽  
Financial Integration ◽  
Global Financial Crisis ◽  
Spillover Effects ◽  
Garch Models ◽  
Asymmetric Garch ◽  
Developed Stock Markets ◽  
The Impact

The main aim of this paper is to investigate volatility spillover effects, the impact of past volatility on present market movements, the reaction to positive and negative news, among selected financial markets. The sample stock markets are geographically dispersed on different continents, respectively North America, Europe and Asia. We also investigate whether selected emerging stock markets capture the volatility patterns of developed stock markets located in the same region. The empirical analysis is focused on seven developed stock market indices, i.e. IBEX35 (Spain), DJIA (USA), FTSE100 (UK), TSX Composite (Canada), NIKKEI225 (Japan), DAX (Germany), CAC40 (France) and five emerging stock market indices, i.e. BET (Romania), WIG20 (Poland), BSE (India), SSE Composite (China) and BUX (Hungary) from January 2000 to June 2018. The econometric framework includes symmetric and asymmetric GARCH models i.e. EGARCH and GJR which are performed in order to capture asymmetric volatility clustering, interdependence, correlations, financial integration and leptokurtosis. Symmetric and asymmetric GARCH models revealed that all selected financial markets are highly volatile, including the presence of leverage effect. The stock markets in Hungary, USA, Germany, India and Canada exhibit high positive volatility after global financial crisis.

scholarly journals Impact of COVID-19 on Stock Market and Gold Returns in India

2021 ◽  
Vol 14 (27) ◽  
pp. 29-46
Author(s):  
Sarika MAHAJAN ◽  
◽  
Priya MAHAJAN ◽  
Keyword(s):  
Stock Market ◽  
Global Economy ◽  
Global Financial Crisis ◽  
Negative Impact ◽  
Arma Model ◽  
Garch Models ◽  
Stock Market Returns ◽  
Joint Dynamics ◽  
Asymmetric Garch ◽  
The Impact

The spread of COVID-19 has caused severe damage to human lives and the global economy. The stock markets around the world have plummeted to their lowest levels since the 2008 Global Financial Crisis. This paper attempts to examine the joint dynamics of gold and stock market returns during unprecedented times of health and financial shock due to COVID-19 between January 2020 and May 2020 using granger test, ARMA model, and symmetric and asymmetric GARCH models to improve the understanding of the microstructure of investment scenario in India. The period considered in the study helps to evaluate the impact of lockdown due to coronavirus on Gold and Nifty index return. Results based on GARCH and E-GARCH models indicate a significant negative impact of gold on nifty returns during the sample period. The results also indicate investors' perception of gold as a safe-haven asset during periods of elevated uncertainty. Thus, the study is expected to enhance the understanding of market asymmetry, the behavior of investors towards these avenues of investments, and information processing.

scholarly journals INVESTIGATING VOLATILITY BEHAVIOUR: EMPIRICAL EVIDENCE FROM ISLAMIC STOCK INDICES

2020 ◽  
Vol 6 (4) ◽  
Author(s):  
Burhanuddin Burhanuddin
Keyword(s):  
Stock Returns ◽  
Risk Premium ◽  
Garch Models ◽  
Single Model ◽  
Volatility Risk ◽  
Stock Indices ◽  
Asymmetric Garch ◽  
Mean Square Errors ◽  
Forecasting Errors ◽  
Daily Returns

The main purpose of this research is to apply five univariate GARCH models to thedaily stock returns of four major sharia stock indices. Two symmetric versions of theGARCH model (GARCH and MGARCH) and three asymmetric versions (EGARCH,TGARCH and PGARCH) are employed to estimate and forecast the volatility of fourmajor sharia indices. The results provide strong evidence that all models can depictthe volatility behaviours in all four sharia index returns. The two symmetric modelsindicate that the volatility of a sharia index’s returns depend on its previous own lags,and statistically prove that a rise in volatility (risk) leads to an increase in mean(return), i.e. the risk premium effect. Meanwhile, the three asymmetric modelssuggest that negative shocks to daily returns tend to have higher impact on thevolatility of sharia indices than positive shocks of the same magnitude. Moreover,based on the values of forecasting errors – root mean square errors (RMSE) andmean absolute errors (MAE) – the asymmetric GARCH models outperform thesymmetric models in forecasting the volatility of four major sharia indices. However,the very small difference values of RMSE and MAE among the univariate GARCH-type models denote that no single model is superior to the others.

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