scholarly journals Modeling Volatility of Asset and Volume of Trade Returns in the Nigerian Stock Market in the Presence of Random Level Shifts

Author(s):  
David Adugh Kuhe ◽  
Moses Abanyam Chiawa ◽  
Sylvester Chigozie Nwaosu ◽  
Jonathan Atsua Ikughur

This study investigated the impact of volatility shock persistence on the conditional variance in the Nigerian stock returns using symmetric and asymmetric higher order GARCH family models in the presence of random level shifts and non-Gaussian errors. The study utilised Bai and Perron methodology to detect structural breakpoints in the conditional variance of daily stock and volume of trade returns in the Nigerian stock market from 2nd January, 1998 to 22nd March, 2017. The study employed symmetric GARCH (3,2) and GARCH (2,1)-M models to estimate volatility of asset returns, symmetric GARCH (2,2) and GARCH (2,1)-M to model volatility of volume of trade returns and asymmetric EGARCH (2,2), TGARCH (3,2) and PGARCH (2,3) models to measure the volatility of asset returns as well as asymmetric EGARCH (2,1), TGARCH (1,3) and PGARCH (3,2) models to estimate volatility of volume of trade returns. These models were optimally selected using information criteria and log likelihood as the best fitting symmetric and asymmetric GARCH models to estimate the conditional volatility of asset and volume of trade returns in the Nigerian stock market with and without structural breaks. Results revealed that when random level shifts were ignored in volatility models, the shocks persistence were very high with long memory and variance explosion. But when the random level shifts were incorporated into the GARCH models, there was a significant reduction in the volatility shocks persistence and long memory. Moreover, volatility half-lives also declined drastically while accounting for these sudden level shifts in variance. The study found asymmetry without leverage effects as well as a positive risk-return tradeoff for both asset and volume of trade returns in the Nigerian stock market. The Nigeria banking reform of 2004, the Global Financial and Economic Crises, as well as other local events in Nigeria, were found to have negative and significant impacts on the Nigerian stock market. The study provided some policy recommendations.

Author(s):  
Alessandra Ortolano ◽  
Eugenia Nissi

The paper is an investigation on the impact of financial markets on the volatility of green bonds credit risk component, measured by the option-adjusted spread/swap curve (OAS) of the Global Bloomberg Barclays MSCI Green Bond Index, for both the non and pandemic periods. For these purpose, after observing the dynamic joint correlations between all the variables through a DCC-GARCH, we adopt GARCH(1,1) and EGARCH(1,1) models, putting the OAS as dependent variable. Our main results show that the conditional variance parameters are significant and persistent in both times, testifying the overall impact of the other markets on the OAS. In more detail, we highlight that the gamma in the two EGARCH models is positive: so the “green” credit risk volatility is more sensitive to positive shocks than negative ones. With reference to the conditional mean, we note that if during the non pandemic time only the stock market is significant, during the pandemic also conventional bonds and gold are impacting. To the best of our knowledge this is the first study that analyzes the specific credit risk component of green bond yields: we deem our findings useful to observe the change of green bonds creditworthiness in a complex market context.


2020 ◽  
Vol 21 (6) ◽  
pp. 1561-1592
Author(s):  
Cristi Spulbar ◽  
Jatin Trivedi ◽  
Ramona Birau

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.


Author(s):  
Nils Muhlack ◽  
Christian Soost ◽  
Christian Johannes Henrich

AbstractThis paper examines the impact of weather phenomena on the German stock market, evaluating cloud cover, humidity, air pressure, precipitation, temperature, and wind speed as weather variables. We use stock market data (returns, trading volume, and volatility) from the DAX, MDAX, SDAX, and TecDAX for the period from 2003 to 2017 and show, with modern time-series (GARCH) models that air pressure is the only weather variable that exerts a potentially consistent effect on the stock market. Air pressure reduces the trading volume on the SDAX and TecDAX, and changes in air pressure lead to increases in returns on the DAX, MDAX and SDAX. The effects of the other weather variables show no clear pattern and are critically discussed. In addition, this article contains an overview of the historical research results on the effects of weather on stock markets.


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