The purpose of this research was to examine the dynamics volatility spillover between energy and environmental, social, sustainable indices. COVID19 prompted select April 2019 March 2022 as a sample period, respective data (Daily Prices) Nifty Energy ESG indices were obtained from National Stock Exchange India Limited. outcomes study confirmed that daily returns 100 not normally distributed rea...

The carbon market is a vital tool to achieve neutrality. This paper uses daily closing price data of Shenzhen trading market, energy, commodity and financial markets from 18 October 2018 19 August 2021, examining the transmission risk/information perspective volatility spillover tail risk based on quantile spillover. stock crash COVID-19 have increased system substantially. Next, increase in fr...

This paper provides a new viewpoint on the time and frequency dynamics of spillover effects among eight major world equity market indexes. We extend Diebold–Yilmaz approach Barunilk Krehik methodology to estimate measure skewness spillover. Our empirical results indicate that total is far smaller than volatility all markets. Although both vary with time, remains relatively smooth varies gradual...

The research on spillover effect in financial markets is frontier theory and technology. The global financial crisis of 2007-2009 affects the stock markets deeply. But, the economic consequences are different among some cross-markets. As an emerging high-speed growth securities market established in 1990, the Chinese securities market has developed significantly. Again in the current internatio...

Abstract This paper examines the effect of geopolitical risk (GPR) on return and volatility dynamics in Middle East North African (MENA) countries by using an ADCC-GARCH model a spillover approach. Unlike previous studies, we include GPR index to capture associated with wars, terrorist acts, political tensions. Moreover, test for both static dynamic analysis rolling window. In brief, findings h...

Over the past years, cryptocurrencies have drawn substantial attention from media while attracting many investors. Since then, cryptocurrency prices experienced high fluctuations. In this paper, we forecast high-frequency 1 min volatility of four widely traded cryptocurrencies, i.e., Bitcoin, Ethereum, Litecoin, and Ripple, by modeling to select best model. We propose various generalized autore...