Predicting volatility is a must in the finance domain. Estimations of volatility, along with the central tendency … assignment of diversifying assets in order to form efficient portfolios with a higher risk to reward ratio. The objective of this … research is to analyze the influence of COVID-19 on the return and volatility of the stock market indices of the top 10 …

The aim of this paper is to study the integration of volatility in the three markets, viz. spot, futures and options … moments (GMM) is used to capture the simultaneous equation modelling of volatility in the three markets. The integration of … the volatility in the three markets is also tested for structural breaks. The main finding of the paper is that the …

than the GARCH model in estimating the volatility of the Australian stock returns. However, another interesting finding is …This paper studies the effect of COVID-19 on the volatility of Australian stock returns and the effect of negative and … positive news (shocks) by investigating the asymmetric nature of the shocks and leverage impact on volatility. We employ a …

bitcoin's return volatility and Value at Risk. The objective of this study is to compare their out-of-sample performance in … forecasting accuracy and risk management efficiency. The results demonstrate that the RNN outperforms GARCH and EWMA in average …One of the notable features of bitcoin is its extreme volatility. The modeling and forecasting of bitcoin volatility …

events on the returns and volatility of commercial banks. It observes that insured and run-prone uninsured depositors choose … the case of Pakistan's commercial banking sector. The estimated volatility series for commercial banks is measured through … the GARCH model, which explains the current financial and political distress for the case of shocks from COVID-19. We …

the market volatility and asymmetric behavior of Bitcoin, EUR, S&P 500 index, Gold, Crude Oil, and Sugar during the COVID …-19 pandemic. We applied the GARCH (1, 1), GJR-GARCH (1, 1), and EGARCH (1, 1) econometric models on the daily time series … returns data ranging from 27 November 2018 to 15 June 2021. The empirical findings show a high level of volatility persistence …

assumptions alone in measuring risk. Cushioning against risk has always created a plethora of complexities and challenges; hence …, this paper attempts to analyse statistical properties of various risk measures in a not normal distribution and provide a … financial blueprint on how to manage risk. It is assumed that using old assumptions of normality alone in a distribution is not …

computational sciences. This special issue of the Journal of Risk and Financial Management on "Financial Time Series: Methods …

The aim of this paper is to investigate the relevance of structural breaks for forecasting the volatility of daily … evident. In forecasting volatility, the combination that averages forecasts obtained using different rolling estimation …

In this study, we examine the effect of introducing SSE 50ETF index options trading on stock market volatility using a … indicators, we estimate the counterfactual volatility of the SSE 50 index and find that the introduction of index options reduces … stock market volatility significantly in the long term. The primary findings are robust to alternative econometric models …