This paper evaluates the performance of conditional variance models using high-frequency data of the National Stock Index (S&P CNX NIFTY) and attempts to determine the optimal sampling frequency for the best daily volatility forecast. A linear combination of the realized volatilities calculated...

COVID-19 pandemic has heavily affected worldwide. One of the major industrial sectors impacted by COVID-19 virus is the travel and hospitality, and it has resulted in extreme level of unemployment in travel and tourism industries especially hotels, restaurant chains, street food caterers and...

Purpose: The study aims to understand the role of different streams of oil shocks (demand, supply and risk shocks) on the oil-importing and exporting countries' stock returns. The study also examines the impact of crude oil shocks across the economic regimes and market states. Besides, the role...

This paper constructs a robust Value-at-Risk (VaR) measure for the Indian stock markets by combining two well-known facts about equity return time series -- dynamic volatility resulting in the well-recognized phenomenon of volatility clustering, and non-normality giving rise to fat tails of the...

This paper presents a new value at risk (VaR) estimation model for equity returns time series and tests it extensively on Stock Indices of 14 countries. Two most important stylized facts of such series are volatility clustering, and non-normality as a result of fat tails of the return...

In this work we propose Monte Carlo simulation models for dynamically computing MaxVaR for a financial return series. This dynamic MaxVaR takes into account the time-varying volatility as well as non-normality of returns or innovations. We apply this methodology to five stock market indices. To...