The implied volatility index: Is ‘investor fear gauge’ or ‘forward-looking’?

Shaikh, Imlak; Padhi, Puja

doi:10.1016/j.bir.2014.10.001

Cited by 40 publications

(17 citation statements)

References 47 publications

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“…The energy market volatility index used in this study was constructed by the CBOE (the Chicago Board Options Exchange) while the EMV-ID was developed by Baker et al (2020). The former has been empirically tested over time and studies have established a negative correlation between the volatility index and market returns (see Bouri et al, 2018;Shaikh & Padhi, 2015). The EMV-ID, however, is still relatively recent and therefore has not received much empirical applications compared to other volatility indexes.…”

Section: Data and Methodology Data And Methodologymentioning

confidence: 99%

Uncertainty Due to Infectious Diseases and Energy Market Volatility

Salisu

Adediran

2020

Energy RESEARCH LETTERS

137

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Motivated by the COVID-19 pandemic, we examine the role of uncertainty due to infectious diseases in predicting energy market volatility using the new dataset on Equity Market Volatility-Infectious Diseases (EMV-ID). We find that the new measure of market uncertainty is a good predictor of energy market volatility in both in-sample and out-of-sample tests. These results have implications for portfolio diversification strategies, which we set aside for future research.

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Section: Data and Methodology Data And Methodologymentioning

confidence: 99%

Uncertainty Due to Infectious Diseases and Energy Market Volatility

Salisu

Adediran

2020

Energy RESEARCH LETTERS

137

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“…It was designed to measure the market’s aggregate expectation of future 30-day volatility ( Chow, Jiang, & Li, 2014 ). VIX is estimated out of the trading prices of the options written on equity index ( Shaikh & Padhi, 2015 ) and does not require a specific model, only current option prices ( Britten-Jones & Neuberger, 2000 ; Jiang & Tian, 2005 ). Accordingly, VIX is a simple and broadly used index (often dubbed the “fear index”) that provides theoretical and empirical support for decisions taken by CBOE.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

All that glitters is not gold. The rise of gaming in the COVID-19 pandemic

López‐Cabarcos

Soriano

Chousa

2020

Journal of Innovation & Knowledge

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The COVID-19 pandemic has led to an unprecedented situation, with incalculable health, social, and economic consequences. At the start of the outbreak, the financial markets collapsed, although not all sectors suffered equally. The gaming and eSports industry is one of those that has suffered the least from the fall in the markets. Millions of people locked up at home, bored, stressed, and anguished, gave gaming and eSports companies growing prominence throughout the first half of 2020. This prominence has elicited interest in analyzing which variables can influence the returns in an industry in better financial health than many others. Using a logit–probit model, this research aims to analyze the relationship between financial (VIX, S&P GSCI Gold Index) and social (worldwide daily variation in total deaths from COVID-19 and worldwide Google attention on coronavirus) variables and the returns offered by the video game and eSports exchange traded fund (ESPO). The results show that the influence of social variables is weaker than the influence of financial variables. There is a significant inverse relationship between market volatility and ESPO returns and a highly significant relationship between ESPO returns and gold returns. While the relationship of ESPO returns with worldwide Google attention on coronavirus is significant, the relationship with worldwide daily variation in total deaths from COVID-19 is not. The conclusions of the study are discussed at the end of the paper.

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“…Zheng (2014) determined there is a negative nexus between stock market sentiment and returns in the commodity market. Shaikh and Padhi (2015) found that VIX is a gauge for evaluating investors' fear of market decline and anticipation of increases in stock market volatility. Smales (2017) showed sentimentality has a greater impact on returns during crisis periods.…”

Section: Literaturementioning

confidence: 99%

The chaotic behavior among the oil prices, expectation of investors and stock returns: TAR-TR-GARCH copula and TAR-TR-TGARCH copula

Bildirici

2018

Pet. Sci.

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This paper has two aims. The first one is to investigate the existence of chaotic structures in the oil prices, expectations of investors and stock returns by combining the Lyapunov exponent and Kolmogorov entropy, and the second one is to analyze the dependence behavior of oil prices, expectations of investors and stock returns from January 02, 1990, to June 06, 2017. Lyapunov exponents and Kolmogorov entropy determined that the oil price and the stock return series exhibited chaotic behavior. TAR-TR-GARCH and TAR-TR-TGARCH copula methods were applied to study the co-movement among the selected variables. The results showed significant evidence of nonlinear tail dependence between the volatility of the oil prices, the expectations of investors and the stock returns. Further, upper and lower tail dependence and comovement between the analyzed series could not be rejected. Moreover, the TAR-TR-GARCH and TAR-TR-TGARCH copula methods revealed that the volatility of oil price had crucial effects on the stock returns and on the expectations of investors in the long run.

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The implied volatility index: Is ‘investor fear gauge’ or ‘forward-looking’?

Cited by 40 publications

References 47 publications

Uncertainty Due to Infectious Diseases and Energy Market Volatility

Uncertainty Due to Infectious Diseases and Energy Market Volatility

All that glitters is not gold. The rise of gaming in the COVID-19 pandemic

The chaotic behavior among the oil prices, expectation of investors and stock returns: TAR-TR-GARCH copula and TAR-TR-TGARCH copula

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