Effects of the first wave of COVID-19 pandemic on implied stock market volatility: International evidence using a google trend measure.

This paper investigates the relationship between investors' attention, as measured by Google search queries, and equity implied volatility during the COVID-19 outbreak. Recent studies show that search investors' behavior data is an extremely abundant repository of predictive data, and investor-limited attention increases when the uncertainty level is high. Our study using data from thirteen countries across the globe during the first wave of the COVID-19 pandemic (January-April 2020) examines whether the search "topic and terms" for the pandemic affect market participants' expectations about future realized volatility. With the panic and uncertainty about COVID-19, our empirical findings show that increased internet searches during the pandemic caused the information to flow into the financial markets at a faster rate and thus resulting in higher implied volatility directly and via the stock return-risk relation. More specifically for the latter, the leverage effect in the VIX becomes stronger as Google search queries intensify. Both the direct and indirect effects on implied volatility, highlight a risk-aversion channel that operates during the pandemic. We also find that these effects are stronger in Europe than in the rest of the world. Moreover, in a panel vector autoregression framework, we show that a positive shock on stock returns may soothe COVID-related Google searches in Europe. Our findings suggest that Google-based attention to COVID-19 leads to elevated risk aversion in stock markets.

Dynamic co-movement in major commodity markets during crisis periods: A wavelet local multiple correlation analysis

We study time-scale co-movement of returns and implied volatilities of oil, gold, wheat, and copper in a multivariate setting using the wavelet local multiple correlation (WLMC) approach. Daily data cover January 03, 2007 – August 08, 2022, including the global financial crisis, COVID-19 pandemic, and Russia-Ukraine war. The results show that the correlations across the commodities are heterogeneous, less stable in the short-term, and more pronounced in the long-term, and vary in sign and magnitude. Despite market instability, contagion is not clearly seen in either return or volatility, reflecting noise trading and the importance of the individual characteristics of commodities.

The time-varying impact of uncertainty on oil market fear: Does climate policy uncertainty matter?

Implied volatility index is a popular proxy for market fear. This paper uses the oil implied volatility index (OVX) to investigate the impact of different uncertainty measures on oil market fear. Our uncertainty measures consider multiple perspectives, specifically including climate policy uncertainty (CPU), geopolitical risk (GPR), economic policy uncertainty (EPU), and equity market volatility (EMV). Based on the time-varying parameter vector autoregression (TVP-VAR) model, our empirical results show that the impact of CPU, GPR, EPU, and EMV on OVX is time-varying and heterogeneous due to these uncertainty measures containing different information content. In particular, the CPU has become increasingly important for triggering oil market fear since the recent Paris Agreement. During the COVID-19 pandemic, CPU, EPU, and EMV, rather than GPR, play a prominent role in increasing oil market fear. © 2023 Elsevier Ltd

Knowledge Discovery to Support WTI Crude Oil Price Risk Management

The high volatility of commodity prices and various problems that the energy sector has to deal with in the era of COVID-19 have significantly increased the risk of oil price changes. These changes are of the main concern of companies for which oil is the main input in the production process, and therefore oil price determines the production costs. The main goal of this paper is to discover decision rules for a buyer of American WTI (West Texas Intermediate) crude oil call options. The presented research uses factors characterizing the option price, such as implied volatility and option sensitivity factors (delta, gamma, vega, and theta, known as "Greeks”). The performed analysis covers the years 2008–2022 and options with an exercise period up to three months. The decision rules are discovered using association analysis and are evaluated in terms of the three investment efficiency indicators: total payoff, average payoff, and return on investment. The results show the existence of certain ranges of the analyzed parameters for which the mentioned efficiency indicators reached particularly high values. The relationships discovered and recorded in the form of decision rules can be effectively used or adapted by practitioners to support their decisions in oil price risk management.

Quantile Dependence between Crude Oil Returns and Implied Volatility: Evidence from Parametric and Nonparametric Tests

We examine the daily dependence and directional predictability between the returns of crude oil and the Crude Oil Volatility Index (OVX). Unlike previous studies, we apply a battery of quantile-based techniques, namely the quantile unit root test, the causality-in-quantiles test, and the cross-quantilogram approach. Our main results show evidence of significant bi-directional predictability that is quantile-dependent and asymmetric. A significant positive Granger causality runs from oil (OVX) returns to OVX (oil) returns when both series are in similar lower (upper) quantiles, as well as in opposite quantiles. The Granger causality from OVX returns to oil returns is only significant during periods of high volatility, although it is not always positive. The findings imply that the forward-looking estimate of oil volatility, reflecting the sentiment of oil market participants, should be considered when studying price variations in the oil market, and that crude oil returns can be used to predict oil implied volatility during bearish market conditions. Therefore, the findings have implications regarding predictability under various conditions for oil market participants.

WTI Crude Oil Options Market Prior to and During the COVID-19 Pandemic

The COVID-19 pandemic has caused turbulence in many areas of the global economy. It also contributed to an increase in volatility on the energy commodities market. This spilled over into the derivatives market, particularly the crude oil futures market. The aim of the article is to compare the costs and effectiveness of using options on WTI oil from before and after the pandemic. The analyzes took into account the value of option premiums and final results obtained by buyers of call options from March 1, 2018 to April 14, 2022. The results showed that buyers of call options during the pandemic, despite paying much higher option premiums, experienced significantly higher payouts and rates of return. They were the highest for options with the longest expiry periods of 21-30 days. Research also showed that during the pandemic, options with strike prices set at a level higher than the price of oil on the contract date had particularly high rates of return, while the highest payout values were achieved by buyers of call options with low strike prices.

Volatility spillovers during normal and high volatility states and their driving factors: A cross-country and cross-asset analysis

Understanding the transmission of volatility across markets is essential for managing risk and financial stability, especially under crisis periods during which an extreme event occurring in one market is easily transmitted to another market. To gain such an understanding and enrich the related literature, we examine in this article the system of volatility spillovers across various equity markets and asset classes using a quantile-based approach, allowing us to capture spillovers under normal and high volatility states. The sample period is 16 March 2011–10 November 2020 and the employed dataset comprises 12 implied volatility indices representing a forward-looking measure of uncertainty of global equities, strategic commodities and the US Treasury bond market. The results show that the identity of transmitters and receivers of volatility shocks differ between normal and high volatility states. The US stock market is at the centre of volatility spillovers in the normal volatility state. European and Chinese stock markets and strategic commodities (e.g. crude oil and gold) become major volatility transmitters in the high volatility state, after acting as volatility receivers during normal periods. Furthermore, we study the drivers of implied volatility spillovers using regression models and find that US Default spread contributes to the total volatility spillover index in both volatility states, whereas TED spread plays a significant role in the normal volatility state. As for the role of short rate and risk aversion, it is significant in the high volatility state. These findings matter to the decision-making process of risk managers and policymakers. © 2022 John Wiley & Sons Ltd.

The effect of oil implied volatility and geopolitical risk on GCC stock sectors under various market conditions

The importance of crude oil volatility and geopolitical risk for stock pricing is well known in both developed and emerging economies, but is relatively understudied in major oil-exporting countries at the sectoral level of stock indices and under various market conditions. Using daily data on eight Gulf Cooperation Council (GCC) stock sector indices over the period February 2010–30 June 2022, we capture the effect of two global risk factors, namely oil implied volatility and geopolitical risk, on stock returns and volatility while accounting for bull/bear markets and low/high volatility regimes. The analysis indicates the following results. Firstly, the effect of oil implied volatility is stronger than that of geopolitical risk, notably for Consumer Discretionary and Staples. Secondly, the effect on both returns and volatility is generally positive during bull markets, but it is stronger for volatility;the response of the returns of Energy, Materials, Industrials, and Financials is negative in bear markets and positive during bull markets. Thirdly, the effect of oil implied volatility on stock sector volatility is slightly higher during the COVID-19 outbreak for some cases and is prominent during bull markets. Our findings matter for the predictability of GCC stock sector returns and volatility and for the design of hedging strategies under various market states. © 2023 Elsevier B.V.

Do stock market fear and economic policy uncertainty co-move with COVID-19 fear? Evidence from the US and UK

Purpose: The purpose of the paper is to investigate co-movement of major implied volatility indices and economic policy uncertainty (EPU) indices with both the health-based fear index and market-based fear index of COVID-19 for the USA and the UK to help investors and portfolio managers in their informed investment decisions during times of infectious disease spread. Design/methodology/approach: This study uses wavelet coherence approach because it allows to observe lead–lag nonlinear relationship between two time-series variables and captures the heterogeneous perceptions of investors across time and frequency. The daily data used in this study about the USA and the UK covers major implied volatility indices, EPU, health-based fear index and market-based fear index of COVID-19 for both the first and second waves of COVID-19 pandemic over the period from March 3, 2020 to February 12, 2021. Findings: The results document a strong positive co-movement between implied volatility indices and two proxies of the COVID-19 fear. However, in all the cases, the infectious disease equity market volatility index (IDEMVI), the COVID-19 proxy, is more representative of the stock market and exhibits a stronger positive co-movement with volatility indices than the COVID-19 fear index (C19FI). This study also finds that the UK's implied volatility index weakly co-moves with the C19FI compared to the USA. The results show that EPU indices of both the USA and the UK exhibit a weak or no correlation with the C19FI. However, this study finds a significant and positive co-movement of EPU indices with IDEMVI over the short horizon and most of the sampling period with the leading effect of IDEMVI. This study's robustness analysis using partial wavelet coherence provides further strengths to the findings. Research limitations/implications: The investment decisions and risk management of investors and portfolio managers in financial markets are affected by the new information on volatility and EPU. The findings provide insights to equity investors and portfolio managers to improve their risk management practices by incorporating how health-related risks such as COVID-19 pandemic can contribute to the market volatility and economic risks. The results are beneficial for long-term equity investors, as their investments are affected by contributing factors to the volatility in US and UK's stock markets. Originality/value: This study adds following promising values to the existing literature. First, the results complement the existing literature (Rubbaniy et al., 2021c) in documenting that type of COVID-19 proxy matters in explaining the volatility (EPU) relationships in financial markets, where market perceived fear of COVID-19 is appeared to be more pronounced than health-based fear of COVID-19. Second, the use of wavelet coherence approach allows us to observe lead–lag relationship between the selected variables, which captures the heterogeneous perceptions of investors across time and frequency and have important insights for the investors and portfolio managers. Finally, this study uses the improved data of COVID-19, stock market volatility and EPU compared to the existing studies (Sharif et al., 2020), which are too early to capture the effects of exponential spread of COVID-19 in the USA and the UK after March 2020. © 2022, Emerald Publishing Limited.

The COVID-19 risk in the cross-section of equity options.

We use the implied volatility slope measures derived from US stock options to examine the impact of COVID-19 risk on the options market. The severity of COVID-19 is measured by the number of new confirmed cases. We find that equity options that are most sensitive to COVID-19 generate a more positive IV slope than less COVID-19-sensitive equity options. Moreover, this measure is more positive and significant during the lockdown period. Our findings suggest that the hedging cost of downside tail risk is more expensive during the high-uncertainty period, the time when COVID-19 is more intensive.

Do stock market fear and economic policy uncertainty co-move with COVID-19 fear? Evidence from the US and UK

Purpose>The purpose of the paper is to investigate co-movement of major implied volatility indices and economic policy uncertainty (EPU) indices with both the health-based fear index and market-based fear index of COVID-19 for the USA and the UK to help investors and portfolio managers in their informed investment decisions during times of infectious disease spread.Design/methodology/approach>This study uses wavelet coherence approach because it allows to observe lead–lag nonlinear relationship between two time-series variables and captures the heterogeneous perceptions of investors across time and frequency. The daily data used in this study about the USA and the UK covers major implied volatility indices, EPU, health-based fear index and market-based fear index of COVID-19 for both the first and second waves of COVID-19 pandemic over the period from March 3, 2020 to February 12, 2021.Findings>The results document a strong positive co-movement between implied volatility indices and two proxies of the COVID-19 fear. However, in all the cases, the infectious disease equity market volatility index (IDEMVI), the COVID-19 proxy, is more representative of the stock market and exhibits a stronger positive co-movement with volatility indices than the COVID-19 fear index (C19FI). This study also finds that the UK's implied volatility index weakly co-moves with the C19FI compared to the USA. The results show that EPU indices of both the USA and the UK exhibit a weak or no correlation with the C19FI. However, this study finds a significant and positive co-movement of EPU indices with IDEMVI over the short horizon and most of the sampling period with the leading effect of IDEMVI. This study's robustness analysis using partial wavelet coherence provides further strengths to the findings.Research limitations/implications>The investment decisions and risk management of investors and portfolio managers in financial markets are affected by the new information on volatility and EPU. The findings provide insights to equity investors and portfolio managers to improve their risk management practices by incorporating how health-related risks such as COVID-19 pandemic can contribute to the market volatility and economic risks. The results are beneficial for long-term equity investors, as their investments are affected by contributing factors to the volatility in US and UK's stock markets.Originality/value>This study adds following promising values to the existing literature. First, the results complement the existing literature (Rubbaniy et al., 2021c) in documenting that type of COVID-19 proxy matters in explaining the volatility (EPU) relationships in financial markets, where market perceived fear of COVID-19 is appeared to be more pronounced than health-based fear of COVID-19. Second, the use of wavelet coherence approach allows us to observe lead–lag relationship between the selected variables, which captures the heterogeneous perceptions of investors across time and frequency and have important insights for the investors and portfolio managers. Finally, this study uses the improved data of COVID-19, stock market volatility and EPU compared to the existing studies (Sharif et al., 2020), which are too early to capture the effects of exponential spread of COVID-19 in the USA and the UK after March 2020.

COVID-19 related stringencies and financial market volatility: sectoral evidence from India

PurposeThis study aims to examine the impact of the stringency of COVID-19 protocols on the volatility of sectoral indices during the period 03:2020-05:2021. Specifically, this study investigates the role of economic disturbances on sectoral volatility by applying a range of conditional volatility techniques. Design/methodology/approachFor this analysis, two approaches were adopted. The first approach considers COVID stringency as a factor in the conditional variance equation of sectoral indices. In contrast, the second approach considers the stringency indicator as a possible determinant of their estimated conditional volatility. FindingsResults show that the stringency of the protocols throughout the pandemic phase led to an instantaneous spike followed by a gradual decrease in estimated volatility of all the sectoral indices except pharma and health care. Specific sectors such as bank, FMCG, consumer durables, financial services, IT, media and private banks respond to protocols expeditiously compared to other sectors. Originality/valueThe key contribution of this study to the existing literature is the innovative approach. The inclusion of the COVID stringency index as a regressor in the variance equation of the conditional volatility techniques was a distinctive approach for assessing the volatility dynamics with the stringency of COVID protocols. Furthermore, this study also adopts an alternative approach that estimates the conditional volatility of the indices and then tests the effect of the stringencies on estimated volatility in a regression framework.

Volatility spillovers during normal and high volatility states and their driving factors: A cross‐country and cross‐asset analysis

Understanding the transmission of volatility across markets is essential for managing risk and financial stability, especially under crisis periods during which an extreme event occurring in one market is easily transmitted to another market. To gain such an understanding and enrich the related literature, we examine in this article the system of volatility spillovers across various equity markets and asset classes using a quantile-based approach, allowing us to capture spillovers under normal and high volatility states. The sample period is 16 March 2011-10 November 2020 and the employed dataset comprises 12 implied volatility indices representing a forward-looking measure of uncertainty of global equities, strategic commodities and the US Treasury bond market. The results show that the identity of transmitters and receivers of volatility shocks differ between normal and high volatility states. The US stock market is at the centre of volatility spillovers in the normal volatility state. European and Chinese stock markets and strategic commodities (e.g. crude oil and gold) become major volatility transmitters in the high volatility state, after acting as volatility receivers during normal periods. Furthermore, we study the drivers of implied volatility spillovers using regression models and find that US Default spread contributes to the total volatility spillover index in both volatility states, whereas TED spread plays a significant role in the normal volatility state. As for the role of short rate and risk aversion, it is significant in the high volatility state. These findings matter to the decision-making process of risk managers and policymakers.

COVID-19 vaccine and post-pandemic recovery: Evidence from Bitcoin cross-asset implied volatility spillover.

This paper examines implied volatility spillovers and connectedness between Bitcoin and a broad range of traditional financial assets (U.S. equity market, gold, crude oil, emerging markets and developing markets) from January 8, 2019 to January 20, 2022. Vector Auto-Regression and Generalized Forecast Error Variance Decomposition are used to compare results before COVID-19, during COVID-19 and after the vaccine becomes available. Results indicate higher connectedness during COVID-19 but very low connectedness after the vaccine is available, signaling recovery in financial markets. We also find that Bitcoin is a strong transmitter of volatility during COVID-19.

Do stock market fear and economic policy uncertainty co-move with COVID-19 fear? Evidence from the US and UK

Purpose - The purpose of the paper is to investigate co-movement of major implied volatility indices and economic policy uncertainty (EPU) indices with both the health-based fear index and market-based fear index of COVID-19 for the USA and the UK to help investors and portfolio managers in their informed investment decisions during times of infectious disease spread. Design/methodology/approach - This study uses wavelet coherence approach because it allows to observe lead-lag nonlinear relationship between two time-series variables and captures the heterogeneous perceptions of investors across time and frequency. The daily data used in this study about the USA and the UK covers major implied volatility indices, EPU, health-based fear index and market-based fear index of COVID-19 for both the first and second waves of COVID-19 pandemic over the period from March 3, 2020 to February 12, 2021. Findings - The results document a strong positive co-movement between implied volatility indices and two proxies of the COVID-19 fear. However, in all the cases, the infectious disease equity market volatility index (IDEMVI), the COVID-19 proxy, is more representative of the stock market and exhibits a stronger positive co-movement with volatility indicts than the COVID-19 fear index (C19FI). This study also finds that the UK's implied volatility index weakly co-moves with the C19FI compared to the USA. The results show that EPU indices of both the USA and the UK exhibit a weak or no correlation with the C19FI. However, this study finds a significant and positive co-movemmit of EPU indices with IDEMVI over the short horizon and most of the sampling period with the leading effect of IDEMVI. This study's robustness analysis using partial wavelet coherence provides further strengths to the findings. Research limitations/implications - The investment decisions and risk management of investors and portfolio managers in financial markets are affected by the new information on volatility and EPU. The findings provide insights to equity investors and portfolio managers to improve their risk management practices by incorporating how health-related risks such as COVID-19 pandemic can contribute to the market volatility and economic risks. The results are beneficial for long-term equity investors, as their investments are affected by contributing factors to the volatility in US and UK's stock markets. Originality/value - This study adds following promising values to the existing literature. First, the results complement the existing literature (Rubbaniy et at, 2021c) in documenting that type of COVID-19 proxy matters in explaining the volatility (EPU) relationships in financial markets, where market perceived fear of COVID-19 is appeared to be more pronounced than health-based fear of COVID-19. Second, the use of wavelet coherence approach allows us to observe lead-lag relationship between the selected variables, which captures the heterogeneous perceptions of investors across time and frequency and have important insights for the investors and portfolio managers. Finally, this study uses the improved data of COVID-19, stock market volatility and EPU compared to the existing studies (Sharif et al, 2020), which are too early to capture the effects of exponential spread of COVID-19 in the USA and the UK after March 2020.

Construction of a volatility index from exchange-traded dollar-rupee options

Purpose This paper aims to propose the implied volatility index for the US dollar-Indian rupee pair (INRVIX). The study seeks to examine whether INRVIX truly reflects future USDINR (US Dollar-Indian rupee) volatility and signals profitable currency trading strategies. Design/methodology/approach Two measures of INRVIX are constructed and compared: a model-free version based on the methodology adopted by the Chicago Board of Options Exchange (CBOE) and a model-dependent version constructed from Black-Scholes-Merton-implied volatility. The proposed INRVIX is computed by tweaking some parameters of the CBOE methodology to ensure compatibility with the microstructure of the Indian currency derivatives market. The volatility forecasting ability of INRVIX is compared to that of a generalized autoregressive conditional heteroscedasticity (1,1) model. Ordinary least squares regression is used to examine the relationship between n-day-ahead USDINR returns and different quantiles of INRVIX. Findings Results indicate that INRVIX based on the model-free approach reflects ex post volatility in a better manner than its model-dependent counterpart, although neither measure is found to be an unbiased and efficient forecast. Subsample analysis across tranquil and turbulent periods corroborates the results. The volatility forecasting performance of INRVIX is found to be better than that of forecasts based on historical time-series. These results are consistent with similar studies of developed market currencies. The study does not find any significant relationship between extreme levels of INRVIX and the profitability of trading strategies based on such levels, which is contrary to results from the equity options market. Practical implications Foreign exchange volatility affects the costs of international trade and the external sector competitiveness of Indian multinationals. It is a significant risk factor for financial institutions and traders in the financial markets. An implied VIX for the USDINR could serve as an indicator of expected foreign exchange risk. It could thus provide a signal for a possible intervention in the forex market by the regulator. Regulators could introduce volatility derivative contracts based on the INRVIX. Such contracts would enable hedging of the pure volatility risk of dollar-rupee exposure. Thus, the study has practical implications for investors, hedgers, regulators and academicians alike. Originality/value To the author's knowledge, this is one of a few studies to construct an implied VIX for an emerging currency like the rupee. The study is based on up-to-date sample data that includes the recent COVID-19 market crash. A novel contribution of this paper is that in addition to examining whether INRVIX contains information about future USDINR volatility, and it also examines the signalling power of INRVIX for currency trading strategies.

The information content of ETF options

We examine the information content of China's Shanghai Stock Exchange (SSE) 50 ETF options introduced in 2015. Trading volume and implied volatilities of calls versus puts differ markedly: trading volume is consistently higher for calls, and implied volatility is higher for puts. Put-call volume and implied volatility ratios are not good predictors of future SSE 50 returns. Implied volatility follows a right-skewed smirk across strike prices, indicating a tendency among option traders to turn bullish and expect the stock market to recover from the June 2015 market crash. The options market dominates the price discovery process, with an average information leadership share of 67%. Our price discovery results persist during the COVID outbreak.

A grey-based correlation with multi-scale analysis: S&P 500 VIX and individual VIXs of large US company stocks

We provide first evidence of the multiscale comovement of correlations between the S&P 500 VIX and the VIXs of Amazon, Apple, Google, Goldman Sachs, and IBM. Using grey correlation and wavelet analysis on daily data (July 2011 - September 2021), the dynamics of grey-based correlations vary across scales and depend on the fluctuation intensity of the medium time–frequency domains. The lead–lag relationships of VIX correlations are inconclusive about the dominant periodicity, although some evidence of weekly and monthly periodicity emerges. The pandemic affects the dynamics and lead-lag relationships. Such indications are useful for trading strategies and market-timing decisions.

The Impact of the Infectious diseases and Commodity on Stock Markets

We investigate short and long-run effects of commodities and the EMVID indices in stocks. It pre-dominantly compares the magnitude of the effect in China and the USA and analyzes the differences utilizing the QARDL method. It becomes evident that the impacts of the EMVID and commodity indexes vary depending on the stock market developments. The short-run results reveal that the US stocks are negatively affected by the extreme quantiles, while almost all quantiles are negatively affected by commodity shocks in the long-run before pandemic. During the COVID-19 outbreak, the EMVID index is positively correlated with the stocks for both countries.

The Mediating Effects of Implied Volatility and Exchange Rate on the U.S. Tourism-Growth Nexus

In this paper, we examine the impact of destination risk and currency valuation on the U.S. tourism-growth nexus using the recently developed nonlinear autoregressive distributed lag cointegration technique. Tourism development is proxied by tourist arrivals, while growth is measured by real GDP. Empirical results show evidence of long-run asymmetric bidirectional causality. Positive shocks in tourism development directly impact growth, while negative shocks in GDP have a negative causal effect on tourism. This latter finding, which supports the growth-led tourism hypothesis, suggests that in the long run, tourism tends to improve following periods of economic weakness, perhaps due to the dollar’s weakness at such times. However, we have evidence only of unidirectional causality running from GDP to tourism in the short run. An important implication of these findings is the need to promote inbound tourism, especially when weakness in the U.S. economy is accompanied by a decline in the value of the dollar.