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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.
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Purpose: This 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/approach: For 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. Findings: Results 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/value: The 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. © 2022, Emerald Publishing Limited.
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This paper utilizes intraday five-minute stock market indices to investigate the causal relation between global stock market volatility and investor attention measured by the Google search volume index during the COVID-19 pandemic. Using the bi-power variation method proposed by Barndorff-Nielsen and Shephard (2004), we separate the realized volatility into two components: Continuous and Jump. Based on 5,583 stock indices-day observations, we find that investor attention is positively related to the realized volatility and its continuous component, but to a lesser extent to jumps. A growth in confirmed cases is positive to all measures of market volatility. Moreover, when the number of confirmed cases increases, more attentive investors reduce market volatility. Our findings are robust regarding various estimation approaches and are less likely to suffer from omitted variable biases and endogeneity concerns. Understanding the findings revealed in this paper is crucial to regulators and policymakers as warnings of additional risks facing retail investors around the globe over the extremely volatile periods. JEL Codes: G14;G15;G40;G41 © 2023 Institute of Financial Management and Research.
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While several studies evaluate the impacts of the novel coronavirus pandemic on different markets, it is worth the while to also examine its contagion (fractal) effect on the top (based on their market capitalization) twenty cryptocurrency markets. These cryptocurrency markets' information (return and volatility) were sampled for both the ex-ante and ex-post coronavirus outbreak periods for this event study analysis. The detrended cross-correlation approaches are employed for both the main and robustness analyses. The results are robust and confirm a significant fractal contagion effect of the pandemic on the cryptocurrency space through their return and volatility. The contagion effect is relatively stronger for the crypto markets' volatilities compared to the returns, nonetheless. Hence, this study supports the contagious effect of the coronavirus pandemic on the cryptocurrency markets and its policy implications for investors in the crypto space. © 2022 Elsevier Inc.
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This paper dissects the dynamics of the hedge fund industry with four financial markets, including the equity market, commodities, currencies, and debt market by employing a large number of assets from these markets. We employ four main representative hedge fund strategy indices, and a cap-weighted global index to estimate an asymmetric dynamic conditional correlation (ADCC) GJR-GARCH model using daily data from April 2003 to May 2021. We break down the performance, riskiness, investing style, volatility, dynamic correlations, and shock transmissions of each hedge fund strategy thoroughly. Further, the impact of commodity futures basis on hedge funds' return is analyzed. Comparing the dynamic correlations during the 2008 global financial crisis (GFC) with COVID-19 pandemic reveals changing patterns in hedge funds' investing styles. There are strong and pervasive shock spillovers from hedge fund industry to other financial markets, especially to futures commodities. An increase in the futures basis of several commodities drives up hedge funds' performance. While hedge fund industry underperforms compared to equity market and commodities, the risk-reward measures show that hedge funds are superior to other markets, and safer than the bond market. © 2022 Elsevier Inc.
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PurposeThis paper examines the time-varying return connectedness between renewable energy, oil, precious metals, the Gulf Council Cooperation region and the United States stock markets during two successive crises: the pandemic Covid-19 and the 2022 Russo-Ukrainian war. The main objective is to investigate the effect of the Covid-19 pandemic and the Russo-Ukrainian war on the connectedness between the considered stock markets. Design/methodology/approachThis paper uses the time-varying parameter vector autoregression approach, which represents an extension of the Spillover approach (Diebold and Yilmaz, 2009, 2012, 2014), to examine the time-varying connectedness among stock markets. FindingsThis paper reflects the effect of the two crises on the stock markets in terms of shock transmission degree. We find that the United States and renewable energy stock markets are the main net emitters of shocks during the global period and not just during the two considered crises sub-periods. Oil stock market is both an emitter and a receiver of shocks against Gulf Council Cooperation region and United States markets during the full sample period, which may be due to price fluctuation especially during the two crises sub-periods, which suggests that the future is for renewable energy. Originality/valueThis paper examines the effect of the two recent and successive crises, the Covid-19 pandemic and the 2022 Russo-Ukrainian war, on the connectedness among traditional stock markets (the United States and Gulf Council Cooperation region) and commodities stock markets (renewable energy, oil and precious metals).
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Socially responsible mutual funds (SRMF) , the "antisocially conscious", Vitium Global Fund Barrier Fund (formerly known as the Vice Fund, the term used in this paper) returns, volatility patterns , causal effects are examined in this study within the context of the lessons learned from the 2008 Global Economic and Financial Crisis (GEFC). In times of a new and unprecedented crisis due to the COVID-19 pandemic, a look back to our recent past reveals that volatility patterns on daily stock returns presented some level of predictability on prices for both types of funds. The research findings are significant as funds' potential predictability could help market players when designing their investment strategies. More specifically, an increase in volatility persistence is found after the GEFC, together with an increase in the Vice Fund's resilience to market shocks. Although all funds, without substantial differences, take time to absorb the shocks. A noteworthy outcome relates to SRMF that was able to achieve higher returns and exhibited lower volatility levels during the crisis period. Whereas the Vice Fund revealed long-run sustainable performance offering fund managers and investors investment opportunities that are endorsed by the fund performance over the period. Furthermore, unidirectional causality was found running from the Vice Fund to the SRMF, exhibiting a clear dominance during the GEFC period. The research findings contribute to the debate on the future of socially responsible investment, indicating that SRMF appears to be driven by "antisocially conscious" funds signaling limited rewards for investors inclined to invest in funds that are considered socially responsible.
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In India, the coronavirus (COVID-19) pandemic-induced country-wide regulatory lockdown and consequential supply-chain disruptions and market instability have all posed serious challenges before the regulators and policymakers. Amid the pandemic, the stock market showed return volatilities primarily due to the unexpected investors' behaviour. One of the behavioural biases is herding, which has the power to wreck the market equilibrium and shatter the market efficiency. Given that the pandemic has generated unprecedented spirals of uncertainties across the globe, thereby creating interruptions in the pattern of stock market investment decisions, this study examined the herding behaviour of 54 stocks of banking and financial services sectors listed in the national stock exchange. In the quantile regression framework, the study provides evidence of the presence of herding for public sector banking and financial services under the bull market conditions during the pandemic in the 90th quantile of the return distribution. This finding has implications for the mispricing of financial assets in these sectors. So, the study suggests removing information asymmetry among the market participants and devising policy initiatives for ensuring market stability. © 2023 Association of Asia Scholars.
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This study primarily investigates whether China's economic policy uncertainty (EPU) can predict the environmental governance index volatility, which selects companies regarding environmental protection such as sewage treatment, solid waste treatment, air treatment, and energy saving. Empirical results reveal that China's EPU index can predict the environmental governance index volatility. Furthermore, even during periods of fluctuating volatility and the COVID-19 pandemic, China's EPU index can reliably forecast the environmental governance index volatility. This paper tries to provide new evidence regarding the connection between EPU and environmental governance companies' stock volatility. © 2023
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This paper mainly investigates whether the climate policy uncertainty index (CPU) can predict the volatility of Chinese stock market volatility considering different sectors. Out-of-sample results show that climate policy uncertainty index can have a greater effect on the utility sector. We also investigate the effects of CPU based on longer horizons, different volatility levels and the COVID-19 pandemic. This paper tries to provide new evidence based on sector stock indices. © 2022
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The paper investigates the volatility spillover across China's carbon emission trading (CET) markets using the connectedness method based on the quantile VAR framework. The non-linear result shows strong volatility spillover effects in upper quantiles, resulting from major economic and political events. This is in accordance with the risk contagion hypothesis that volatility of carbon price returns is affected by the shocks of economic fundamentals and spills over to other pilots. Guangdong and Shanghai are the most significant contributors to volatility transmission because of their high liquidity and active markets. Hubei CET pilot has shifted from transmitter to receiver since the COVID-19 pandemic. Regarding the pairwise directional connectedness, geographical location and similar market attribute also matter in volatility transmission. This provides implications for policymakers and investors to attach importance to risk management given the quantile-based method rather than the average shocks. © 2023 Elsevier B.V.
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We investigate the predictive relationship between uncertainty and global stock market volatilities from a high-frequency perspective. We show that uncertainty contains information beyond fundamentals (volatility) and strongly affects stock market volatility. Using several crucial uncertainty measures (i.e., uncertainty and implied volatility indices), we prove that the CBOE volatility index (VIX) performs best in point (density) forecasting;the financial stress index (FSI) in directional forecasting. Furthermore, VIX's predictive power improved dramatically after the COVID-19 outbreak, and the VIX-based portfolio strategy enables mean-variance investors to achieve higher returns. There are two empirical properties of VIX: (i) it helps reduce significantly forecast variance rather than bias;and (ii) its forecasts encompass other uncertainty forecasts well. Overall, we highlight the importance of considering uncertainty when exploring the expected stock market volatility. © 2022 Elsevier Inc.
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This study investigates the impacts of crude oil-market-specific fundamental factors and financial indicators on the realized volatility of West Texas Intermediate (WTI) crude oil price. A time-varying parameter vector autoregression model with stochastic volatility (TVP-VAR-SV) is applied to weekly data series spanning January 2008 to October 2021. It is found that the WTI oil price volatility responds positively to a shock in oil production, oil inventories, the US dollar index, and VIX but negatively to a shock in the US economic activity. The response to the EPU index was initially positive and then turned slightly negative before fading away. The VIX index has the most significant effect. Furthermore, the time-varying nature of the response of the WTI realized oil price volatility is evident. Extreme effects materialize during economic recessions and crises, especially during the COVID-19 pandemic. The findings can improve our understanding of the time-varying nature and determinants of WTI oil price volatility. © 2022
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Our article employs a quantile vector autoregression (QVAR) to identify the connectedness of seven variables from April 1, 2019, to June 13, 2022, in order to examine the relationships between crypto volatility and energy volatility. Our findings reveal that the dynamic connectedness is approximately 25% in the short term and approximately 9% in the long term. The 50% quantile equates to the overall average connectedness of the entire period, according to dynamic net total directional connectedness over a quantile, which also indicates that connectedness is very intense for both highly positive changes (above the 80% quantile) and crypto and energy volatility (below the 20% quantile). With the exception of the early 2022 period when the Crypto Volatility Index transmits a net of shocks because of the Ukraine-Russia Conflict, dynamic net total directional connectedness implies that in the short term, the Crypto Volatility Index acts as a net shock receiver across time. While this indicator is a net shock receiver for long-term dynamics, wind energy is a net shock transmitter during the short term. Green bonds are a short-term net shock receiver. This role is valid in the long term. Clean energy and solar energy are the long-term net transmitters of shocks;nevertheless, the series is always and only momentarily a net receiver of shocks because of the short-term dynamics. Natural gas and crude oil play roles in both two quantiles. Dynamic net pairwise directional connectedness over a quantile suggests that uncertain events like the COVID-19 epidemic or Ukraine-Russia Conflict influence cryptocurrency volatility and renewable energy volatility. © 2022 Elsevier Ltd
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The pandemic caused by the novel coronavirus COVID-19 has impact the economies of countries across the world. In a short period of time, researchers have begun to analyse the effect of the pandemic on global stock markets. Although the most known measurements of COVID-19 are the number of new cases and deaths, there are more robust indicators. In particular, the effective reproductive number is one of the most important indicators to analyse the pandemic which indicates the degree to which the spread is under control. In this paper, we assess the impact that the Effective Reproductive Number (Rt) has on 26 countries around the world (32 stock market indexes) comparing the performance of various forms of Generalized AutoRegressive Conditional Heteroskedasticity models. The results demonstrate that of the 32 stock markets analysed, 37.5% had a negative effect with respect to Rt and only in 12.5% of the cases was the effect of the variation of Rt positive. This implies that in more than a third of the stock markets analysed as the pandemic progressed uncontrolled the result was a decrease in the value of the market index. The 11 of the 26 countries analysed had a negative and significant effect (Brazil, Germany, Indonesia, Israel, Italy, Japan, Russia, South Korea, Sweden, Taiwan, and United States). Findings suggest that the Effective Reproductive Number volatility had a significant impact on 10 of the 26 countries analysed (38.5%) (Australia, Brazil, Canada, China, India, Italy, Mexico, Russia, Singapore and United Kingdom). © 2023 John Wiley & Sons Ltd.
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With several commodity and financial markets allegedly performing poorly during the coronavirus disease (Covid-19) pandemic, the objective of this study is to examine how the pandemic has affected stock markets in the G7 economies. The study applies the recently developed cross-quantilogram model introduced by Han et al. (2016) to investigate quantile dependence between the conditional stock return distributions of G7 countries and the total daily global confirmed Covid-19 cases across investment horizons. The results reveal that the cross-quantile dependence between the confirmed Covid-19 cases and G7 stock returns is most significant in the short and medium term. The interlinkage weakens as the lag period lengthens. These findings imply that, in the short and medium term, stock markets in the G7 countries reacted negatively and disproportionately to the increase in the number of daily verified Covid-19 cases. Besides, cross-quantile correlations calculated from recursive subsamples indicate that they change over time, especially in low and medium quantiles, suggesting that they are prone to jumps and discontinuities in the dependence structures. The findings can aid investors and policymakers in better understanding stock market dynamics, particularly during times of great stress and unknown events.
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We examine the time-frequency co-movements and return and volatility spillovers between the rare earths and six major renewable energy stocks. We employ the wavelet analysis and the spillover index methodology from January 1, 2018 to May 15, 2020. We report that the COVID-19-triggered significant increase in co-movements and spillovers in returns and volatility between the rare earths and renewable energy returns and volatility. The rare earths act as net recipient of both return and volatility spillovers, while the clean energy stocks are net transmitters of return and volatility spillovers before and during the COVID-19 crisis. The solar and wind stocks are net transmitters/receivers of spillovers before/during the pandemic. The remaining markets shift from net spillover receivers to transmitters or vice versa;evidencing the effects of the pandemic. Our results show that cross-market hedge strategies may have their efficiency impaired during the periods of crises implying a necessity of portfolio rebalancing. © 2022 The Authors
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The purpose of this paper is to explore whether the categorical Economic Policy Uncertainty (EPU) indices are predictable for the volatility of carbon futures, in the mixed data sampling (MIDAS) regression framework. The prediction methods include the MIDAS-RV model, the MIDAS models extended by individual categorical EPU index, combination prediction approaches, the MIDAS models extended by dimensionality reduction techniques as well as the machine learning methods on the basis of MIDAS model and Markov regime switching method. We find firstly that categorical EPU indices are predictable for carbon futures volatility, but the predictive power of individual categorical EPU indices is not robust. Secondly, machine learning methods, especially the machine learning method considering the Markov regime switching structure, help to obtain valid information from multiple categorical EPU indices and produce robust and superior prediction accuracy for carbon futures volatility. The results of the extension analysis also found that machine learning methods, especially the machine learning method considering the Markov regime switching structure help to produce higher investment performance and more accurate long-term carbon futures volatility forecasts. Meanwhile, we also find the advantages of the MIDAS based machine learning methods over the traditional AR based machine learning methods. Finally, the forecasting performance of the machine learning method which considering Markov regime switching structure are superior during both the low and high volatility regimes and even during the COVID-19 pandemic. © 2022 Elsevier Inc.
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This study investigates the interconnection among several commodities in the advent of two well-known phenomena: the 2008 global financial crisis (GFC) and the COVID-19 pandemic. We use a daily return series for selected commodities: three base metals (copper, zinc, and lead), two benchmark crude oils (WTI and Brent), and gold. Three different methods have been considered to study interconnection: Multifractality, Network theory, and Wavelet coherences. By applying Detrending Moving-average Cross-correlation Analysis (DMCA) method, we witnessed an increase in cross-correlation in the higher time windows in most time series. Generally, we observe that the benchmark crude oils have the highest relationships, and then, in the following positions, we have the dependency among base metals (copper, lead, and zinc) and between the base metals and the crude oils. In the context of the Wavelet analysis, we notice that the significant fluctuations and changes in the extent of interconnections among data could be traced when the two crises occurred, particularly between October 2018 and April 2021, and in the frequency range of 4-128 days. This phenomenon indicates the role of the COVID-19 pandemic in creating a volatile situation in the commodity markets. The findings of this study have significant implications for investors, academic researchers, and policymakers.
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Purpose: This study aims to investigate the relationship between stock markets, environmental, social and governance (ESG) factors and Shariah-compliant in an integrated framework. Design/methodology/approach: The authors employ the multivariate factor stochastic volatility (mvFSV) framework to extract the volatility of the different sectoral indices. Based on this evidence, the authors employ the quantile vector autoregressive (QVAR) approach to examine the dynamic spillover connectedness among the aforementioned indices. Findings: The study emphasizes the following major findings: (1) significant time-varying spillover connectedness across quantiles, (2) bidirectional and asymmetric spillover effect among the ESG index and the other sectoral indices, (3) the strength of spillover connectedness is time-varying across quantiles, (4) based on the perspective of portfolio optimization, ESG market is a significant strong forecasting contributor to conventional and Shariah-compliant markets, (5) overall, the findings point out serious quantile pass-through effect among ESG index and the other sectoral indices during the COVID-19 health crisis. Originality/value: This study extends the previous literature in the following ways. First, to the best of the researchers' knowledge, none of the existing studies have investigated the relationship between stock markets, ESG factors and Shariah-compliant in an integrated framework. Second, this study extends the previous scholarships by applying the mvFSV. Third, the authors propose a new rolling version to estimate dynamic spillovers, namely the rolling-window quantile VAR method. This approach provides a great advantage in computing the dynamics of return and variance spillover between variables in terms not only of the overall factor but also of the net (pairwise) aspect. © 2023, Emerald Publishing Limited.