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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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We examine the impact of the recent restrictions/bans imposed by several nations on air travel to India in the light of the increasing number of infections amid the second wave of covid-19. We employ the standard event study method on a sample of 34 airline stocks across seven nations to find that the recent restrictions/bans on air travel significantly impact the global airline industry, although the country-specific impacts are not similar. We find that the post-event reaction in all nations has been different from those evidenced during the global pandemic declaration. We are the first to examine these impacts during the current wave of the pandemic. It contributes to the literature on the effects of the pandemic on the global airline industry. Further, it also provides practical explanations to the investors on how the airline stocks react to the persistence of the pandemic. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
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This study examines the impact of the COVID-19 outbreak on the French stock market and investigates whether companies with a commitment to corporate social responsibility (CSR) were less affected. Examining a sample consisting of 464 French firms, we separate firms that have implemented CSR activities around the event period (considered as active CSR adopters) from CSR-adopters (firms that did not indulge in CSR activities around that period) and non-CSR adopters. The empirical results indicate that active CSR adopters were less affected as some positive returns have been observed around the event date, indicating that their stock prices were relatively resistant to the crisis. The multivariate analysis shows that the French market reacted significantly to CSR strategy and that active CSR adopters are the least affected.
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In this paper, we study the impact of news and sentiments related to covid-19 on United Kingdom (UK)'s stock returns from February 4, 2020 to December 7, 2020. Our results show that covid-19 daily cases exert a significant negative effect on stock returns whereas covid-19 daily deaths have a significant positive impact. These findings hold when covid-related news and sentiments indices are controlled with the 2nd wave data, and when the US policies and equity market volatilities from infectious diseases are used as controls. The magnitude of the effect of covid cases and deaths indicates that the pandemic is not very harmful to the UK stock market. © 2022 CEPII (Centre d'Etudes Prospectives et d'Informations Internationales), a center for research and expertise on the world economy
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This paper examines whether the Covid-19 pandemic has had a homogeneous or heterogeneous effect on stock returns in India. We consider panel data by using 1,318 companies that are listed on the National Stock Exchange of India. We find that the daily growth rate in Covid-19 cases and Covid-19 deaths are negatively associated with stock returns. Further, we observe that the average stock returns during Lockdown 2 are positive and highly significant, while the returns during Lockdowns 3 and 4 are negative. Moreover, our results show that the chemical, technology, and food and beverage industries earn higher returns. In contrast, the banking and finance, automotive, services, and cement and construction industries yield lower returns for the overall period. Interestingly, all industry groupings in this study earn a positive return during the lockdown period. In particular, the chemical, technology, automotive, metals and mining, and food and beverage industries provide higher returns during the lockdown period. Finally, this study supports the claim that the Covid-19 pandemic has had a heterogeneous effect in the Indian stock markets. © 2022, Academy of Economics and Finance.
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In the past, it was believed that investors may generate abnormal returns (AR) for trading stocks by employing technical trading rules. However, since the COVID-19 pandemic broke out, stock markets around the world seem to suffer a serious impact. Therefore, whether investors can beat the markets by applying technical trading rules during the period of COVID-19 pandemic becomes an important issue for market participants. The purpose of this study is to examine the profitability of trading stocks with the use of technical trading rules under the COVID-19 pandemic. By trading the constituent stocks of DJ 30 and NASDAQ 100, we find that almost all of the trading rules employed in this study fail to beat the market during the COVID-19 pandemic period, which is different from the results in 2019. The revealed findings of this study may shed light on that investors should adopt technical trading with care when stock markets are seriously affected by black swan events like COVID-19. © 2023 World Scientific Publishing Company.
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We study the effects of COVID-19 intensity on equity market liquidity across U.S. states. We exploit cross-sectional variation in cases and deaths to investigate any association with the deterioration of stock liquidity of firms whose headquarters or operations are in the corresponding state(s). Our motivation stems from several underlying economic channels such as order processing costs, inventory costs, and adverse selection costs. We find strong negative relations between pandemic intensity and various intra-day liquidity measures. Our results are more pronounced for firms operating in states with more stringent containment and health measures and within industries with greater risk exposure.
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The study investigates the asymmetric effect of investors sentiments on herding behavior and stock returns of S&P 500 markets during pre and post covid 19. We analyze daily data from May 15, 2000 (Pre Covid) to 20 Feb 2020 and form 20 Feb to –13 May, 2022 (Post Covid). We conduct Modified multiple regression Analysis by introducing investors sentiments proxy i.e., trading volume into the Chang et al., (2000) herding model named as cross-sectional absolute deviation along with Vector Autoregressive Regression and Granger Causality tests. We establish that trading volume increases herding asymmet-ric. Post COVID-19 has significant negative effects on herding behaviour. The findings illustrate that COVID-19 increased herding behavior in S&P 500 markets and became more intensified during COVID-19, which contributes to ac-centuate and elongate it. The study also documents significant positive effect of investor sentiment on stock returns, whereas COVID-19 has negative effect on S&P 500 stock returns. We propose that investor sentiments may present extrapolative or predictive feature of herding behaviour. The study will be ben-eficial to shape an understanding of different dynamics associated with portfolio and market in-efficiency, trading strategies as well as risk management perspective. © 2023, Economic Laboratory for Transition Research. All rights reserved.
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This paper investigates the relationship between oil and airline stock returns under different time frequencies. First, we propose an Autoregressive moving average model with mixed frequency exogenous variable to analyse the different impacts of oil on airline stock returns on daily, weekly, and monthly basis. We consistently find a negative oil-airline stock return nexus on a daily basis, but a positive relationship on a weekly basis. While the former supports the economic-based channel, the latter is in line with the market inertia channel. Our findings help explain mixed results reported in the literature. Further, our time frequency connectedness analysis shows that the economic-based channel dominates the market inertia channel since the connectedness is more pronounced in the short-run compared to the medium- and long-run. Our block connectedness results highlight that business models of airline firms can play a significant role in affecting the connectedness, in which the low-cost airlines are more sensitive to the oil price changes. It is worth noting that there are distinguished drivers of the oil-airline stock return nexus in different time frequencies. The drivers also vary between the Global Financial Crisis and the COVID-19 pandemic. Our results are consistent under a battery of robustness checks and deliver important implications to investors, portfolio managers, and executives of airline firms. © 2022 Elsevier B.V.
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This paper investigates the impact of COVID-19 on financial markets. It focuses on the evolution of the market efficiency, using two efficiency indicators: the Hurst exponent and the memory parameter of a fractional Lévy-stable motion. The second approach combines, in the same model of dynamic, an alpha-stable distribution and a dependence structure between price returns. We provide a dynamic estimation method for the two efficiency indicators. This method introduces a free parameter, the discount factor, which we select so as to get the best alpha-stable density forecasts for observed price returns. The application to stock indices during the COVID-19 crisis shows a strong loss of efficiency for US indices. On the opposite, Asian and Australian indices seem less affected and the inefficiency of these markets during the COVID-19 crisis is even questionable. © 2022 Elsevier B.V.
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This paper provides new evidence on workers' perceptions of the returns to job search effort using hypothetical vignettes. This allows us to overcome limitations with survey data on realized behavior in which search effort and reservation wages may be endogenous to perceived job finding rates. The perceived job finding probability is nearly linear in hours searched and only slightly concave for most respondents. While workers are over-optimistic about the probability of receiving a job offer conditional on any search, they perceive the marginal return to additional search hours as positive but comparably low. Job seekers receiving an offer, update their perceived returns upwards, while the beliefs of unsuccessful searchers regress towards the direction of the mean. We find little evidence that novel aspects of the pandemic recession have fundamentally changed workers' motivations for job search: that an existing job is expected to end or has unsatisfactory pay are the primary motives for on-the-job search. On the contrary, workers' ability to do their tasks from home is not a strong predictor of job search nor a significant motive for switching occupations. © 2022 The Author(s)
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We find that the COVID-19 pandemic increases (decreases) stock return sensitivity to market -wide (firm-specific) news, which is associated with return reversals (delayed reactions). These results are consistent with limited investor attention and investors paying heightened (reduced) attention to macro (micro) information after the outbreak. There are more biased reactions when the epidemic spread is higher, to good news than bad news, for firms headquartered in pandemic epicenters, and for larger stocks. We also find higher (lower) imbalanced trading, information flow, and price efficiency associated with market-wide (firm-specific) news during the pandemic.
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Purpose: In 2014, real estate investment trust (REIT) emerged as a new alternative investment option in India. This research aims to give an empirical authentication of the Indian REITs performance from April 2019 to July 2022 across a range of investment variables. Design/methodology/approach: Using monthly total returns in Indian Rupee, risk-adjusted Indian REIT performance and investment portfolio characteristics are examined. Indian REITs' potential in a diversified multi-asset portfolio is analysed using the mean-variance analysis, asset allocation diagram and efficient frontier. Findings: During April 2019–July 2022, Indian REITs provided a lower return than stocks but outperformed bonds despite coronavirus disease 2019 (COVID-19) lockdowns, which hurt the traditional working from office concept. The study also examined REIT allocation to an Indian mixed-asset portfolio and the benefits of a diversified portfolio. Practical implications: Indian REITs provide a liquid, transparent alternative to direct property for investors seeking exposure to Indian real estate markets. Indian REITs gave real estate companies an extra funding source and investors an alternate asset. This paper explores Indian REITs' potential opportunities, given that domestic and foreign investors' demand for transparent property investment in India. The analysis found a positive early performance despite a challenging environment. Originality/value: This paper offers the first empirical performance validation of Indian REITs as a way to obtain exposure to commercial property in India and the REITs' role in a diversified asset portfolio. The authors' study improves investors' decision-making abilities by providing empirically validated, valuable and practicable property investing insights. © 2022, Emerald Publishing Limited.
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We examine herding behavior before, during, and after the Covid-19 pandemic in eight prominent Asian stock markets. Daily stock returns for the period Jan- 2018 to July- 2022 in the markets were investigated using the models prescribed by Chang et al., (2000) and Chiang and Zheng (2010). The empirical results provide strong support to earlier studies by providing robust evidence of herding in Vietnam, Indonesia, India, South Korea, and Singapore when the market is bullish and Indonesia and Vietnam also exhibit herding when the market is bearish. Herding tendency is dominant for Vietnam, India, and Indonesia during the pandemic with the post-pandemic time being more potent for China and Vietnam. Notably, an anti-herding tendency is found in China, Hong Kong, and Singapore. As a policy measure, efficient information dissemination, deterrence of insider trading, and regulation of mispricing can be undertaken.
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This paper examines the resilience of banks as perceived by market participants during the COVID-19 crisis. We analyse how bank stock returns during January-March 2020 relate to the pre-crisis activation of macroprudential policy across 52 countries in a cross-sectional dimension. We find that, overall, a tighter macroprudential policy stance is beneficial for bank systemic risk, as assessed by equity market investors. A robust finding is that a perceived decrease in bank risk stems primarily from the use of credit growth limits, reserve requirements, and dynamic provisioning. By contrast, a pre-crisis build-up of capital surcharges on systemically important financial institutions seems to lower bank stock returns. Alternative bank risk indicators suggest that the latter is likely to be driven by concerns about profits rather than the probability of default.
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This paper investigates the stock-bond dependence structure using a dependence-switching copula model. The model allows stock-bond dependence to switch between positive dependence regimes (contagions or crashes of the two markets during downturns or booms in both markets during upturns) and negative dependence regimes (flight-to-quality from stock markets to bond markets or flight-from-quality from bond markets to stock markets). Using data from four developed markets including the US, Canada, Germany, and France for the period between January 1985 and August 2022, we find that the within-country stock-bond (extreme) dependence could be both positive and negative. In the positive dependence regimes, the stock-bond dependence is asymmetric with stronger left tail dependence than the right tail dependence, giving evidence of a higher likelihood of joint stock-bond market crashes or contagions during market downturns than the collective stock-bond market booms. Under the negative dependence regimes, we find both flight-from-quality and flight-to-quality, with flight-to-quality being more dominant in the North American markets while flight -from-quality is more prominent in the European markets. Further, the dependence switches between positive and negative regimes over time. Moreover, the dependence is mainly in the positive regimes before 2000 while mostly in the negative regimes after that, indicating contagions mostly before 2000 and flights afterwards. Further, the dependence switches between positive and negative regimes around financial crises and the COVID-19 pandemic. These results greatly enrich the findings in the existing literature on the co-movements of stock-bond markets and are important for risk management and asset pricing.
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This article explores the impact of fuel price movements on the stock market return of 2020 during the COVID-19 disruptions. In doing so, a monthly data of seven selected stock market indices representing developed and emerging economies globally was used for analysis. The study used a time-varying parameter VAR model to examine a time-varying causal association between oil prices and stock market returns and a novel quantile-causality approach to capture the fluctuations of these markets under COVID-19's varying market conditions. The study further utilises the entropy transfer approach to capture the Granger-causal relationship in the presence of nonlinearities of the data series. The results indicate a high information flow from fuel prices to the FTSE-100, Pacific, and European stock indicies, but not the other way round. The results show that, for the FTSE-100 and the European region, there is a two-way information flow between equities and natural gas, and vice-versa. However, a one-way information flow was established from the stock market to the Pacific and emerging economies.
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COVID-19 unexpectedly ensnared the entire world and wreaked havoc on global economic and financial systems. The stock market is sensitive to black swan events, and the COVID-19 disaster was no exception. Against this backdrop, this study explores the impact of COVID-19 and economic policy uncertainty (EPU) on Chinese stock markets' returns for the period spanning January 23, 2020 to August 04, 2021. The outcomes of the novel quantile-on-quantile regression analysis revealed that both COVID-19 and EPU had a significant negative impact on both Shanghai and Shenzhen stock market returns, while COVID-19 aggravated the level of economic uncertainty in both financial markets. The quantile causality approach of Troster et al. (2018) validates our main estimations. We conclude that COVID-19 and a high level of EPU enervated the returns of China's leading stock markets. Our study provides key insights to policymakers and market participants to determine the behavior of China's stock market returns vis-à-vis COVID-19 during the peak of the pandemic and beyond. Specifically, our findings apprise portfolio investors to augment their portfolio diversification fronts.
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The Corona Crisis led to a high drawdown in the stock markets in the whole world in March 2020. After that, infection rates, incidences, and dead people were published by many countries. Based on 11 stock price indices analyses according to volatility and correlation, we can conclude that only one event seems to be substantially affected by a Corona-related event not tied to specific countries. Therefore, in times of crisis, stock indices correlate highly positively. This leads us to a second step to our central research question: Do Corona dates significantly impact the stock price development? Therefore, we analyzed several events in Germany and the US with the event study approach. The main result is that only the March 2020 event significantly impacts the volatility and the returns. The following bad news but also the good news do not have any influence on the share prices and do not lead to abnormal returns. For example, the first approval of vaccinations had no apparent effect on the stock market, which was reflected in price movements comparable to those during the initial Lockdown.
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Since the World Health Organization (WHO) declared the COVID-19 outbreak as a public health emergency of international concern, the global economy has been straining under a range of burdens: surging inflation and unemployment rates, tangled global supply chains and tumbling financial markets (Batten et al., 2022;Boubaker et al., 2022;Choudhury et al., 2022;Liu et al., 2022). [...]using a difference-in-differences (DID) analysis, they investigate the epidemic's impact on the market quality of overseas companies and compare it to that of local firms with the same name. [...]the authors compare international companies based on firm-specific features and those of their home countries. According to the authors' findings, the conflict has significantly negatively influenced airlines, although it has benefited the market for military goods. According to the results, investors in these energy markets exhibit a herding behavior.