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Due to the COVID-19 pandemic, a very low interest rate policy was economically applied in Korea, and various investment activities through loans were activated. Real estate and stock prices rose rapidly, and many people became involved in stock investments because of economic instability. However, hastily started investment behavior resulted in economic loss and addictive behavior in stocks. The phenomenon of using stock investment to satisfy individual sensation seeking or addictive dependence on stocks due to lowered life satisfaction expectancy can become a serious social problem. However, the improvement of distress tolerance and the ability to endure pain despite frequent stock price fluctuations or lowered life satisfaction expectancy would be good alternatives to prevent stock addiction tendency. Therefore, the purpose of this study is to test the moderating effect of distress tolerance on the effect of adults' sensation seeking and life satisfaction expectancy in stock addiction tendencies. The participants were 272 adults with stock investment experience. As a result, distress tolerance significantly moderated the positive effect of sensation seeking on stock addiction tendency. In addition, life satisfaction expectancy did not significantly increase in the group with high distress tolerance even if life satisfaction expectancy was lowered. These results suggest that stock addiction can be prevented by enhancing distress tolerance.
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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.
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Do stronger relationships with customers (customer-company relationships [CCR]) help firms better weather economic crises? To answer this question, we examine firm performance during the stock market crashes associated with the two most severe economic crises of the last 15 years-the protracted Great Recession crisis (2008-2009) and the shorter but extreme COVID-19 pandemic crisis (2020). Juxtaposing the predominant expected utility theory perspective with observed deviations in investor behavior during crises, we find that both pre-crash firm-level customer satisfaction and customer loyalty are positively associated with abnormal stock returns and lower idiosyncratic risk during a market crash, while pre-crash firm-level customer complaint rate negatively affects abnormal stock returns and increases idiosyncratic risk. On average, we find that one standard deviation higher CCR is associated with between $0.9 billion and $2.4 billion in market capitalization on an annualized basis. Importantly, we find that these effects are weaker for firms with higher market share during the COVID-19 crash, but not during the Great Recession crash. These results are found to be robust to a variety of alternate model specifications, time periods, sub-samples, accounting for firm strategies during the crises, and endogeneity corrections. When compared to relevant non-crash periods, we also find that such effects are equally strong during the Great Recession crash and even stronger during the COVID-19 pandemic crash. Contributing to both the marketing-finance interface literature and the nascent literature on marketing during economic crises, implications from these findings are provided for researchers, marketing theory, and managers. Supplementary information: The online version contains supplementary material available at 10.1007/s11747-023-00947-1.
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Through the reinterpretation of housing data as candlesticks, we extend Nature Scientific Reports article by Liang and Unwin [LU22] on stock market indicators for COVID-19 data, and utilize some of the most prominent technical indicators from the stock market to estimate future changes in the housing market, comparing the findings to those one would obtain from studying real estate ETF's. By providing an analysis of MACD, RSI, and Candlestick indicators (Bullish Engulfing, Bearish Engulfing, Hanging Man, and Hammer), we exhibit their statistical significance in making predictions for USA data sets (using Zillow Housing data) and also consider their applications within three different scenarios: a stable housing market, a volatile housing market, and a saturated market. In particular, we show that bearish indicators have a much higher statistical significance then bullish indicators, and we further illustrate how in less stable or more populated countries, bearish trends are only slightly more statistically present compared to bullish trends.
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We assess the individual and compounding impacts of COVID-19 and climate physical risks in the economy and finance, using the EIRIN Stock-Flow Consistent model. We study the interplay between banks' lending decisions and government's policy effectiveness in the economic recovery process. We calibrate EIRIN on Mexico, being a country highly exposed to COVID-19 and hurricanes risks. By embedding financial actors and the credit market, and by endogenising investors' expectations, EIRIN analyses the finance-economy feedbacks, providing an accurate assessment of risks and policy co-benefits. We quantify the impacts of compounding COVID-19 and hurricanes on GDP through time using a compound risk indicator. We find that procyclical lending and credit market constraints amplify the initial shocks by limiting firms' recovery investments, thus mining the effectiveness of higher government spending. When COVID-19 and hurricanes compound, non-linear dynamics that amplify losses emerge, negatively affecting the economic recovery, banks' financial stability and public debt sustainability.
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Purpose: This paper focuses on the stock market performance of a set of biopharmaceutical companies listed in the US stock exchange in response to news about the unfolding of the COVID pandemic and the development of COVID-19 vaccines. Methods: We analyze the short-term impact of some episodes by means of event analysis. We consider two categories of events: news related to the expansion of the pandemic and information about the development of COVID-19 vaccines. Results: We find that the impact during the first months of the pandemic news impacted the returns of the pharmaceutical firms, but the effect was not large, in general. The only exceptions are two small biotechnological firms, Moderna and Novavax, are exceptions since they registered large positive abnormal returns, which vanished over time. Encouraging announcements about the success of Phase III results had a positive impact the share prices of Pfizer, Moderna and Novavax. Our results also suggest that the emergency authorization provided by the US regulatory agency to the Pfizer vaccine was anticipated several days in advance and welcomed by the market. The announcement of a deal to supply vaccines between Moderna and the European Commission have generated large positive returns for this company. Conclusion: Our findings have policy implications. First, financial markets have supported and reinforced government strategies to fight the pandemic, characterized by funding of promising projects, building diversified vaccine portfolios and expediting approvals by regulatory agencies. Second, our findings suggest that not all drug developers have automatically obtained large profits from the design and manufacturing of COVID-19 vaccines, according to the behaviour of stock prices. These results cast doubts over attempts to discredit the efficacy of COVID-19 vaccines with the argument that they are primarily a means to obtain large and quick profits by pharmaceuticals, or than vaccination campaigns are driven by economic goals rather than by public health considerations.
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This study investigates the impact of COVID-19 pandemic on the Chinese stock market in 2020. Using daily data of three industries, this study addresses the identification of abnormal stock returns as a multiple hypothesis testing problem and proposes to apply a grouped comparison procedure for better detection. By comparing the numbers of daily signals and numbers of stocks with abnormal positive and negative returns, the empirical result shows that the three industries perform differently under the pandemic. Compared to the non-grouped testing procedure, the signals found by the grouped procedure are more prominent, which is advantageous for some situations when there tends to be abnormal performance clustering at the occurrence of major event. This paper on stock return anomalies gives a new perspective on the impact of major events to the stock market, like the global outbreak disease.
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PurposeThe authors examine the volatility connections between the equity markets of China and its trading partners from developed and emerging markets during the various crises episodes (i.e. the Asian Crisis of 1997, the Global Financial Crisis, the Chinese Market Crash of 2015 and the COVID-19 outbreak).Design/methodology/approachThe authors use the GARCH and Wavelet approaches to estimate causalities and connectedness.FindingsAccording to the findings, China and developed equity markets are connected via risk transmission in the long term across various crisis episodes. In contrast, China and emerging equity markets are linked in short and long terms. The authors observe that China leads the stock markets of India, Indonesia and Malaysia at higher frequencies. Even China influences the French, Japanese and American equity markets despite the Chinese crisis. Finally, these causality findings reveal a bi-directional causality among China and its developed trading partners over short- and long-time scales. The connectedness varies across crisis episodes and frequency (short and long run). The study's findings provide helpful information for portfolio hedging, especially during various crises.Originality/valueThe authors examine the volatility connections between the equity markets of China and its trading partners from developed and emerging markets during the various crisis episodes (i.e. the Asian Crisis of 1997, the Global Financial Crisis, the Chinese Market Crash of 2015 and the COVID-19 outbreak). Previously, none of the studies have examined the connectedness between Chinese and its trading partners' equity markets during these all crises.
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The transmission rate is an important indicator for characterizing a virus and estimating the risk of its outbreak in a certain area, but it is hard to measure. COVID-19, for instance, has greatly affected the world for more than 3 years since early 2020, but scholars have not yet found an effective method to obtain its timely transmission rate due to the fact that the value of COVID-19 transmission rate is not constant but dynamic, always changing over time and places. Therefore, in order to estimate the timely dynamic transmission rate of COVID-19, we performed the following: first, we utilized a rolling time series to construct a time-varying transmission rate model and, based on the model, managed to obtain the dynamic value of COVID-19 transmission rate in mainland China;second, to verify the result, we used the obtained COVID-19 transmission rate as the explanatory variable to conduct empirical research on the impact of the COVID-19 pandemic on China's stock markets. Eventually, the result revealed that the COVID-19 transmission rate had a significant negative impact on China's stock markets, which, to some extent, confirms the validity of the used measurement method in this paper. Notably, the model constructed in this paper, combined with local conditions, can not only be used to estimate the COVID-19 transmission rate in mainland China but also in other affected countries or regions and would be applicable to calculate the transmission rate of other pathogens, not limited to COVID-19, which coincidently fills the gaps in the research. Furthermore, the research based on this model might play a part in regulating anti-pandemic governmental policies and could also help investors and stakeholders to make decisions in a pandemic setting.
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This study analyzed the impact of COVID-19 outbreak and targeted required reserve ratio cut policy on stock returns of Chinese listed companies. This paper uses the data of 3,449 A-share listed companies from February 3, 2020 to December 31, 2020 for research, the empirical results showed that stock prices of private enterprises with stronger debt-paying ability and looser financing constraints, and state-owned enterprises with less supply chain credit risks performed better, in the central and western regions, enterprises with stronger solvency and looser financing constraints have better stock price performance during the early stages of pandemic. After the implementation of the targeted RRR cut policy, the stock prices of enterprises with poor solvency, private enterprises, and enterprises in central and western regions with strong financing constraints, state-owned enterprises, and enterprises in eastern region with high credit risks all showed significant reversals, and the stock prices reflected the effect of the targeted RRR cut policy in the short and medium term. Over time, the pandemic has been controlled, and the resumption of work and production has freed most enterprises from financial difficulties. However, due to sporadic outbreaks, large private enterprises and eastern enterprises with strong risk resistance and loose financing constraints enjoy better stock price performance. This study is helpful for enterprises to understand the value of financial flexibility and solvency and provides a reference for enterprises to make financial decisions: how to balance the benefits and costs of solvency. © Tian Wang, Fang Fang and Linhao Zheng, 2023.
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Initial Public Offering (IPO) is a fund-raising tool through which a company gets listed for the first time under SEBI regulation and issues IPOs to raise funds from the public. The shift from a privately-owned to a publicly-owned firm via an IPO is the most significant event in a company's life (Pagano et al., 1998). In an IPO investment, there is limited historical data to analyze and predict the future performance of the company;hence it becomes a risky investment for the investors as they cannot predict how the shares will perform in the future. Most companies that go for an IPO are in the growth or expansion phase so it becomes more difficult to predict their market position and performance in the future, which leads to uncertainty in deriving their future value. Also, most IPOs are of companies going through a transitory growth period, and are therefore subject to additional uncertainty regarding their future value. This study analyzes the performance of the IPOs issued during the Covid-19 pandemic, when the markets across the world faced massive disruptions. The IPOs from various sectors like finance, technology, service, infrastructure, food, pharmaceutical and information technology were considered for the study. The study also analyzes the factors affecting investor perception towards investment in an IPO. The study considered the IPOs issued during the pandemic, and their performance on the listing day was measured by considering issue price, listing price and closing price. It was observed that 90% of the IPOs selected performed well during the listing day and 10% underperformed. It was also found that factors like company brand, company sector, fundamental analysis, company ratings, expert opinion and stock market conditions had a positive impact on the investors' decision to invest in an IPO. The study also revealed that factors like risk factor in primary market, returns on IPO on the listing day and Gray Market Premium have no significant impact on the investors' perception.
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This paper examines whether the ESG reporting transparency of listed firms in the UK can play a role in mitigating the impact of the COVID-19 pandemic. We investigate 350 UK firms in the FTSE350 index from 2016 to 2021 with daily data on stock performance and annual data on financial performance. The empirical results show that firms with a high ESG disclosure score have a lower volatility of stock performance during the COVID-19 pandemic. For these firms, the negative relationship between stock performance, as well as financial performance, and their main driving factors, is lower during the COVID-19 pandemic. Among these factors, we identify the lockdown announcement, quantitative easing announcement, and the intensity of news media coverage of the company. These results tend to indicate that the quantity of ESG data reported by firms can contribute to mitigating the impact of the COVID-19 pandemic on stock performance volatility and financial performance. © 2023 Journal of Innovation Economics and Management. All rights reserved.
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The COVID-19 crisis battered the Japanese economy. The purpose of this paper is to investigate whether the pandemic has left scars. To this end, it employs out-of-sample forecasting models and detailed stock market data for 30 sectors and disaggregated current account data for the 3 years after the first case occurred. The findings indicate that stock prices in sectors such as tourism, education, and cosmetics remain far below forecasted values after three years. Office equipment and semiconductor stock prices initially fell more than predicted but have since recovered. Other sectors such as bicycle parts and home appliances gained at first but are now performing as expected. Sectors such as home delivery and electronic entertainment continue to outperform. The results also indicate that income flows from Japanese investments abroad are much larger than forecasted, keeping the Japanese current account in surplus even as imports of oil and commodities have created persistent trade deficits. Since the travails of hard-hit sectors such as tourism reflect their exposure to the COVID-19 pandemic rather than bad choices made by firms, policymakers should consider employing cost-effective ways to stimulate economic activity in these sectors. © 2023 by the author.
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The aim of the present research is to highlight whether there exist any diversification opportunities from investing in developed and developing countries' Shariah-compliant and non-Shariah-compliant stock markets during global financial crisis (GFC) and the COVID-19 pandemic periods. For this purpose, we employ daily data for both Shariah and non-Shariah indices from 29 October 2007 to 31 December 2021. The study uses multivariate GARCH-DCC and wavelet approaches to examine if there exist diversification opportunities in the selected markets. Evidence from this study shows that although the developing markets' stock returns experience high volatility of a similar degree, the conventional indices of Malaysia have the highest volatility among them. This shows that Shariah indices have less exposure to risk and higher possibilities of diversification compared to their conventional counterparts. Regarding developed markets, the Japanese conventional index and the U.S. Shariah indices are more volatile compared to other indices in the market. Moreover, the results of the wavelet power spectrum show significant and higher volatility during the COVID-19 pandemic rather than the GFC. Similarly, the Chinese conventional market experienced minimum variance during the GFC and COVID-19 pandemic period. On the other hand, the results of wavelet-coherence transform indicate that the Japanese Shariah-based market offered better portfolio opportunities for U.S. traders during the GFC and the COVID-19 pandemic periods. Hence, opportunities for investment in this selected market are basically close to zero. Therefore, investors should carefully choose which stocks they can include in their investment portfolio. © 2023 by the authors.
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This paper investigates the dynamics and drivers of informational inefficiency in the Bitcoin futures market. To quantify the adaptive pattern of informational inefficiency, we leverage two groups of statistics which measure long memory and fractal dimension to construct a global-local market inefficiency index. Our findings validate the adaptive market hypothesis, and the global and local inefficiency exhibits different patterns and contributions. Regarding the driving factors of the time-varying inefficiency, our results suggest that trading activity of retailers (hedgers) increases (decreases) informational inefficiency. Compared to hedgers and retailers, the role played by speculators is more likely to be affected by the COVID-19 crisis. Extremely bullish and bearish investor sentiment has more significant impact on the local inefficiency. Arbitrage potential, funding liquidity, and the pandemic exert impacts on the global and local inefficiency differently. No significant evidence is found for market liquidity and policy uncertainty related to cryptocurrency.
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With the outbreak of COVID-19, the Chinese government implemented the "zero-COVID” policy as a measure to curb the spread of the virus. The different measures of the policy include widespread testing, contact tracing, and strict quarantine and isolation protocols. In view of recent changes in COVID-19 trends and other economic indicators, the Chinese government withdrew significant provisions of the zero-COVID policy in China. The present study investigates the sectoral performance of the Chinese stock market after the withdrawal of the zero-COVID policy. The study considers eighteen sectoral indices of the Shenzhen Stock Exchange of China as a sample and applies the event study methodology to study the impact of the policy withdrawal on the stock prices performance. The results of the study indicate that sectors such as hotel, consumer staples, the financial sector, real estate, media, and culture have reported significant positive movement after the withdrawal of the zero-COVID policy, while other sectors such as consumer discretionary, energy, healthcare, information technology, manufacturing, mining, technology, telecom, transportation, utilities, wholesale, and retail have shown insignificant reactions. These results also indicate that when the COVID-19 outbreak happened in China, different sectors of the economy reacted negatively except the retail and wholesale sectors, while with the withdrawal of the zero-COVID policy by the Chinese government, the reaction of investors is optimistic as different sectors are reporting either positive reactions in the stock price movement or no reaction. © Prashant Sharma, Surender Kumar, 2023.
ABSTRACT
Purpose: The present study aims to test the Quadratic Programming model for Optimal Portfolio selection empirically. Need for the Study: All the investors who buy financial products are motivated to obtain higher profits or, in other words, to maximise their returns. However, the high returns are often accompanied by higher risks, and avoiding such risks has become the primary concern for all investors. There is a great need for such a model to maximise profits and minimise risk, which can help design an investment portfolio with minimum risk and maximum return. The Quadratic Programming model is one such model which can be applied for selected shares to build an optimised portfolio. Methodology: This study optimises the stock samples using a two-level screening of correlation coefficient and coefficient of variation. The monthly closing prices of the NSE-listed Indian pharmaceutical stocks from December 2019 to January 2022 have been used as sample data. The Lagrange Multiplier method is used to apply the model to achieve the optimal portfolio solution. Based on the market reality, the transaction costs have also been considered. The Quadratic programming model is further optimised to achieve the optimal portfolio for the select stocks. Findings: The traditional portfolio theory and the modified quadratic model gives similar and consistent results. In other words, the modified quadratic model asserts the accuracy of the conventional portfolio model. The portfolio constructed in the present study gives a return much higher than the return of the benchmark portfolio of Nifty Fifty, indicating the usefulness of applying the Quadratic Programming model. Practical Implications: The construction of an optimal portfolio using the traditional or modified Quadratic model can help investors make rational investment decisions for better returns with lower risks. © 2023 by Chetna and Dhiraj Sharma.
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This paper examines the presence of a contagion effect between Chinese and G20 stock markets as well as its intensity over a recent period from 1(st) January 2013 to 7 April 2022. The empirical study is conducted using the time-varying copula approach. The obtained results show strong evidence of a contagion effect between China and all countries except United States America, Argentina and Turkey during the COVID-19 period. In particular, the Chinese stock market exhibits the highest level of dependence with the Asian and European stock markets in addition to the greatest variability in dependence. These findings are interesting and have important implications for several financial applications.
ABSTRACT
Covid-19 salgınının ortaya çıkmasından sonra dünya çapında ekonomik çalkantılar ve şiddetli piyasa düşüşlerinin ortaya çıktığı görülmüştür. Bu dönemde hisse senedi piyasalarına yatırım yapmış ajanlar için hedge ve/veya güvenli liman araçları arayışları artmıştır. Kripto paralar ve altın özellikle gelişmekte olan ülke piyasalarındaki yatırımcılar için hedge ve/veya güvenli liman olma konusunda iyi potansiyellere sahiptir. Bu çalışmada, Borsa Ístanbul için Bitcoin, Etherium, Ripple, Litecoin ve altın piyasalarının hedge ve/veya güvenli liman piyasalar olup olmadığı, GARCH(1,1) hata terimleri varsayımı altında modellenmiş regresyon sistemi yardımı ile araştırılmıştır. Analizlerde örneklem olarak 4 Eylül 2017 – 30 Mart 2022 tarihleri arasındaki günlük frekanslı verilerden faydalanılmıştır. Ayrıca, Covid-19 salgın dönemi etkilerini ayrıştırmak için örneklem iki alt gruba ayrılmış ve tahminler Covid-19 öncesi dönem (31 Aralık 2019 öncesi) ve Covid-19 dönemi (31 Aralık 2019 ve sonrası) için ayrı ayrı analiz edilmiştir.A.B.D. doları cinsinden elde edilmiş kripto para (BTC, ETH, XRP, LTC), altın ve BÍST100 endeks getirileri kullanılarak bulunan tahmin sonuçlarına göre, tüm örneklem için Litecoin zayıf güvenli liman olarak ortaya çıkarken, Covid-19 öncesi dönemde Bitcoin ve Etherium zayıf hedge, Covid-19 salgın döneminde de Etherium zayıf güvenli liman olma özellikleri göstermektedir. Tüm örneklem ve salgın öncesi dönem verileri söz konusu olduğunda, BÍST100 endeks getiri dağılımının %10 çeyrek değerinden az olduğu durumlarda Bitcoin, Etherium ve Ripple güvenli liman piyasalar olarak gözlemlenirken, salgın döneminde altın, BÍST100 endeks getiri dağılımının %1 çeyrek değerinden az olduğu durumlarda güvenli bir liman olarak ortaya çıkmıştır. Fakat tüm analizlere dayanarak, altının genel görünümüyle BÍST100 endeksi için hedge veya güvenli limandan çok bir çeşitlendirici varlık olarak öne çıktığı söylenebilir.Alternate :After the Covid-19 outbreak, economic turmoil and severe market crashes have been observed around the world. During this crisis period, cyriptocurrencies and gold have become potentially good hedge and/or safe haven assets for especially the stock investors in emerging markets. This study investigates whether or not Bitcoin, Etherium, Ripple, Litecoin and gold markets have hedge and/or safe-haven properties for Borsa Ístanbul through a regression system modeled under the assumption of GARCH(1,1) error terms. Daily frequency data covering the period September 4, 2017 through March 30, 2022 is used in the sample analysis. In addition, to separate out the effects of the Covid-19 pandemic on the analysis, full sample is divided into two subgroups and the estimations are made separately for the pre-Covid-19 period (before 31 December 2019) and the Covid-19 period (31 December 2019 and later).According to the estimation results, Litecoin emerges as a weak safe haven for Borsa Ístanbul over the entire sample period, while Bitcoin and Etherium appear to be weak hedges in the pre-pandemic period. During the Covid-19 pandemic period, Etherium is shown to be a weak safe haven for the BÍST100 index. Full sample and pre-pandemic data analysis reveal that, Bitcoin, Etherium and Ripple act as safe-haven markets in some cases when the BÍST100 index returns hit lower than their 10% quantile value. After the outburst of the Covid-19 however, gold seems to act as a safe haven asset for Borsa Ístanbul when the BÍST100 index returns hit lower than their 1% quantile value. Based on the overall estimation results, gold stands out as a diversifier rather than a hedge and/or a safe haven asset for the BÍST100 index.
ABSTRACT
This paper examines the dynamics of volatility spillovers among five major tourism stock indices during the Covid-19 period. Our paper enriches the current literature as it is the first paper to investigate the volatility spillovers among major global tourism stock indices by adopting Diebold and Yilmaz (2012. Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57–66. ), and Barunik and Krehlik (2018. Measuring the Frequency Dynamics of Financial Connectedness and Systemic Risk. Journal of Financial Econometrics, 16(2), 271–296.) time and frequency domain methods. Results suggest that total spillovers of the tourism stock indices rose significantly during the pandemic. Turkey and Italy are net volatility spillover transmitters, and others are net volatility spillover receivers. Findings of this study also indicates that the effect of volatility transmission among tourism stock markets is temporary (short-lasting). The results suggest that short-term investors and portfolio managers should avoid investing in the tourism indices in the short term.