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Constructing a positive sentiment index for COVID-19: Evidence from G20 stock markets
Abstract
The present study investigates the degree of market responses through the scope of investors' sentiment during the COVID-19 pandemic across G20 markets by constructing a novel positive search volume index for COVID-19 (COVID19⁺). Our key findings, obtained using a Panel-GARCH model, indicate that an increased COVID19⁺ index suggests that investors decrease their COVID-19 related crisis sentiment by escalating their Google searches for positively associated COVID-19 related keywords. Specifically, we explore the predictive power of the newly constructed index on stock returns and volatility. According to our findings, investor sentiment positively (negatively) predicts the stock return (volatility) during the COVID-19. This is the first study assessing global sentiment by proposing a novel proxy and its impacts on the G20 equity market.
... Economic recovery continues at the national and international levels. The organization of the G20 contributes to this effort (Alqahtani et al., 2021;Anastasiou et al., 2022;Berawi, 2022). The successful implementation of the G20 summit conducted in Bali on November 15-16, 2022, positively impacted the stock performance of LQ45 companies. ...
... The three main priority issues in implementing the G20, namely global health architecture, digital transformation, and sustainable energy transition, can create a positive sentiment for related sectors (Kirton, 2020). These sectors can potentially conduct initial public offerings (Anastasiou et al., 2022). ...
... Moreover, the variable that affects participation in the LQ45 stock price in this model, Indonesia's G20 presidency, is treated as an independent variable that affects the LQ45 stock price (Anastasiou et al., 2022;Berawi, 2022;Larionova, 2023). Previous estimates suggest that the INDG20 is not fully exogenous and requires robustness testing with the two-step SYS-GMM test to address the endogeneity issues in the model (Arellano & Bond, 1991;Arellano & Bover, 1995;Blundell & Bond, 1998;Wuri et al., 2023). ...
This study investigates the role of Indonesia’s G20 presidency and exchange rates on the stock prices of LQ45. Daily data were collected from companies listed on Indonesia’s stock exchanges between November 15 and December 24, 2022. Furthermore, we employed a dynamic panel model approach, specifically the system generalized method of moments regression. This analytical technique controls for unobserved heterogeneity, simultaneity, and dynamic endogeneity. The results illustrate that Indonesia’s G20 presidency positively impacts the stock prices in LQ45. In addition, Exchange rate negatively influences on the LQ45 stock prices, and the stock prices of LQ45 in the previous year often correspond to that in the current year. This study’s results provide recommendations for potential investors who wish to invest in the subsectors of LQ45 member companies. The policies implemented during Indonesia's G20 presidency can increase stock prices and create positive market sentiment to encourage migration flows. Additional studies are required to determine the impact of implementing the G20 priority agenda, which includes enhancing the global health framework, fostering employment prospects, transitioning to green and renewable energy, and advancing the digital economy to increase stock prices.
... The BCI is a diffusion indicator varying from 0 to 100 (CNI, 2020). Anastasiou et al. (2022) point out that the diffusion indicators are measures of moving base so that the indicator itself presents the sample confidence levels. Potrich et al. (2015) and Barbosa and Nogueira (2018) highlight the relation of the BCI with the macroeconomic variables. ...
... The variation of new COVID-19 cases and new COVID-19 deaths are statistically significant and present a negative coefficient (À4.03199750) and (À2.43517710) respectively, confirming the work presented by Anastasiou et al. (2022) in which exogenous shocks, such as the COVID-19 pandemic negatively affect the confidence indices. ...
... The results are consistent with the work of previous research presented bySilber (2020), Miklian and Hoelscher (2021), Garretsen et al. (2022) and Anastasiou et al. (2022), reinforcing the fact that exogenous factors, such as pandemics and financial crises negatively influence the investorsconfidence level, in this specific study, the ICEI. ...
Purpose
In the context of investment decisions, the intricate interplay between exogenous shocks and their influence on investor confidence significantly shapes their behaviors and, consequently, their outcomes. Investment decisions are influenced by uncertainties, exogenous shocks as well as the sentiments and confidence of investors, factors typically overlooked by decision-makers. This study will meticulously examine these multifaceted influences and discern their intricate hierarchical nuances in the sentiments of industrial entrepreneurs during the COVID-19 pandemic.
Design/methodology/approach
Employing the robust framework of the generalized linear latent and mixed models (GLLAMM), this research will thoroughly investigate individual and group idiosyncrasies present in diverse data compilations. Additionally, it will delve deeply into the exogeneity of disturbances across different sectors and regions.
Findings
Relevant insights gleaned from this research elucidate the adverse influence of exogenous forces, including pandemics and financial crises, on the confidence of industrial entrepreneurs. Furthermore, a significant discovery emerges in the regional analysis, revealing a notable homogeneity in the propagation patterns of industrial entrepreneurs' perceptions within the sectoral and regional context. This finding suggests a mitigation of regional effects in situations of global exogenous shocks.
Originality/value
Within the realm of academic inquiry, this study offers an innovative perspective in unveiling the intricate interaction between external shocks and their significant impacts on the sentiment of industrial entrepreneurs. Furthermore, the utilization of the robust GLLAMM captures the hierarchical dimension of this relationship, enhancing the precision of analyses. This approach provides a significant impetus for data-informed strategic directions.
... The financial markets literature on the Covid-19 pandemic ascribes considerable significance to the investor sentiment channel (Chundakkadan & Nedumparambil, 2021;Huynh et al., 2021;Smales, 2021;Sun et al., 2021). Most of these studies employ the novel Google search volume index (GSVI) measure as a proxy of retail investor sentiment (Anastasiou et al., 2022;Chundakkadan & Nedumparambil, 2021;Huynh et al., 2021;Smales, 2021). These studies suggest that the most prominent keywords based on the search volume interest include "Coronavirus" and 'Covid-19". ...
... There is ample empirical evidence in the "Behavioral Finance Literature" that investor sentiment is a contrarian predictor of time series of cross-sectional returns (Andrei & Hasler, 2014;Baker et al., 2012;Stambaugh et al., 2014;Yu & Yuan, 2011). More recently, after the Covid-19 pandemic, this strand of literature has witnessed considerable attention from academics and practitioners (Ali et al., 2020;Anastasiou et al., 2022;Corbet et al., 2020;Huynh et al., 2021). The majority of these studies document market anomalies and security price behavior that does not conform to the postulations of the "Efficient Market Hypothesis" of Eugene Fama (Fama, 1970(Fama, , 1991(Fama, , 1998. ...
... In this backdrop, very few studies examine the impact of the global component of investor sentiment on international stock market returns (Anastasiou et al., 2022;Baker et al., 2012;Fraiberger et al., 2021;Han & Li, 2017;Wu et al., 2017). Most of these studies highlight that measurement of this global component of sentiment is difficult and ascribe this to the unavailability of appropriate international sentiment proxies (Baker et al., 2012;Baker & Wurgler, 2007). ...
We examine the impact of the global component of sentiment on the price return and volatility of 25 major futures market indices across the globe, during the Covid-19 pandemic. The global component of sentiment causes investor overreactions. These overreactions accelerate the fall in prices and contribute to the rising volatility levels. The futures prices revert, though gradually, to their fundamental values as information from more reliable sources becomes available. This leads to price recovery and lower volatility levels.
... There is no empirical research on the reasons for strengthening this rising. However, [11] documented that the strengthening of the economy occurred after the announcement of the success of the COVID-19 vaccine in mid-November 2021. ...
... Numerous studies on the impact of investor attitude on stock returns have been conducted in various countries, including Indonesia ( [4,11,[20][21][22][23]). However, research that discusses the relationship of causality between the two variables is rarely carried out [24]. ...
... This research is a development according to [25] by dividing investor sentiment into positive and negative [11]. The numerous keyword searches related to the COVID 19 pandemic that reflect the negative sentiment was successfully developed by [25] whereas a keyword search activity for vaccines that reflect the positive sentiment is developed by [11]. ...
... First, unlike relevant studies (e.g. Alomari et al. 2022;Anastasiou, Ballis, and Drakos 2022;Hsu and Tang 2022;Kamal and Wohar 2023) that focus on only a handful of predictors, we assess the explanatory power of a broad collection that involves 32 candidate variables capturing global health, economic, and financial developments. Included in this collection are dummy variables proxying for the potential volatility impact of crucial events (i.e. the stock market crash, the oil price war, US presidential elections, the COVID-19 vaccination campaign, the confirmation of the first US Omicron variant infection). ...
... This result agrees with those of Hsu and Tang (2022) who demonstrate that both positive and negative news pertaining to the pandemic affect the unexpected conditional volatility in major stock markets. Based on data from G20 economies, Anastasiou et al. (2022) document that positive investor sentiment, proxied by vaccine-related Google search queries, has a positive (negative) influence on market returns This table presents parameter selection results via the elastic net penalized regression. Blank entries denote variables whose coefficients are shrunk to zero. ...
This paper seeks to identify key variables contributing to sectoral stock market volatilities in the US under the enduring pressure of the COVID-19 pandemic, using a broad array of candidate factors. We adopt a Beta-Skew-t-EGARCH model to capture the time-varying dynamics of the individual sectoral return volatilities. The empirical analysis is performed via an elastic-net regularized regression model. We find that trading volume, volatility of broad US dollar exchange rates, coronavirus infection rates, VIX, Google search trends, US economic policy uncertainty, and the initiation of vaccination programmes are the most common determinants of sectoral volatility.
... Several studies examine the effect of specific events (crises and pandemics) related to investor's sentiment on financial markets, like crises (e.g., Anastasiou et al., 2022;Zouaoui et al., 2011), and pandemics (e.g., Anastasiou et al., 2022;Chatterjee and French, 2022;Hsu and Tang, 2022). Also, other studies reveal that wars tend to have a negative impact on stock markets, with studies demonstrating varying effects on different countries (e.g., Brune et al., 2015;Hudson and Urquhart, 2015;Schneider and Troeger, 2006). ...
... Several studies examine the effect of specific events (crises and pandemics) related to investor's sentiment on financial markets, like crises (e.g., Anastasiou et al., 2022;Zouaoui et al., 2011), and pandemics (e.g., Anastasiou et al., 2022;Chatterjee and French, 2022;Hsu and Tang, 2022). Also, other studies reveal that wars tend to have a negative impact on stock markets, with studies demonstrating varying effects on different countries (e.g., Brune et al., 2015;Hudson and Urquhart, 2015;Schneider and Troeger, 2006). ...
This study explores the impact of Russia-Ukraine war and sanctions news sentiments (RUWESsent) on global equity markets using three robust estimators. The quantile-on-quantile regression (QQR) results show that RUWESsent has heterogeneous effects on stock returns. The rolling window wavelet correlation (RWWC) indicates a time-varying influence on the G10 stock market. The results of the time–frequency quantile VAR (TF-QVAR) approach show a time-varying and heterogeneous connectedness. Moreover, RUWESsent acts as the net shock transmitter across extreme quantiles. These results give investors, regulators, and policymakers valuable insights into geopolitical events.
... First, both domestic and foreign investors speak English extensively. The majority of trading platforms utilize English, and Google search engines favor English keywords over other languages (Anastasiou et al., 2022;Wanidwaranan and Padungsaksawasdi, 2022). The process of choosing relevant search terms is arbitrary. ...
The current study investigates how the recent war between Ukraine and Russia impacted the volatility of G7 economies of the stock markets in major industrialized countries like United States (US), the United Kingdom (UK), Canada, Japan, France, Germany, and Italy. The paper applies EGRACH model to detect the influence of the war on stock markets volatility. EGRACH estimations revealed that there is a direct impact of the information content of the war on the volatility of the majority of the countries under study. More specifically, four countries are negatively influenced by the war, Canada, France, Germany and UK. While three countries are not affected by the news which are Japan, USA and Italy. Granger causality reveals that there is a unidirectional relationship between war news and stock indices of three economies which are Germany, France and Italy. However, other indices did not show any unidirectional relationship (Japan, USA, UK and Canada). To find out if there is a long-term association between indices and the information content of the war, co-integration test was employed. The results showed the long-term association between the two variables.
... The authors found that greater COVID-19-related investor sentiment is associated with higher stock market uncertainty. Anastasiou et al. (2022) explored the predictive power of a positive search volume index for COVID-19 (i.e., a proxy for investors' sentiment during the COVID-19 pandemic). They found that investor sentiment positively (negatively) predicts the stock return (volatility) during COVID-19. ...
This study investigates the impact of COVID‐19 infections and mobility restriction policies on stock market volatility. We estimate panel data models for seven countries using daily data from February 12, 2020 to April 14, 2021. Our results show that the number of new cases of COVID‐19 infections and the introduction of mobility restriction policies plays a crucial role in shaping stock market volatility during the pandemic. We found that new cases of COVID‐19 infections and mobility restrictions policies increase stock market jumps rather than increase continuous volatility. We also find that mobility restriction policies lessen the impact of new COVID‐19 cases on stock market volatility.
... Investors' sentiments. This study shows that COVID-19 pandemic information sharing significantly moderates the relationship between investors' sentiments and their investment decisions, validating that pandemic-related information, such as infection rates and economic downturns, heavily influences investors' sentiments and alters their risk perceptions (Anastasiou et al. 2022;Hsu and Tang 2022;Bin-Nashwan and Muneeza 2023;Gao et al. 2023;Sohail et al. 2020). ...
This study aims to investigate the impact of behavioral biases on investment decisions and the moderating role of COVID-19 pandemic information sharing. Furthermore, it highlights the significance of considering cognitive biases and sociodemographic factors in analyzing investor behavior and in designing agent-based models for market simulation. The findings reveal that these behavioral factors significantly positively affect investment decisions, aligning with prior research. The agent-based model’s outcomes indicate that younger, less experienced agents are more prone to herding behavior and perform worse in the simulation compared to their older, higher-income counterparts. In conclusion, the results offer valuable insights into the influence of behavioral biases and the moderating role of COVID-19 pandemic information sharing on investment decisions. Investors can leverage these insights to devise effective strategies that foster rational decision-making during crises, such as the COVID-19 pandemic.
... Their results suggest that GSSI has a positive relationship with sovereign risk. Recently, Anastasiou et al. (2022) developed a COVID-19 positive sentiment index using Google Trends data. Their results suggest there is a positive association between stock returns and sentiment but a negative one with stock volatility. ...
Stock price forecasting is a challenging task because financial time series are primarily nonlinear, noisy, and disordered systems that are complicated to forecast. Deep learning models show promise in this domain along with natural language processing, to extract relevant features from text data and map them to numerical representations. This study aims to forecast stock prices using text analysis and deep learning approaches and explain the models using explainable AI. We construct a World Halal Tourism Composite Sentiment Index (WHTCSI) using text analysis to forecast halal tourism stock price. The results suggest that Convolutional Neural Networks (CNN) outperform all other models. The results are robust when considering country-level data. In addition, model explanations show that the index contributes 35.55% to the forecasting model, indicating irrational investment activity and herding behavior in the halal tourism industry. The study’s findings have significant implications for investors, analysts, and portfolio managers in making investment decisions.
... Alnafea and Chebbi (2022) found that the possibility of a stock market crash is increased by investor sentiment and triggers future stock crashes. This study are the same as research conducted by Anastasiou et al. (2022) that found that Investor Sentiment has a negative and significant effect on crash risk. The sentiment coefficient in sentiment-sensitive sectors is negative, indicating an average reversal of the sentiment effect (Muguto et al., 2022). ...
This study evaluates the relationship investor sentiment, exchange rate volatility, net foreign portfolio investment and the country index crash risk. The moderating variable, net foreign portfolio investment, is introduced. While previous crash risk studies typically focus on individual firms, this study takes a country-level perspective. CRASH, NCSKEW and DUVOL represent the Country Index Crash risk. The data will be analyzed using EViews software, including panel data from logistic regression and OLS regression using a two-dimensional clustered standard error method. The findings demonstrate the importance of exchange rate fluctuations and investor mood in affecting the country index crash risk. The influence of Net Foreign Portfolio Investment on the crash risk is negligible. Moreover, the study reveals that higher Net Foreign Portfolio Investment does not strengthen the impact of Investor Sentiment but weakens its influence in conjunction with Exchange Rate Volatility on the country index crash risk.
... The author illustrates the relationship between the two kinds of data and the return behaviour of G20 overall market stocks. The data results show that COVID-19-related search terms with negative signs will bring more crisis sentiment to investors, while keywords with positive signs will do the opposite, meaning that G20 might have a higher return on the stock market (Anastasiou, Ballis, & Drakos, 2022). Zhang studying the daily case data of the first three months of COVID-19, a comparative analysis of the degree of infection in various countries is carried out through simple statistics. ...
... First, English is widely used by local and foreign investors. Google search algorithms prioritize English keywords over other languages, and most trading platforms use English (Anastasiou et al., 2022;Wanidwaranan & Padungsaksawasdi, 2022). The selection of appropriate search keywords is a subjective process. ...
The Russia-Ukraine military conflict, commencing on February 24, 2022, notably impacted the international community. This study aims to quantify the volatility engendered by the conflict, drawing from the analysis of stock market indices across 40 countries. Time-series returns data from January 1 to December 31, 2022, were examined utilizing EGARCH econometric models. The relationship between volatility and news regarding the conflict was analyzed through a vector autoregression model, and associations between variables were examined using the Granger causality test. Findings suggest that some markets proximate to Ukraine, notably in Hungary, Polassnd Poland, Serbia, Bosnia and Herzegovina, and the Czech Republic, reacted in anticipation of the conflict, days prior to February 24. Remote markets experienced comparatively lower volatility, along with the primary stock markets. Additionally, a decline in volatility was observed as war-related information became available. Notably, the period between March 2 and March 16, 2022, recorded the highest volatility in 21 countries. Conversely, the value markets of the US, China, Japan, the UK, and Germany navigated the analyzed period with lower volatilities. These results demonstrate that conflict shocks influence stock markets globally. The implications of these findings are significant for investors, decision-makers, portfolio managers, investment funds, and central banks.
... The author illustrates the relationship between the two kinds of data and the return behaviour of G20 overall market stocks. The data results show that Covid-19-related search terms with negative signs will bring more crisis sentiment to investors, while keywords with positive signs will do the opposite, meaning that G20 might have a higher return on the stock market [2]. Zhang studying the daily case data of the first three months of Covid-19, a comparative analysis of the degree of infection in various countries is carried out through simple statistics. ...
During the period of different changes in the global situation, the stock indexes of China, the United States and the United Kingdom all showed different trends. Overall, during the outbreak of the epidemic, they all received a huge impact, and due to the different policies and coping strategies of various countries, the follow-up performance also varies greatly. Brexit has only had a slight impact on the British domestic market in a short period time, and China and the United States have prepared for investment in the new market after Brexit, which has also caused the corresponding market index to perform better before the follow-up. Due to the differences in the main market targets and the differences in the geographical location of countries, the negative impact on the British market was more obvious during the Russia-Ukraine conflict, while the stock indexes of China and the United States were relatively stable and even showed an upward trend. It can be seen from the data analysis that the markets in different countries are affected by time differently. With the growing correlation between the markets of various countries, investors should pay more attention to the global situation and the policy orientation of different countries. Considering risk diversification while taking policy dividends helps to obtain stable returns.
... Third, we introduce a new Cryptocurrency Tail Risk Index (CTRI) that captures the risk exposure of cryptocurrency market, as a whole. In contrasts to the current cryptocurrency indexes based on the news coverage data (see, Trimborn and Härdle, 2018;Anastasiou et al., 2022;Lucey et al., 2022;Wang et al., 2022), our new index relies on the actual trading data which cushion the impact of speculative nature of media over the index movements. The CTRI index aims to support the delivery of risk-informed investment by green investors, investors, and policymakers who make investment decisions, primarily in the financial sector. ...
... To this end, we construct variables of interest used in the literature. First, we use changes in COVID-19 deaths and vaccination doses administered as a proxy for bad and good news about COVID-19, repsecitvely (Anastasiou et al., 2022;Iyer & Simkins, 2022;Liu et al., 2021;Subramaniam & Chakraborty, 2021). Second, as in the literature (Fatum & Hutchison, 1999;Fullana et al., 202 l;Kim & Stock, 2014;Wongswan, 2009), we also use the effective federal funds rate (EFFR) to proxy the monetary policy. ...
We examine how monetary policy of the Federal Reserve System, COVID-19 mortality cases, and vaccinations are associated with the US stock market volatility during the pandemic period. Using the wavelet coherence analysis, we first find that there is a positive relationship between the volatility and death tolls. Second, while in the short term the sizable interest rate cut causes market instability, in the intermediate term it stabilizes the market. Third, vaccinations and the volatility have a negative relationship. Finally, the monetary policy and the volatility have much stronger coherency than the vaccination and the movements. These findings are consistent with panel regression results. Specifically, we find that the systemic COVID-19 shock in the US stock market is alleviated by an increase in the number of COVID-19 vaccination doses administered and a low and stable change in the effective federal funds rate. Furthermore, our results show that the monetary policy influences the stock market volatility significantly more than the vaccination, regardless of firm size and industry type. Thus, this study helps policymakers cope with possible systemic shocks from other infectious diseases, considering the magnitude of monetary and health policy and their short/intermediate/long-term lagging effectiveness in reducing market volatility.
... Through various schemes, the government has begun to reduce social restrictions by accelerating the vaccine program so that the economy recovers quickly. Investor sentiment toward the pandemic has also started to wane along with the vaccine program (Anastasiou et al., 2022). Responding to the issue of climate change and increasing income, the government issued a tax reform policy by passing the Law on the Harmonization of Tax Regulations (UU HPP). ...
This study aims to examine the market reaction to tax reform. Tax reform was carried out by the government on the issue of post-covid economic recovery and responding to environmental changes. This policy has a new tax regulation policy in Indonesia in the form of a carbon tax, an increase in VAT, and an increase in income tax. This research is event study research. The population of this study is companies listed on the Indonesia Stock Exchange on October 7, 2021. The data are taken from Yahoo Finance, totalling 753 companies. The sampling method used is the purposive sampling method, with the sample in the form of the Kompas 100 index and each company sector listed on the Indonesia Stock Exchange with a total of 9 sectors with an observation period of 10 days, 5 days, and 3 days before and after the ratification (-10.10), (-5.5), and (-3.3). The market reacted to the tax reform, and there was a significant abnormal return (p-value <0.05). Companies in the agricultural and mining sectors are companies that are of interest to investors. In contrast, companies in the financial, trade, services, and investment sectors are not attractive to investors with negative cumulative abnormal returns.
... They found that investor sentiments in 17 countries showed a strong correlation, and the feverish sentiment index can positively predict the stock volatility of several countries. Recently, Anastasiou et al. (2022) constructed a novel positive search volume index for COVID-19 (COVID19 +) and found that the rise of COVID-19 + could reduce investors' crisis sentiment and ease stock market volatility. Therefore, because of the COVID-19 outbreak, our study divides the sample into pre-and post-pandemic subsamples and examines whether there are any differences in the impacts of the two investor sentiment proxies on volatilities in different periods. ...
The effect of investor sentiment on stock volatility is a highly attractive research question in both the academic field and the real financial industry. With the proposal of China's "dual carbon" target, green stocks have gradually become an essential branch of Chinese stock markets. Focusing on 106 stocks from the new energy, environmental protection, and carbon–neutral sectors, we construct two investor sentiment proxies using Internet text and stock trading data, respectively. The Internet sentiment is based on posts from Eastmoney Guba, and the trading sentiment comes from a variety of trading indicators. In addition, we divide the realized volatility into continuous and jump parts, and then investigate the effects of investor sentiment on different types of volatilities. Our empirical findings show that both sentiment indices impose significant positive impacts on realized, continuous, and jump volatilities, where trading sentiment is the main factor. We further explore the mediating effect of information asymmetry, measured by the volume-synchronized probability of informed trading (VPIN), on the path of investor sentiment affecting stock volatility. It is evidenced that investor sentiments are positively correlated with the VPIN, and they can affect volatilities through the VPIN. We then divide the total sample around the coronavirus disease 2019 (COVID-19) pandemic. The empirical results reveal that the market volatility after the COVID-19 pandemic is more susceptible to investor sentiments, especially to Internet sentiment. Our study is of great significance for maintaining the stability of green stock markets and reducing market volatility.
... Second, while the relationship between consumer confidence and tourism has been established in previous studies (e.g., Crotts et al., 1993;Turner and Witt 2001;Gholipour and Tajaddini 2018), the link between businesswise confidence indicators and international tourist arrivals has received relatively little research attention in the tourism literature (Guizzardi and Stacchini, 2015). Finally, we add on the growing research of how non-fundamental variables, such as sentiment, expectations and/or business confidence, affect general aspects of the economic environment (see among others, Kulendran and Witt, 2003;Baker and Wurgler, 2006;Guizzardi and Stacchini 2015;Alaei et al., 2019;Fu et al., 2019;Anastasiou and Katsafados, 2020;Hao et al., 2020;Anastasiou and Drakos, 2021;Letdin et al., 2021;Anastasiou et al., 2022a;Anastasiou et al., 2022b). ...
We introduce a novel tourism-specific business expectations sentiment index and explore whether it can operate as a leading indicator for international tourist arrivals in Greece. Using monthly data spanning 2002-2021 and employing a VAR model, we document that this newly introduced tourism-specific business sentiment serves as a leading indicator, whose higher levels foreshadow increased demand for international travel. We also find that its inclusion in a tourism-oriented model increases forecasting accuracy, which can be utilized by travel agent businesses, local government officials and policymakers in their efforts to predict tourist arrivals in Greece.
Purpose
Although the effects of both news sentiment and expectations on price in financial markets have now been extensively demonstrated, the jointness that these predictors can have in their effects on price has not been well-defined. Investigating causal ordering in their effects on price can further our understanding of both direct and indirect effects in their relationship to market price.
Design/methodology/approach
We use autoregressive distributed lag (ARDL) methodology to examine the relationship between agent expectations and news sentiment in predicting price in a financial market. The ARDL estimation is supplemented by Grainger causality testing.
Findings
In the ARDL models we implement, measures of expectations and news sentiment and their lags were confirmed to be significantly related to market price in separate estimates. Our results further indicate that in models of relationships between these predictors, news sentiment is a significant predictor of agent expectations, but agent expectations are not significant predictors of news sentiment. Granger-causality estimates confirmed the causal inferences from ARDL results.
Research limitations/implications
Taken together, the results extend our understanding of the dynamics of expectations and sentiment as exogenous information sources that relate to price in financial markets. They suggest that the extensively cited predictor of news sentiment can have both a direct effect on market price and an indirect effect on price through agent expectations.
Practical implications
Even traditional financial management firms now commonly track behavioral measures of expectations and market sentiment. More complete understanding of the relationship between these predictors of market price can further their representation in predictive models.
Originality/value
This article extends the frequently reported bivariate relationship of expectations and sentiment to market price to examine jointness in the relationship between these variables in predicting price. Inference from ARDL estimates is supported by Grainger-causality estimates.
Subject. This article examines the relationship between the sentiment caused by the news on the CoinTelegragh professional forum and the changes in Bitcoin, Litecoin and Ethereum cryptocurrencies. Objectives. The article aims to assess the impact of the sentiment of various Internet publications on the volatility of cryptocurrencies, as well as the predictive power of Google Trends and the VIX Index for cryptocurrencies. Methods. For the study, we used the cross-quantilogram method and the VADER sentiment analysis model. Results. The article finds that the Google Trends Index in a short period of one to three days can be used to predict the closing prices of Bitcoin, Litecoin, and Ethereum, while the VIX Index (Stock Market Uncertainty) has no relationship with the cryptocurrency market. This means that cryptocurrencies can be used as a safe-haven asset when the background market is highly volatile. Conclusions. The crypto market has a complex sentiment component, with its prices and trading activity determined by popularity, emotion, and sentiment. The findings confirm previous studies, which claim that during the period of prevalence of negative news and publications, the crypto market gets narrowed, the trading volume drops off, and the interest of Internet users gets low to a minimum. The euphoria in the market, on the contrary, attracts new unqualified investors, and this is confirmed by the number of views of basic information about cryptocurrencies on Wikipedia.
Economic and political disorders have multidimensional impacts on all economies around the world. The global world has faced out COVID-19 pandemic in 2020, and now the Russian-Ukraine geopolitical crisis. This study investigates the nexus among commodities, crypto, and G20 capital markets along with risk and returns implications. To examine the impact, we applied the TVPVAR technique suggested by Koop and Korobilis (2014), and Antonakakis, Chatziantoniou, and Gabauer (2020) by adjusting the framework of Diebold and Yilmaz (2012). The research findings reveal that a high level of connectedness was observed during Covid-19, which was persistent for a long period and has multidimensional impacts. More particularly, EU, Canada, France Germany, and the UK were the principal supplier of spillovers to other commodities, Bitcoin, and the remaining markets. During Geopolitical Crisis (here after GPC), conclusively it is observed that of USA, Brazil, Saudi Arabia, Canada, Mexico, China, Indonesia, and Japan are the net receivers of the volatility spillovers and Russia, Germany, France, European Union, Italy, UK, Argentina, India, Australia, Turkey, Korea, and South Africa are the net transmitters of volatility spillovers. Interestingly, among net transmitters Argentina, South Africa and Turkey are suffered from high inflation and substantial budget deficits, considered as weak economies of G20. Portfolio weights has been increased dramatically during COVID-19 and Russian-Ukraine war. This research could be utilized to take investment, hedging, and diversification decisions about commodities, cryptocurrencies, and stocks, particularly in such turmoil situations with the help of connectedness and various hedging techniques.
This study analyses existing literature about investor behavior around news an- nouncements. We use bibliometric analysis to explore the evolution and development in this theme. We analyze 815 research articles collected from Scopus database from 1992 to 2021 through bibliometric measurements and social networks using Vosviewer. We Önd that the number of studies examining investor behavior in response to news announcements has been steadily increasing over time, particularly since 2008. Further, the study highlighted ináuential authors, countries, institutions, impactful journals, and top articles in this theme. To identify the research gap to propose agenda for future research, the study conducted clustering and factor analysis of main studies and themes in this literature. Majority of the studies has focused on the impact of news announcements on stock market and individual investor sentiment, particularly herd behavior of investors. Even though many researchers tried to investigate di§erent aspects of investor behavior around corporate and macroeco- nomic news announcements, to the best of our knowledge, no studies have been conducted to evaluate the performance and trends in this theme. This study signiÖcantly contributes to the Önancial literature dedicated to news announcements by analyzing the trend and pattern of publication in this theme and helping researchers and other participants in the Önancial market to get insight in this theme and to conduct future studies
In this study, we construct an investor sentiment indicator (SsPCA) to predict stock volatility in the Chinese stock market by applying the scaled principal component analysis (sPCA). As a new dimension reduction technique for supervised learning, sPCA is employed to extract useful information from six individual sentiment proxies and obtain the common variations to characterize the investor sentiment (SsPCA). The empirical results indicate that SsPCA is a significant and powerful volatility predictor both in and out of sample. We also employ the partial least squares (PLS)-based investor sentiment index, three extra sentiment measures in past studies, and six individual sentiment proxies for comparison, and find SsPCA outperforms them on predicting stock volatility in the Chinese stock market. More importantly, the predictability of SsPCA remains significant before and after the famous financial crises (the sub-prime mortgage crisis and Chinese stock market turbulence) and the spread of the pandemic (COVID-19). Additionally, our findings imply that SsPCA still plays an essential role in predicting sock volatility after considering the leverage effect. The robustness of SsPCA in volatility forecasting is further verified in various industry indices of the Chinese stock market. Finally, we state that the strong predictability of SsPCA is highly related to its dimensionality reduction. Our results indicate that SsPCA is a robust volatility predictor from various aspects and performs better compared with existing sentiment indicators.
This paper investigates the effect of media-talk on financial markets in response to COVID-19 news published by the Wall Street Journal (WSJ). Collecting data from the United States Centers for Disease Control and Prevention Center (CDC), we investigate the effect of WSJ's coverage and stress tone on stock markets. Also, we attempt to measure a media hype that compares the number of stress words to the number of cases. We document three main findings. First, news coverage raises information in financial markets, increasing returns and reducing risk, but excessive information leads to high uncertainty. Second, increased use of the stress tone leads to negative returns and increased expected risk to investors. Third, the overstatement of the pandemic by WSJ negatively affects financial markets. Overall, we find that investors seem to be more affected by long periods of high-stress sentiment and uncertainty than single-day news.
We use daily data of the Google search engine volume index (GSVI) to capture the pandemic uncertainty and examine its effect on stock market activity (return, volatility, and illiquidity) of major world economies while controlling the effect of the Financial and Economic Attitudes Revealed by Search (FEARS) sentiment index. We use a time-frequency based wavelet approach comprising wavelet coherence and phase difference for our empirical assessment. During the early spread of the COVID-19, our results suggest that pandemic uncertainty, and FEARS sentiment strongly co-move, and increased pandemic uncertainty leads to pessimistic investor sentiment. Furthermore, our partial wavelet analysis results indicate a synchronization relationship between pandemic uncertainty and stock market activities across G7 countries and the world market. Our results are robust to the inclusion of alternative pandemic fear measure in the form of equity market volatility infectious disease tracker. The pandemic uncertainty and associated sentiment implications could be one plausible reason for increased volatility and illiquidity in the market, and hence, policymakers should look upon this issue for the financial market stability perspective.
Using textual analysis we study the relationship between social media sentiments and stock markets during the COVID-19 pandemic. Our analysis is based on a sample of 1,616,007 tweets over the period January to June 2021 for seven countries. We process the tweets via the VADER analyzer thereby producing both positive and negative sentiment measures. Particularly, we prove that higher positivism is associated with a short-term increase in stock prices. On the other side, negativism relates inversely to stock prices with long-term impact, in the case of English spoken countries. Notably, our results remain robust to the inclusion of various control variables, including virtual fear and Google vaccine indexes. Finally, we prove that positivism is associated with higher returns and lower volatility in the short-run, while negativism is linked with lower returns in the short run.
We investigate whether economic sentiment exerts an impact on firms' decision to apply for a bank loan or not and hence its impact on discouragement prevalence. Using survey data for Eurozone firms and employing a Probit Heckman selection model, we document that a positive shock in economic sentiment lowers the percentage of discouraged bank borrowers in the economy. In contrast, higher economic sentiment shock volatility leads to an increase in discouragement.
We investigate the impact of sentimental shocks on house price fluctuations in the Euro area. To this end, we isolate and measure non-fundamental-based sentimental shocks by employing survey-based indicators that proxy four key types of expectations of housing market participants. The novelty of our study is that specific sentimental shocks are identified through four uncertainty transmission channels in the real estate market (i.e., the precautionary savings channel, the credit supply channel, the credit demand, and the inflationary channel). We provide strong evidence that sentimental shocks drive fluctuations in house prices even in the absence of any changes in aggregate fundamentals. Finally, we find that these results are more pronounced in the peripheral Euro area countries. The finding that the real estate market is also governed by irrational behavior implies that both governments and policymakers should consider sentimental shocks when they form their real estate market policies or take actions to stabilize and improve the proper function of the European housing market.
The COVID-19 global pandemic has disrupted business-as-usual, hence, affecting sustained economic development across countries. However, it appears economic uncertainty following COVID-19 containment measures favor market signals of cryptocurrencies. Here, this study empirically and structurally investigates the implication of COVID-19 health outcomes on market prices of Bitcoin, Bitcoin Cash, Ethereum, and Litecoin. Evidence from the novel Romano-Wolf multiple hypotheses reveal COVID-19 shocks spur Litecoin by 3.20-3.84%, Bitcoin by 2.71-3.27%, Ethereum by 1.43-1.75%, and Bitcoin Cash by 1.34-1.62%.
Employing monthly search volume data on crisis-related queries from the Google Trends database, we introduce two modified Google search-based crisis sentiment indicators as measures of depositors’ fear. These indices capture depositors’ crisis sentiment, and they are found to be significant drivers of bank deposits flows across European Union countries. Our findings indicate that countries for which the search intensity of crisis-related keywords is high, they tend to witness bank deposit outflows. By employing a Panel Vector Autoregressive approach, we document the robustness of our findings. Our findings suggest that policy makers should incorporate depositors’ fear in their macroprudential policies as predictor of bank insolvency.
We investigate the impact of Covid-19 on stock markets across G7 countries and their business sectors. We highlight the synchronicity and severity of this unprecedented crisis. We find strong transition evidence to a crisis regime in all countries and sectors, yet crisis intensity and timings vary. The Health Care and Consumer services sectors were the most severely affected; a reflection of the Covid-19 drug-race and international travel restrictions. The Technology sector was hit the latest and least severely, as imposed lockdown measures forced people to explore various web-based entertainment and distraction options. Country-wise the UK and the US were the most affected with the highest heterogeneity in their business sectors' response; a possible reflection of the ambiguity in the initial response and adoption of lockdown measures. Financial markets' response to Covid-19 is akin to response in previous financial crisis rather than previous pandemics. A series of robustness checks confirms our findings.
We examine the effect of crisis sentiment on cryptocurrencies’ price crash risk. We show that cryptocurrencies’ price crash risk is positively related to the FEARS index, indicating that a higher crisis sentiment by investors increases cryptocurrencies’ price crash risk. Our findings advance the understanding of the consequences of investor sentiment on the cryptocurrency market.
We construct a new newspaper-based sentiment indicator for Spain that allows to monitor economic activity in real-time. As opposed to survey-based confidence indicators that are released at the end of the month, our indicator can be constructed on a daily basis. We compare our index with the popular Economic Sentiment Indicator of the European Commission and show that ours performs significantly better in nowcasting the Spanish GDP. Moreover, it proves to be helpful to predict the current COVID-19 recession from an earlier date.
We study an equilibrium risk and return model to explore the effects of the coronavirus crisis and associated skewness on the market price of risk. We derive the moment and equilibrium equations, specifying skewness price of risk as an additive component of the effect of variance on mean ex-pected return. We estimate our model using the flexible skewed generalized error distribution, for which we derive the distribution of returns and the likelihood function. Using S&P 500 Index re-turns from January 1980 to mid-October 2020, our results show that the coronavirus crisis generat-ed a deeply negative reaction in the skewness and total market price of risk, more negative even than the subprime and the October 1987 crises.
We examine the U.S. stock market reaction to the World Health Organization's announcement declaring COVID-19 a global health emergency, with a focus on firms' international exposure. We find that while international exposure through foreign sales, foreign assets, imports and exports are significant and negatively associated with standardized cumulative abnormal returns in the short-run, the effect reverses in the long-run. In the longer run, internationalization contributes to multinational firms being more resilient to economic shocks caused by COVID-19.
The financial market response to the COVID-19 pandemic provides the first example of a market crash instigated by a health crisis. As such, the crisis provides a unique setting in which to examine the market response to changes in investor attention. We utilise Google search volume (GSV) as a proxy for investor attention. GSV for the “coronavirus” keyword increases markedly from late-February and peaks in mid-March before declining substantially. Our results are broadly consistent with Da, Engelberg, and Gao (2015), indicating that GSV is primarily a proxy for the attention of retail investors and confirming that investor attention negatively influences global stock returns during this crisis period. A rise in the number of internet searches during the COVID-19 crisis induces a faster rate of information flow into financial markets and so is also associated with higher volatility. The identified relationships are economically and statistically significant even after controlling for the number of COVID-19 cases and macroeconomic effects. Increases in GSV have less impact on government bond yields where the limited role of GSV is likely due to lower participation of retail investors. The results suggest that, rather than searching for information on potential stocks to buy (Barber & Odean, 2008), retail investors are searching for information to resolve uncertainty about household FEARS (Da et al., 2015) during the COVID-19 crisis.
Since the outbreak of the COVID-19 pandemic, stock markets around the world have experienced unprecedented declines amid high uncertainty. In this paper, we use Google search volume activity as a gauge of panic and fear. The chosen search terms are specific to the coronavirus crisis and correspond to phrases related to nonpharmaceutical intervention policies to fight physical contagion. We show that during this period, fear of the coronavirus – manifested as excess search volume – represents a timely and valuable data source for forecasting stock price variation around the world.
Using the financial data of listed Chinese companies, we study the impact of COVID-19 on corporate performance. We show that COVID-19 has a negative impact on firm performance. The negative impact of COVID-19 on firm performance is more pronounced when a firm’s investment scale or sales revenue is smaller. We show, in an additional analysis, that the negative impact of COVID-19 on firm performance is more pronounced in serious-impact areas and industries. These findings are among the first empirical evidence of the association between pandemic and firm performance.
We empirically investigate the effect of the official announcements regarding the COVID-19 new cases of infection and fatality ratio, on the financial markets volatility in the United States (US). We consider both COVID-19 global and US figures and show that the sanitary crisis enhances the S&P 500 realized volatility. Our findings are robust to different model specifications and suggest that the prolongation of the coronavirus pandemic is an important source of financial volatility, challenging the risk management activity.
This paper studies the impact of fear sentiment caused by the coronavirus pandemic on Bitcoin price dynamics. We construct a new proxy for coronavirus fear sentiment using hourly Google search queries on coronavirus-related words. The results show that market volatility has been exacerbated by fear sentiment as the result of an increase in search interest in coronavirus. Moreover, we find that negative Bitcoin returns and high trading volume can be explained by fear sentiment regarding the coronavirus. Our results also show that Bitcoin fails to act as a safe haven during the pandemic.
Do government interventions aimed at curbing the spread of COVID-19 affect stock market volatility? To answer this question, we explore the stringency of policy responses to the novel coronavirus pandemic in 67 countries around the world. We demonstrate that non-pharmaceutical interventions significantly increase equity market volatility. The effect is independent from the role of the coronavirus pandemic itself and is robust to many considerations. Furthermore, two types of actions that are usually applied chronologically particularly early—information campaigns and public event cancellations—are the major contributors to the growth of volatility.
Purpose
(1) A concern often expressed in relation to cryptocurrencies is the environmental impact associated with increasing energy consumption and mining pollution. Controversy remains regarding how environmental attention and public concerns adversely affect cryptocurrency prices. Therefore, the paper aims to introduce the index of cryptocurrency environmental attention (ICEA), which aims to capture the relative extent of media discussions surrounding the environmental impact of cryptocurrencies. (2) The impacts of cryptocurrency environmental attention on long-term macro-financial markets and economic development remain part of undeveloped research fields. Based on these factors, the paper will further examine the effects of the ICEA on financial markets or economic developments.
Design/methodology/approach
(1) The paper introduces a new index to capture cryptocurrency environmental attention in terms of the cryptocurrency response to major related events through gathering a large amount of news stories around cryptocurrency environmental concerns – i.e. >778.2 million news items from the LexisNexis News & Business database, which can be considered as Big Data – and analysing that rich dataset using variety of quantitative techniques. (2) The vector error correction model (VECM) and structural VECM (SVECM) [impulse response function (IRF), forecast error variance decomposition (FEVD) and historical decomposition (HD)] are useful for characterising the dynamic relationships between ICEA and aggregate economic activities.
Findings
(1) The paper has developed a new measure of attention to sustainability concerns of cryptocurrency markets' growth, ICEA. (2) ICEA has a significantly positive relationship with the UCRY indices, volatility index (VIX), Brent crude oil (BCO) and Bitcoin. (3) ICEA has a significantly negative relationship with the global economic policy uncertainty (GlobalEPU) and global temperature uncertainty (GTU). Moreover, ICEA has a significantly positive relationship with the industrial production (IP) in the short term, whilst having a significantly negative relationship in the long term. (4) The HD of the ICEA displays higher linkages between environmental attention, Bitcoin and UCRY indices around key events that significantly change the prices of digital assets.
Research limitations/implications
The ICEA is significant in the analysis of whether cryptocurrency markets are sustainable regarding energy consumption requirements and negative contributions to climate change. Understanding of the broader impacts of cryptocurrency environmental concerns on cryptocurrency market volatility, uncertainty and environmental sustainability should be considered and developed. Moreover, the paper aims to point out future research and policy legislation directions. Notably, the paper poses the question of how cryptocurrency can be made more sustainable and environmentally friendly and how governments' cryptocurrency policies can address the cryptocurrency markets.
Practical implications
(1) The paper develops a cryptocurrency environmental attention index based on news coverage that captures the extent to which environmental sustainability concerns are discussed in conjunction with cryptocurrencies. (2) The paper empirically investigates the impacts of cryptocurrency environmental attention on other financial or economic variables [cryptocurrency uncertainty (UCRY) indices, Bitcoin, VIX, GlobalEPU, BCO, GTU index and the Organisation for Economic Co-operation and Development IP index]. (3) The paper provides insights into making the most effective use of online databases in the development of new indices for financial research.
Social implications
Whilst blockchain technology has a number of useful implications and has great potential to transform several industries, issues of high-energy consumption and CO2 pollution regarding cryptocurrency have become some of the main areas of criticism, raising questions about the sustainability of cryptocurrencies. These results are essential for both policy-makers and for academics, since the results highlight an urgent need for research addressing the key issues, such as the growth of carbon produced in the creation of this new digital currency. The results also are important for investors concerned with the ethical implications and environmental impacts of their investment choices.
Originality/value
(1) The paper provides an efficient new proxy for cryptocurrency and robust empirical evidence for future research concerning the impact of environmental issues on cryptocurrency markets. (2) The study successfully links cryptocurrency environmental attention to the financial markets, economic developments and other volatility and uncertainty measures, which has certain novel implications for the cryptocurrency literature. (3) The empirical findings of the paper offer useful and up-to-date insights for investors, guiding policy-makers, regulators and media, enabling the ICEA to evolve into a barometer in the cryptocurrency era and play a role in, for example, environmental policy development and investment portfolio optimisation.
News about referendums and the ongoing evolution of a global contagious increase uncertainty about the development of economic fundamentals reflected by increased volatility in the financial markets. In this paper, employing volatility impulse response functions and assessing the volatility spillovers we examine intra-market volatility transmission in the Athens stock market. We employ a large sample period of daily data that spans from December 1999 to December 2020 and captures major events of the last 20 years especially related to the announcement of the two referendums during the Greek government-debt crisis in 2010 and the economic and political turmoil that increased country instability, the following years, the BREXIT referendum and the COVID-19 pandemic of 2020. Our results demonstrate that negative shocks during the announcement of the referendum produce larger impulse responses than during the announcement of the country lockdowns. Furthermore, we shed light on the existence of the dynamic relationship of volatility spillovers. Volatility spillovers peaked during the COVID-19 pandemic. Dynamic spillover plots demonstrate that during the COVID-19 pandemic, more volatility is transmitted by mid cap firms to large cap firms. Our findings have implications to market participants, policy makers and market regulators.
This study combined time-varying parameter vector autoregression (TVP-VAR) and a spillover index model to analyze the static, total, and net spillover effects of energy and stock markets before and after the COVID-19 outbreak. A network method was also used to depict structural changes more intuitively. Furthermore, we calculated and compared changes in the hedge ratio, optimal portfolio weights, and hedge effectiveness to guide investors to adjust portfolio strategies during COVID-19. The main findings were as follows: First, COVID-19 had a significant impact on spillover effects, and the average value of total spillover index increased by 19.94% compared with that before the epidemic. Second, the energy market was an important risk recipient of the stock market before COVID-19, and the extent of risk acceptance increased after the COVID-19 outbreak. Third, the hedging ratio, optimal portfolio weights, and hedge effectiveness showed huge changes after the COVID-19 outbreak, requiring investors to adjust their portfolio strategies.
The COVID-19 pandemic has exerted a noteworthy impact on stock market volatility around the world. Can vaccination programs revert these adverse effects? To answer this question, we scrutinize daily data from 66 countries from January 1, 2020 to April 30, 2021. We provide convincing evidence that COVID-19 vaccination assists in stabilizing the global equity markets. The drop in volatility is robust to many considerations and does not result solely from either the pandemic itself or the government policy responses—the negative correlation remains significant after controlling for these factors. The impact of vaccinations is relatively stronger within developed markets than in emerging ones.
This paper proposes a new approach to estimating investor sentiments and their implications for the global financial markets. Contextualising the COVID-19 pandemic, we draw on the six behavioural indicators (media coverage, fake news, panic, sentiment, media hype and infodemic) of the 17 largest economies and data from 1st January 2020 to 3rd February 2021. Our key findings, obtained using a time-varying parameter-vector auto-regression (TVP-VAR) model, indicate the total and net connectedness for the new index, entitled ’feverish sentiment’. This index provides us insight into economies that send or receive the sentiment shocks. The construction of the network structures indicates that the United Kingdom, China, the United States and Germany became the epicentres of the sentimental shocks that were transmitted to other economies. Furthermore, we also explore the predictive power of the newly constructed index on stock returns and volatility. It turns out that investor sentiment positively (negatively) predicts the stock volatility (return) at the onset of COVID-19. This is the first study of its kind to assess international feverish sentiments by proposing a novel approach and its impacts on the equity market. Based on empirical findings, the study also offers some policy directions to mitigate the fear and panic during the pandemic.
We have developed and made available a new Cryptocurrency Uncertainty Index (UCRY) based on news coverage. Our UCRY Index captures two types of uncertainty: that of the price of cryptocurrency (UCRY Price) and uncertainty of cryptocurrency policy (UCRY Policy). We show that the constructed index exhibits distinct movements around major events in cryptocurrency space. We suggest that this index captures uncertainty beyond Bitcoin, and can be used for academic, policy, and practice-driven research.
In this paper, we investigated the relationship between cryptocurrency market and hedge funds in two different ways. First, we focus on the dependence between Cryptocurrency hedge funds and conventional hedge funds strategies using VAR and VECM models, while analyzing the impact of COVID-19 on the hedge funds' values. Secondly, we choose between ARDL and ARDL-ECM models to study the effects of cryptocurrency price changes on Crypto- Currency hedge funds' values during COVID-19 crisis. Our empirical findings demonstrate that there is substantial interactions between Crypto-Currency and conventional hedge funds. The COVID-19 pandemic has significant negative impact on the performance of the following hedge funds: Event Driven, Relative Value and Distressed Debt fund strategies, this has reflected in a significant drop in their values during this critical period. However, we demonstrate that COVID-19 pandemic did not affect the relationship between crypto-currency hedge funds and both bitcoin and Ethereum. These findings hold profound implications for hedge funds managers, cryptocurrency market main players and policy makers. Our study is crucial in forecasting the performance of these markets especially during global pandemics.
Prior research has shown that energy sector stock prices are impacted by uncertainty. The coronavirus (COVID-19) pandemic has given rise to widespread health and economic-related uncertainty. In this study, we investigate the impact and the timing of the impact of COVID-19 related uncertainty on returns and volatility for 20 national energy indices and a global energy index using ARCH/GARCH models. We propose a novel ‘overall impact of uncertainty’ (OIU) measure, explained using a natural phenomenon analogy of the overall impact of a rainstorm, to gauge the magnitude and intensity of the impact of uncertainty on energy sector returns. Drawing from economic psychology, COVID-19 related uncertainty is measured in terms of searches for information relating to COVID-19 as captured by Google search trends. Our results show that the energy sectors of countries further west from the outbreak of the virus in China are impacted to a greater extent by COVID-19 related uncertainty. A similar observation is made for net energy and oil exporters relative to importers. We also find that the impact of uncertainty on most national energy sectors intensified and then weakened as the pandemic evolved. Additional analysis confirms that COVID-19 uncertainty is part of the composite set of factors that drive energy sector returns over the COVID-19 period although its importance has declined over time.
Inter-sectoral volatility linkages in the Chinese stock market are understudied, especially asymmetries in realized volatility connectedness, accounting for the catastrophic event associated with the COVID-19 outbreak. In this paper, we examine the asymmetric volatility spillover among Chinese stock market sectors during the COVID-19 pandemic using 1-min data from January 2, 2019 to September 30, 2020. In doing so, we build networks of generalized forecast error variances by decomposition of a vector autoregressive model, controlling for overall market movements. Our results show evidence of the asymmetric impact of good and bad volatilities, which are found to be time-varying and substantially intense during the COVID-19 period. Notably, bad volatility spillover shocks dominate good volatility spillover shocks. The findings are useful for Chinese investors and portfolio managers constructing risk hedging portfolios across sectors and for Chinese policymakers monitoring and crafting stimulating policies for the stock market at the sectoral level.
Does past stock price reaction to pandemics contain information about future returns? To answer this, we estimate firm exposure to a pandemic index representing global concerns of infectious diseases. We demonstrate that such a pandemic beta reliably predicts the cross-section of future stock returns. The highest pandemic beta decile outperforms the lowest pandemic beta decile by about 1% per month on a risk-adjusted basis. The effect is not explained by well-known return predictors and is robust to many considerations. Our findings indicate that investors do not correctly price information stemming from firms’ reactions to pandemics.
We develop and make available a new Cryptocurrency Uncertainty Index (UCRY) based on news coverage. Our UCRY Index captures two types of the uncertainty: cryptocurrency price uncertainty (UCRY Price) and cryptocurrency policy uncertainty (UCRY Policy). We show that the constructed index has distinct movements around major events in cryptocurrency space. We suggest that this index captures uncertainty beyond Bitcoin, and can be used for academic, policy, and practice-driven research.
Purpose
The purpose of this paper is to capture the investors' mood related to the COVID-19 pandemic and analyze its impact on the stock market returns.
Design/methodology/approach
To capture the investor mood related to the COVID-19 pandemic, the authors construct a unique COVID-19 fear index based on the Search Volume Index (SVI) from Google Trends (http://www.Google.com/trends/) of the search terms related to COVID-19 words and phrases as revealed by Google and Internet dictionaries. The COVID-19 fear index was used to investigate its impact on the stock market returns.
Findings
The study finds a strong negative association between COVID-19 fear and stock returns. Unlike other studies, the relationship is persistent for a significant period. This relationship is not found to reverse in the following days. The results also highlight that COVID-19 fear strongly impacts the stock market. The sentiment persists for a significant period and is not reversed soon, unlike the regular times in earlier studies.
Originality/value
The study is among the very few studies that constructed COVID-19 fear index using several Google search terms and captured its impact on the stock market returns.
Employing the new measure of the contagion effect of the COVID-19, i.e. the Infectious Disease EMV Index by Baker et al. (2020) and the novel Quantile Cross-spectral (coherency) approach proposed by Baruník and Kley (2019), this study probes into the interconnectedness between EPU and cryptocurrencies as well as that between the COVID-19 pandemic and cryptocurrencies in a time series from August 10th 2015 to June 30th 2020. Our empirical findings indicate cryptocurrencies act as good hedging tools against high EPU, but not during periods of moderate or low EPU and that their hedging properties don’t remain all the time. Several kinds of cryptocurrencies, XRP and XLM specifically, can serve as hedging assets during such period of extreme financial market panic. Evidence from China, the US and the UK insists that timely response to extreme outbreak like COVID-19 is of pivotal significance to prevent the financial market and the economy from descending into a catastrophe. Notably, XLM demonstrates the best hedging properties against high EPU, severe pandemic and other cryptocurrencies. XLM and BTC are excellent choices of hedging assets both for individual investors and institutional investors. The difference lies in that the individual investors have two more options, namely LTC and XMR.
Uncertainty surrounding COVID-19 is widespread. We investigate the timing and quantify the impact of COVID-19 related uncertainty on returns and volatility for regional market aggregates using ARCH/GARCH models. Drawing upon economic psychology, COVID-19 related uncertainty is measured by searches for information as reflected by Google Trends. Asian markets are more resilient than others. Latin American markets are most impacted in terms of returns and volatility. For most regions, there is evidence of an increasing impact of COVID-19 related uncertainty which dissipates as the crisis evolves. We confirm that Google Trends capture uncertainty by comparing this measure against alternative uncertainty measures.
The coronavirus (COVID-19) pandemic halted economic activity worldwide, hurting firms and pushing many of them toward bankruptcy. This paper discusses four central issues that have emerged in the academic and policy debates related to firm financing during the downturn. First, the economic crisis triggered by the pandemic is radically different from past crises, with important consequences for optimal policy responses. Second, it is important to preserve firms’ relationships with key stakeholders (e.g., workers, suppliers, customers, and creditors) to avoid inefficient bankruptcies and long-term detrimental economic effects. Third, firms can benefit from “hibernation,” incurring the minimum bare expenses necessary to withstand the pandemic while using credit to remain alive until the crisis subdues. Fourth, the existing legal and regulatory infrastructure is ill-equipped to deal with an exogenous systemic shock like a pandemic. Financial sector policies can help channel credit to firms, but they are hard to implement and entail different trade-offs.
During the outbreak of the COVID-19, concerns related to the severity of the pandemic have played a prominent role in investment decisions. In this paper, we analyze the relationship between public attention and the financial markets using search engine data from Google Trends. Our findings show that search query volumes in Italy, Germany, France, Great Britain, Spain, and the United States are connected with stock markets. The Italian Google Trends index is found to be the main driver of all the considered markets. Furthermore, the country-specific market impacts of COVID-19-related concerns closely follow the Italian lockdown process.
Our paper is among the first to measure the potential effects of the COVID-19 pandemic on the tourism industry. Using panel structural vector auto-regression (PSVAR) (Pedroni, 2013) on data from 1995 to 2019 in 185 countries and system dynamic modeling (real-time data parameters connected to COVID-19), we estimate the impact of the pandemic crisis on the tourism industry worldwide. Past pandemic crises operated mostly through idiosyncratic shocks' channels, exposing domestic tourism sectors to large adverse shocks. Once domestic shocks perished (zero infection cases), inbound arrivals revived immediately. The COVID-19 pandemic, however, is different; and recovery of the tourism industry worldwide will take more time than the average expected recovery period of 10 months. Private and public policy support must be coordinated to assure capacity building and operational sustainability of the travel tourism sector during 2020–2021. COVID-19 proves that pandemic outbreaks have a much larger destructive impact on the travel and tourism industry than previous studies indicate. Tourism managers must carefully assess the effects of epidemics on business and develop new risk management methods to deal with the crisis. Furthermore, during 2020–2021, private and public policy support must be coordinated to sustain pre-COVID-19 operational levels of the tourism and travel sector.
The COVID-19 pandemic and government intervention such as lockdowns may severely affect people’s mental health. While lockdowns can help to contain the spread of the virus, they may result in substantial damage to population well-being. We use Google Trends data to test whether COVID-19 and the associated lockdowns implemented in Europe and America led to changes in well-being related topic search-terms. Using difference-in-differences and a regression discontinuity design, we find a substantial increase in the search intensity for boredom in Europe and the US. We also found a significant increase in searches for loneliness, worry and sadness, while searches for stress, suicide and divorce on the contrary fell. Our results suggest that people’s mental health may have been severely affected by the pandemic and lockdown.
How do retail investors respond to the outbreak of COVID-19? We use transaction-level trading data to show that investors significantly increase their trading activities as the COVID-19 pandemic unfolds, both at the extensive and at the intensive margin. Investors, on average, increase their brokerage deposits and open more new accounts. The average weekly trading intensity increases by 13.9% as the number of COVID-19 cases doubles. The increase in trading is especially pronounced for male and older investors, and affects stock and index trading. Following the 9.99%-drop of the Dow Jones on March 12, investors significantly reduce the usage of leverage.
We investigate whether Greek depositors’ uncertainty about the future currency contains information for the observed acute depletion of deposits in the Greek banking system. We conduct a Nowcasting exercise using the Google search intensity for the term «Drachma» and document that higher search intensity leads to higher Total deposits outflows, which are primarily driven by outflows in Time deposits. We also find that the Google search intensity for the term «Drachma» exerts an asymmetric impact across one-day deposits and time deposits. In addition, the asymmetry is also present between firms’ deposits and households’ deposits. These findings support that ‘a flight-to-safety’ behavior caused by uncertainty about the future currency accounts for the erosion of deposits in Greece.
This paper offers two main innovations. First, we construct a global fear index (GFI) for the COVID-19 pandemic to support economic, financial and policy analyses in this area. Second, we demonstrate the application of the index to stock return predictability using OECD data. The panel data predictability results reveal the significance of the index as a good predictor of stock returns during the pandemic. Also, we find that accounting for “asymmetry” effect and macro (common) factors improves the forecast performance of the GFI-based predictive model for stock returns. With regular updates and improvements of the index, several empirical analyses can be extended to other macroeconomic fundamentals in future research.
The paper aims to critically review past and emerging literature to help professionals and researchers alike to better understand, manage and valorize both the tourism impacts and transformational affordance of COVID-19. To achieve this, first, the paper discusses why and how the COVID-19 can be a transformational opportunity by discussing the circumstances and the questions raised by the pandemic. By doing this, the paper identifies the fundamental values, institutions and pre-assumptions that the tourism industry and academia should challenge and break through to advance and reset the research and practice frontiers. The paper continues by discussing the major impacts, behaviours and experiences that three major tourism stakeholders (namely tourism demand, supply and destination management organisations and policy makers) are experiencing during three COVID-19 stages (response, recovery and reset). This provides an overview of the type and scale of the COVID-19 tourism impacts and implications for tourism research.
We empirically investigate the impact of economic uncertainty related to global pandemics on the volatility of the broad commodity price index as well as on the sub-indexes of crude oil and gold. The results show that uncertainty related to pandemics have a strong negative impact on the volatility of commodity markets and especially on crude oil market, while the effect on gold market is positive but less significant.
In this paper, we examine the stock markets’ response to the COVID-19 pandemic. Using daily COVID-19 confirmed cases and deaths and stock market returns data from 64 countries over the period January 22, 2020 to April 17, 2020, we find that stock markets responded negatively to the growth in COVID-19 confirmed cases. That is, stock market returns declined as the number of confirmed cases increased. We further find that stock markets reacted more proactively to the growth in number of confirmed cases as compared to the growth in number of deaths. Our analysis also suggests negative market reaction was strong during early days of confirmed cases and then between 40 to 60 days after the initial confirmed cases. Overall, our results suggest that stock markets quickly respond to COVID-19 pandemic and this response varies over time depending on the stage of outbreak.
In this paper, we analyze the connectedness between the recent spread of COVID-19, oil price volatility shock, the stock market, geopolitical risk and economic policy uncertainty in the US within a time-frequency framework. The coherence wavelet method and the wavelet-based Granger causality tests applied to US recent daily data unveil the unprecedented impact of COVID-19 and oil price shocks on the geopolitical risk levels, economic policy uncertainty and stock market volatility over the low frequency bands. The effect of the COVID-19 on the geopolitical risk substantially higher than on the US economic uncertainty. The COVID-19 risk is perceived differently over the short and the long-run and may be firstly viewed as an economic crisis. Our study offers several urgent prominent implications and endorsements for policymakers and asset managers.
How do retail investors respond to the outbreak of COVID-19? We use transaction-level trading data to show that investors significantly increase their trading activities as the COVID-19 pandemic unfolds, both at the extensive and at the intensive margin. Investors, on average, increase their brokerage deposits and open more new accounts. The average weekly trading intensity increases by 13.9% as the number of COVID-19 cases doubles. The increase in trading is especially pronounced for male and older investors, and affects stock and index trading. Following the 9.99%-drop of the Dow Jones on March 12, investors significantly reduce the usage of leverage.
This paper quantifies the impact of stock-specific news sentiment on future financial returns. Daily predictive regressions yield significant t-statistics for 7% at most of our sample of more than 1000 large stocks listed in the USA. While a few assets do run through pockets of predictability, the evidence suggests that the feedback effect is stronger in the reverse direction: returns are more likely to drive future sentiment than the other way around.
The rapid spread of coronavirus (COVID-19) has dramatically impacted financial markets all over the world. It has created an unprecedented level of risk, causing investors to suffer significant loses in a very short period of time. This paper aims to map the general patterns of country-specific risks and systemic risks in the global financial markets. It also analyses the potential consequence of policy interventions, such as the US’ decision to implement a zero-percent interest rate and unlimited quantitative easing (QE), and how these policies may introduce further uncertainties into global financial markets.
This paper highlights the enormous economic and social impact of COVID-19 with respect to articles that have either prognosticated such a large-scale event, and its economic consequences, or have assessed the impacts of other epidemics and pandemics. A consideration of possible impacts of COVID-19 on financial markets and institutions, either directly or indirectly, is briefly outlined by drawing on a variety of literatures. A consideration of the characteristics of COVID-19, along with what research suggests have been the impacts of other past events that in some ways roughly parallel COVID-19, points toward avenues of future investigation.
This study investigates the impact of firm-specific investor sentiment on stock price crash risk. To achieve this goal, we first develop a firm-specific investor sentiment index. Based on the sentiment index, we conduct empirical tests and find that there is a significant positive relationship between firm-specific investor sentiment and stock price crash risk. This finding holds after a series of robustness checks including different measures of crash risk, the winsorization of some variables, and the inclusion of some omitted variables. Further analyses show that the positive relationship is more pronounced for firms with worse liquidity.