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Bitcoin market had a significant momentum phenomenon before the launch of Futures, and then it turned into an insignificant reversal effect. After Covid-19 appeared, the momentum effect and reversal effect disappeared. The advent of bitcoin futures has increased how investors respond to information. With the outbreak of COVID-19, investor interest in Bitcoin as a safe-haven asset has increased the effectiveness of the price. We estimate the speed of signal diffusion in the bitcoin market, and the results support that effective response to information is the essential mechanism for the disappearance of momentum effect.
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The developmental origins of health and disease (DOHaD) indicate that fetal tissues and organs in critical and sensitive periods of development are susceptible to structural and functional changes due to the adverse environment in utero. Maternal immune activation (MIA) is one of the phenomena in DOHaD. Exposure to maternal immune activation is a risk factor for neurodevelopmental disorders, psychosis, cardiovascular diseases, metabolic diseases, and human immune disorders. It has been associated with increased levels of proinflammatory cytokines transferred from mother to fetus in the prenatal period. Abnormal immunity induced by MIA includes immune overreaction or immune response failure in offspring. Immune overreaction is a hypersensitivity response of the immune system to pathogens or allergic factor. Immune response failure could not properly fight off various pathogens. The clinical features in offspring depend on the gestation period, inflammatory magnitude, inflammatory type of MIA in the prenatal period, and exposure to prenatal inflammatory stimulation, which might induce epigenetic modifications in the immune system. An analysis of epigenetic modifications caused by adverse intrauterine environments might allow clinicians to predict the onset of diseases and disorders before or after birth.
Subject(s)
Prenatal Exposure Delayed Effects , Pregnancy , Female , Humans , Immune System/metabolism , Parturition , Cytokines , MothersABSTRACT
This paper examines the impacts of local housing sentiments on the housing price dynamics of China. With a massive second-hand transaction dataset, we construct monthly local housing sentiment indices for 18 major cities in China from January 2016 to October 2020. We create three sentiment proxies representing the local housing market liquidity and speculative behaviors from the transaction dataset and then use partial least squares (PLS) to extract a recursive look-ahead-bias-free local housing sentiment index for each city considered. The local housing sentiments are shown to have robust predictive powers for future housing returns with a salient short-run underreaction and long-run overreaction pattern. Further analysis shows that local housing sentiment impacts are asymmetric, and housing returns in cities with relatively inelastic housing supply are more sensitive to local housing sentiments. We also document a significant feedback effect between housing returns and market sentiments, indicating the existence of a pricing-sentiment spiral which could potentially enhance the ongoing market fever of Chinese housing markets. The main estimation results are robust to alternative sentiment extraction methods and alternative sentiment proxies, and consistent for the sample period before COVID-19.
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This study tests whether pairs trade conditional on representative bias in the options and stock markets leads to abnormal returns. While previous literature on representativeness focuses on a single index, S&P 500 and Russell 2000 indexes are used to examine the extent to which representative bias arises due to a pattern of similar information shock in the three analyzed periods. The empirical results of the options market lend little support to the representativeness anomalies because Russell 2000 index, relative to S&P 500 index, does not adjust to a sequence of information shocks in the 2020 economic downturn inflicted by the coronavirus pandemic, despite the asymmetrical responsiveness to information shock over the sample period of 2004 to 2020, and during the 2008 global financial crisis. However, the empirical findings of the stock market verify, to some degree, the existence of representative bias during the sample period of 2004 to 2020. To examine whether asymmetrical representativeness in the options market or representativeness in the stock market yields abnormal returns, pairs trade is designed to exploit riskless profits via buying S&P 500 index and selling Russell 2000 index. Based on the Fama and French three-factor model, the empirical evidence is in support of market efficiency because the pairs trading strategy cannot generate positive abnormal returns in both options and stock markets.
ABSTRACT
Bitcoin market had a significant momentum phenomenon before the launch of Futures, and then it turned into an insignificant reversal effect. After Covid-19 appeared, the momentum effect and reversal effect disappeared. The advent of bitcoin futures has increased how investors respond to information. With the outbreak of COVID-19, investor interest in Bitcoin as a safe-haven asset has increased the effectiveness of the price. We estimate the speed of signal diffusion in the bitcoin market, and the results support that effective response to information is the essential mechanism for the disappearance of momentum effect.
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Purpose: This study examines the impact of firm-specific information and macroeconomic variables on market overreaction of US and Chinese winner and loser portfolio before and during COVID-19. Design/methodology/approach: The firm-specific information includes firm size, volume, volatility, return of asset (ROA), return of equity (ROE), earning per share (EPS) and quick ratio while the macroeconomic variables are export rate, import rate, real GDP, nominal GDP, FDI, IPI and unemployment rate. Besides, one-third of the top performance stocks are categorized as winner portfolio while one-third of lowest performance stocks are categorized as loser portfolio. This study uses AECR to indicate stock return and measure market overreaction. GAECR is used to determine contrarian profit. The data range of pre-COVID-19 is from 1-Jan-2015 to 31-Dec-2019 while the period of COVID-19 is from 1-Jan-2020 to 31-Dec-2020. Findings: In pre-COVID-19, firm-specific information (volatility, ROA, ROE and EPS) and macroeconomic variables are found to be correlated to stock return in US and Chinese portfolios except Chinese winner portfolio. Nonetheless, the impact of firm-specific information has vanished and macroeconomic variables are significant to stock return in COVID-19. It shows that investors rely on the economic indicators to trade in turbulent period due to emergence of COVID-19 as a disruption in market. Furthermore, US and Chinese portfolios are overreacted during COVID-19. Chinese loser portfolio has higher tendency of overreaction than US loser portfolio while US winner portfolio has higher tendency of overreaction than Chinese winner portfolio. Originality/value: The results of this study assists academician, practitioners and investors on understanding and create awareness to the existence of market overreaction and the determinants that can cause the phenomenon. © 2021, Emerald Publishing Limited.
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Purpose Research on price extremes and overreactions as potential violations of market efficiency has a long tradition in investment literature. Arguably, very few studies to date have addressed this issue in cryptocurrencies trading. The purpose of this paper is to consider the extreme value modelling for forecasting COVID-19 effects on cryptocoin markets. Additionally, this paper examines the importance of technical trading indicators in predicting the extreme price behaviour of cryptocurrencies. Design/methodology/approach This paper decomposes the daily-time series returns of four cryptocurrency returns into potential maximum gains (PMGs) and potential maximum losses (PMLs) at first and then tests their lead-lag relations under an econometric framework. This paper also investigates the non-random properties of cryptocoins by computing the incremental explanatory power of PML-PMG modelling with technical trading indicators controlled. Besides, this paper executes an event study to identify significant changes caused by COVID-19-related events, which is capable of analysing the cryptocoin market overreactions. Findings The findings of this paper produce the evidence of both market overreactions and trend persistence in the potential gains and losses from coins trading. Extreme price behaviour explains volatility and price trends in crypto markets before and after the outbreak of a pandemic that substantiate the non-random walk behaviour of crypto returns. The presence of technical trading indicators as control variables in the extreme value regressions significantly improves the predictive power of models. COVID-19 crisis affects the market efficiency of cryptocurrencies that improves the usefulness of extreme value predictions with technical analysis. Research limitations/implications This paper strongly supports for the robustness of technical trading strategies in cryptocurrency markets. However, the "beast is moving quick" and uncertainty as to the new normalcy about the post-COVID-19 world puts constraint on making best predictions. Practical implications The paper contributes substantially to our understanding of the pricing efficiency of cryptocurrency markets after the COVID-19 outbreak. The findings of continuing return predictability and price volatility during COVID-19 show that profitable investment opportunities for cryptocoin traders are prevailing in pandemic times. Originality/value The paper is unique to understand extreme return reversals behaviour of cryptocurrency markets regarding events related to COVID-19 breakout.
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This study investigates the stock performance of industries in the panic, rebound, and post-V-shaped periods separated by Covid-19 events in Taiwan, in which industries are classified as the detrimental, impaired, neutral, and beneficial groups. Prices of these four industries slumped about the same in the panic period but subsequently rose differently in the rebound and post-V-shaped periods, implying that investors make investment decisions by perception when facing dread risk but by analytic assessments after dread risk recedes. Regression tests show that prices of individual stocks in the same industry dropped differently in the panic period, reflecting investors' bounded rationality in that they are emotional at the industry level but rational at the firm level. Also, logistic regressions indicate that investors tend to be overoptimistic about the impaired and detrimental industries in the rebound period. More than 10% of firms repurchased their stocks but only a small portion of firms issued equity in the Covid-19 period, revealing that firms would participate in short-run trading but halt long-run investments when facing uncertainty. This study contributes to the literature by showing investors' behavior and firms' actions in different periods of Covid-19.
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The objective of this paper is to examine the overreaction behavior of 20 commodity futures based on intraday data from November 20, 2019 to June 3, 2020 with a focus on the impact of the Covid-19 pandemic. A dynamic and non-parametric approach is applied on intraday data for four different frequencies (from 1 min to 1 h) and two different sub-periods (pre-Covid-19 pandemic and during Covid-19 pandemic) in order to detect overreaction behavior which is defined as a large change of prices followed by proportional price reversals. Our empirical findings show that the overreaction hypothesis is confirmed for the considered commodity futures. Furthermore, both the number and the amplitude of overreactions is higher during the Covid-19 pandemic. Our findings also indicate that soft and metal commodities show much less overreactions than precious metals and especially energy commodities. In particular, crude oil futures exhibit a different overreaction behavior compared to other commodities since it has a higher number of negative than positive overreactions during the Covid-19 pandemic. We also find that the data frequency is independent of the overreacting behavior in both periods as the results continuously improve when having more observations due to higher frequencies. Finally, we find that extreme overreactions during the Covid-19 pandemic provide a great potential for profitable trading returns, which can be exploited by traders.
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This study examines the short-term impact of the 2019 novel coronavirus (COVID-19) outbreak on 52 listed airline companies around the world by using event study methodology. The results demonstrate that airline stock returns decline more significantly than the market returns after three major COVID-19 announcements were made. Overall, investors react differently during the three selected events. The strongest overreaction is noted in the post-event period of the World Health Organization's and President Trump's official announcements. Moreover, the findings confirm that traders in Western countries are more responsive to recent information than the rest of the world. The findings call for immediate policy designs in order to alleviate the impact of the pandemic in the airline industry around the globe.
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This article describes the efforts made by the Israeli government to contain the spread of COVID-19, which were implemented amidst a constitutional crisis and a yearlong electoral impasse, under the leadership of Prime Minister Benjamin Netanyahu, who was awaiting a trial for charges of fraud, bribery, and breach of trust. It thereafter draws on the disproportionate policy perspective to ascertain the ideas and sensitivities that placed key policy responses on trajectories which prioritized differential policy responses over general, nation-wide solutions (and vice versa), even though data in the public domain supported the selection of opposing policy solutions on epidemiological or social welfare grounds. The article also gauges the consequences and implications of the policy choices made in the fight against COVID-19 for the disproportionate policy perspective. It argues that Prime Minister Netanyahu employed disproportionate policy responses both at the rhetorical level and on the ground in the fight against COVID-19; that during the crisis, Netanyahu enjoyed wide political leeway to employ disproportionate policy responses, and the general public exhibited a willingness to tolerate this; and (iii) that ascertaining the occurrence of disproportionate policy responses is not solely a matter of perception.