scholarly journals Effects of COVID-Induced Public Anxiety on European Stock Markets: Evidence From a Fear-Based Algorithmic Trading System

2022 ◽  
Vol 12 ◽  
Author(s):  
Yunpeng Sun ◽  
Haoning Li ◽  
Yuning Cao

The effect of COVID-induced public anxiety on stock markets, particularly in European stock market returns, is examined in this research. The search volumes for the notion of COVID-19 gathered by Google Trends and Wikipedia were used as proxies for COVID-induced public anxiety. COVID-induced public anxiety was shown to be linked with negative returns in European stock markets when a panel data method was used to a sample of data from 14 European stock markets from January 2, 2020 to September 17, 2020. Using an automated trading system, we used this finding to suggest investment methods based on COVID-induced anxiety. The findings of back-testing indicate that these techniques have the potential to generate exceptional profits. These results have significant consequences for government officials, the media, and investors.

2017 ◽  
Vol 9 (7) ◽  
pp. 32
Author(s):  
SingRu Hoe ◽  
Srinivas Nippani

This study seeks to address the question if the 2016 U.S. Presidential election and Mr. Donald Trump’s path to U.S. presidency affected the stock market returns in China. We do not find conclusive results from three leading stock indices of China, SHCOMP, SZCOMP, and SHSZ300. There is an immediate impact shown in SHSZ300, but not in SHCOMP and SZCOMP. We ascribe this to the impact of less sophisticated investors who dominate the stock market in China and also to that country’s censorship of the media wherein the government could effectively either block or downplay the unfavorable information. 


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Slah Bahloul ◽  
Nawel Ben Amor

PurposeThis paper investigates the relative importance of local macroeconomic and global factors in the explanation of twelve MENA (Middle East and North Africa) stock market returns across the different quantiles in order to determine their degree of international financial integration.Design/methodology/approachThe authors use both ordinary least squares and quantile regressions from January 2007 to January 2018. Quantile regression permits to know how the effects of explanatory variables vary across the different states of the market.FindingsThe results of this paper indicate that the impact of local macroeconomic and global factors differs across the quantiles and markets. Generally, there are wide ranges in degree of international integration and most of MENA stock markets appear to be weakly integrated. This reveals that the portfolio diversification within the stock markets in this region is still beneficial.Originality/valueThis paper is original for two reasons. First, it emphasizes, over a fairly long period, the impact of a large number of macroeconomic and global variables on the MENA stock market returns. Second, it examines if the relative effects of these factors on MENA stock returns vary or not across the market states and MENA countries.


2020 ◽  
Author(s):  
Turki Maya

<p>The paper tries to answer the following question: could the 2016 oil price crisis generate financial contagion among stock markets? </p> <p>The study period is composed of two sub-periods; a quiet one from 3/01/2012 to 01/08/2014 and turbulent one from 04/08/2014 to 25/05/2016. Raw data consists of daily international stock market indexes prices. The co-movements of the stock market returns are analyzed through a principal component analysis (PCA).</p> <p>The results revealed that the <em>KMO</em> index (Kaiser-Mayer-Olkin) is higher during the turbulent period than during the quiet one and that the proportion of variance explained by the first component during the turbulent period reached 35% while during the quiet one it represented only 26,7%.Regarding the component structure, for the turbulent period, three factors are able to explain the stock markets indexes movements while for the quiet period four factors are required. </p> <p>The findings give more credit to the thesis supporting the linkage between cross correlation and financial contagion and classify the 2016 oil crisis, as just a coupling episode and not an extreme one.</p>


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Serkan Karadas ◽  
Minh Tam Tammy Schlosky ◽  
Joshua C. Hall

Purpose What information do members of Congress (politicians) use when they trade stocks? The purpose of this paper is to attempt to answer this question by investigating the relationship between an aggregate measure of trading by members of Congress (aggregate congressional trading) and future stock market returns. Design/methodology/approach The authors follow the empirical framework used in academic work on corporate insiders. In particular, they aggregate 61,998 common stock transactions by politicians over the 2004–2010 period and estimate time series regressions at a monthly frequency with heteroskedasticity and autocorrelation robust t-statistics. Findings The authors find that aggregate congressional trading predicts future stock market returns, suggesting that politicians use economy-wide (i.e. macroeconomic) information in their stock trades. The authors also present evidence that aggregate congressional trading is related to the growth rate of industrial production, suggesting that industrial production serves as a potential channel through which aggregate congressional trading predicts future stock market returns. Originality/value To the best of the authors’ knowledge, this study is the first to document a relationship between aggregate congressional trading and stock market returns. The media and scholarly attention on politicians’ trades have mostly focused on the question of whether politicians have superior information on individual firms. The results from this study suggest that politicians’ informational advantage may go beyond individual firms such that they potentially have superior information on the overall trajectory of the economy as well.


2018 ◽  
Vol 19 (6) ◽  
pp. 1538-1553 ◽  
Author(s):  
Ajaya Kumar Panda ◽  
Swagatika Nanda

The present study attempts to capture the return volatility and the extent of dynamic conditional correlation between the stock markets of North America region. The data contain weekly stock market returns spanning from the second week of 1995 to the fourth week of June 2016. Using univariate ARCH and GARCH approaches, the study finds evidence of return volatility and its persistence within the region. Mexican stock market neither reacts intensely to immediate market fluctuations nor the part of the realized past volatility spill over to the current period, whereas the stock markets of Canada and USA experience high persistence of return volatility and Bermuda stock market returns are highly sensitive to the immediate market fluctuations. Using MGARCH-DCC, this article finds that emerging markets are less linked to the developed market in terms of return and that there also exists a weak co-movement between the stock markets. There is no evidence of market integration throughout the sample period. Correlations tend to spread out equally throughout the sample period, but the co-variances were found to be more volatile during 2008–2010. This article reveals that changes in co-movement are not due to a change in the correlations between markets but is simply due to volatility.


Author(s):  
Amalendu Bhunia ◽  
Devrim Yaman

This paper examines the relationship between asset volatility and leverage for the three largest economies (based on purchasing power parity) in the world; US, China, and India. Collectively, these economies represent Int$56,269 billion of economic power, making it important to understand the relationship among these economies that provide valuable investment opportunities for investors. We focus on a volatile period in economic history starting in 1997 when the Asian financial crisis began. Using autoregressive models, we find that Chinese stock markets have the highest volatility among the three stock markets while the US stock market has the highest average returns. The Chinese market is less efficient than the US and Indian stock markets since the impact of new information takes longer to be reflected in stock prices. Our results show that the unconditional correlation among these stock markets is significant and positive although the correlation values are low in magnitude. We also find that past market volatility is a good indicator of future market volatility in our sample. The results show that positive stock market returns result in lower volatility compared to negative stock market returns. These results demonstrate that the largest economies of the world are highly integrated and investors should consider volatility and leverage besides returns when investing in these countries.


2012 ◽  
Vol 468-471 ◽  
pp. 181-185
Author(s):  
Wann Jyi Horng ◽  
Tien Chung Hu ◽  
Ming Chi Huang

The empirical results show that the dynamic conditional correlation (DCC) and the bivariate asymmetric-IGARCH (1, 2) model is appropriate in evaluating the relationship of the Japan’s and the Canada’s stock markets. The empirical result also indicates that the Japan and the Canada’s stock markets is a positive relation. The average estimation value of correlation coefficient equals to 0.2514, which implies that the two stock markets is synchronized influence. Besides, the empirical result also shows that the Japan’s and the Canada’s stock markets have an asymmetrical effect, and the variation risks of the Japan’s and the Canada’s stock market returns also receives the influence of the good and bad news, respectively.


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