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1.
Investment Management and Financial Innovations ; 20(2):116-126, 2023.
Article in English | Scopus | ID: covidwho-20242783

ABSTRACT

With the outbreak of COVID-19, the Chinese government implemented the "zero-COVID” policy as a measure to curb the spread of the virus. The different measures of the policy include widespread testing, contact tracing, and strict quarantine and isolation protocols. In view of recent changes in COVID-19 trends and other economic indicators, the Chinese government withdrew significant provisions of the zero-COVID policy in China. The present study investigates the sectoral performance of the Chinese stock market after the withdrawal of the zero-COVID policy. The study considers eighteen sectoral indices of the Shenzhen Stock Exchange of China as a sample and applies the event study methodology to study the impact of the policy withdrawal on the stock prices performance. The results of the study indicate that sectors such as hotel, consumer staples, the financial sector, real estate, media, and culture have reported significant positive movement after the withdrawal of the zero-COVID policy, while other sectors such as consumer discretionary, energy, healthcare, information technology, manufacturing, mining, technology, telecom, transportation, utilities, wholesale, and retail have shown insignificant reactions. These results also indicate that when the COVID-19 outbreak happened in China, different sectors of the economy reacted negatively except the retail and wholesale sectors, while with the withdrawal of the zero-COVID policy by the Chinese government, the reaction of investors is optimistic as different sectors are reporting either positive reactions in the stock price movement or no reaction. © Prashant Sharma, Surender Kumar, 2023.

2.
Applied Economics ; 2023.
Article in English | Scopus | ID: covidwho-2324450

ABSTRACT

Based on the TVP-VAR-DY and TVP-VAR-BK models, this article examines the characteristics and mechanisms of systemic risk contagion in the Chinese industries under geopolitical events by selecting data spans from 1 January 2010 to 31 August 2022. First, dynamic analysis of full-sample risk contagion shows that there is a significant climb in total risk during geopolitical events. Then the static analysis of risk contagion in the full sample specifically shows the correlation between risk contagion and industry chain between the financial and real sectors. Besides, the sub-sample analysis illustrates that during geopolitical events such as the Sino-US Trade War, the COVID-19 Pandemic and the Russia-Ukraine Conflict, Chinese industrial stock indexes show short-term risk spillovers from key industries related to geopolitical events, and gradually spread along the industrial chain in the long run compared to the Chinese ‘Stock Market Crash'. Through further mechanistic tests, we find that the irrational behaviour of investors in the market exacerbates short-term risk contagion, while the financial distress of real firms due to financing constraints exacerbates long-term risk contagion. In addition, geopolitical risk, economic uncertainty, and policy uncertainty as macro variables also have an impact on the short-run and long-run risk contagion. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

3.
Cogent Economics and Finance ; 11(1), 2023.
Article in English | Scopus | ID: covidwho-2294944

ABSTRACT

The primary purpose of this paper is to explore the herding behavior in the Chinese stock market during COVID-19 and the asymmetry of that behavior using the daily returns of A- and B-shares from 2 January 2019, to 15 October 2021. The study uses the cross-sectional absolute deviation model to analyze stock market herding behavior by non-linear polynomial regression. We show that the herding behavior in the Chinese stock market is more prominent during the COVID-19 pandemic. Herding behavior has a negative effect on stock market volatility. Moreover, such a suppressing effect weakened during the COVID-19 pandemic. There is an asymmetry in herding behavior during the bull and bear markets, which is helpful in our investigation of the market's volatility during the COVID-19 pandemic. The pronounced asymmetry in the herding behavior of the Chinese stock market during COVID-19 is assessed using the E-GARCH (p, q) model. The empirical results of the present study contribute to the literature about herding asymmetry by showing the herding behavior during the health crisis and bull and bear markets. It also helps reconcile the debate about the impact of herding on market stability and provides insightful guidance for investors wishing to invest in the Chinese stock market. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

4.
Energies ; 16(5), 2023.
Article in English | Scopus | ID: covidwho-2272430

ABSTRACT

We analyze crude oil's dependence and the risk spillover effect on the Chinese stock market and the gold market. We compare both static and dynamic copula functions and calculate the average upward and downward spillover effect using the time-varying Copula model and the conditional value-at-risk approach. By utilizing daily data on crude oil prices, China's stock market, and the gold market, we observe an asymmetric spillover effect: the downside spillover effects from crude oil prices on the Chinese stock market and gold market are larger than the upside spillover effect. We then identify changes in the structure of the sample periods and calculate the dynamic conditional correlation between them. In addition, we explore the optimal weight and hedge ratios in diversified portfolios to mitigate potential risks. Our results suggest that investors and portfolio managers should frequently adjust their portfolio strategies, particularly during extreme events like COVID-19, when financial assets become more volatile. Furthermore, crude oil can help reduce the risk in the Chinese stock market and gold market to some extent during different sub-periods. © 2023 by the authors.

5.
International Review of Economics and Finance ; 83:528-545, 2023.
Article in English | Scopus | ID: covidwho-2245372

ABSTRACT

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. © 2022 Elsevier Inc.

6.
Estudios de Economia ; 49(2):199-229, 2022.
Article in English | Scopus | ID: covidwho-2156901

ABSTRACT

We analyze herding behavior in the Chinese stock markets in the context of the COVID-19 pandemic using the cross-sectional absolute deviation (CSAD) model proposed by Chang et al. (2000) to detect herding behavior in the time period between January 30, 2001, and June 12, 2020. We consider stock prices for all firms listed (A-shares) on the Shanghai Stock Exchange (SHSE) and Shenzhen Stock Exchange (SZSE) in China. We report the presence of herding behavior during the period under study and that herding behavior becomes stronger after December 31, 2019 (the COVID-19 event date). We also study herding activity in the context of potential asymmetries in market return and volatility states. The results show that when the market return is high and the volatility is low, there is a more predominant herding behavior trend. Our results do not depend on using different time windows. Results do not change when time-varying coefficients are considered using rolling regressions. Other control variables which may be relevant in explaining CSAD do not change the results when included in the estimations. © 2022, Universidad de Chile. All rights reserved.

7.
International Review of Economics & Finance ; 2022.
Article in English | ScienceDirect | ID: covidwho-2069180

ABSTRACT

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.

8.
J Econ Asymmetries ; 26: e00276, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-2069306

ABSTRACT

The COVID-19 pandemic, which originated in Wuhan, China, precipitated the stock market crash of March 2020. According to published global data, the U.S. has been most affected by the tragedy throughout this outbreak. Understanding the degree of integration between the financial systems of the world's two largest economies, particularly during the COVID-19 pandemic, necessitates thorough research of the risk transmission from China's stock market to the U.S. stock market. This study examines the volatility transmission from the Chinese to the U.S. stock market from January 2001 to October 2020. We employ a variant form of the EGARCH (1,1) model with long-term control over the excessive volatility breakpoints identified by the ICSS algorithm. Since 2004, empirical evidence indicates that the volatility shocks of the Chinese stock market have frequently and negatively affected the volatility of the U.S. stock market. Most importantly, we explore that the COVID-19 pandemic vigorously and positively promoted the volatility infection from the Chinese equity market to the U.S. equity market in March 2020. This precious evidence endorses the asymmetric volatility transmission from the Chinese to the U.S. stock market when COVID-19 broke out. These experimental results provide profound insight into the risk contagion between the U.S. and China stock markets. They are also essential for securities investors to minimize portfolio risk. Furthermore, this paper suggests that globalization has carefully driven the integration of China's stock market with the international equity markets.

9.
The European Journal of Finance ; : 1-36, 2022.
Article in English | Web of Science | ID: covidwho-2017092

ABSTRACT

The purpose of this paper is to study the spillover effects of financial stress among five important financial markets (bond, stock, foreign exchange, interbank, and real estate markets) in China, and explore the important determinants of financial stress spillover level among the markets and the impact of the Chinese stress spillover situation on the European markets. Our findings are as follows: First, there is a significant stress spillover effect among the five markets, and the total financial stress spillover index (TSSI) is very high during the global financial crisis. Generally, the stock and real estate markets are the major transmitters of stress spillover, and the interbank and bond markets are the major receivers. Second, the most macro factors have significant impacts on the financial stress spillover level among the markets, especially CPI index, the Chinese economic policy uncertainty index and VIX index. And the severity of the COVID-19 epidemic in China and the world has a significant impact on the TSSI, especially from March 2020 to August 2020. Finally, the TSSI can significantly increase the volatility of French stock market, Italian stock market and German government bond market, especially during the Sino-US trade war and the COVID-19 epidemic.

10.
Journal of Commodity Markets ; : 100275, 2022.
Article in English | ScienceDirect | ID: covidwho-1983379

ABSTRACT

Using 5-min data of Chinese stock market index and eight Chinese commodity futures (soybean, wheat, corn, gold, silver, copper and aluminum, crude oil) from March 26, 2018 to October 22, 2020, we analyze the dynamic spillover connectedness of returns and realized moments, including realized volatility, realized skewness, and realized kurtosis, during various shock periods via a time-varying parameter vector autoregression (TVP-VAR) connectedness approach. The results show that spillover effects between stock and commodity markets intensify during shock periods such as ‘Trade disputes between China and the United States’ and ‘COVID-19’. Volatility spillovers are relatively stronger;however, higher-order moment spillovers contain additional information of stock-commodity spillovers that cannot be observed from volatility spillovers. Shocks from the silver market influence all three realized moments of the entire financial markets. Soybean, corn, aluminum, and oil markets are easily affected by other markets. The contribution of wheat to the system of spillovers between stock and commodity markets is only observed at higher-order moments. Further analyses involving OLS and quantile regressions show that total spillovers are generally affected by the US stock market and economic uncertainties as well as the COVID epidemic. We construct daily realized volatility, skewness, and kurtosis using 5-min data of eight Chinese commodity futures and the Chinese stock market index from March 26, 2018 to October 22, 2020, then analyse the dynamic spillovers of realized moments among these markets. The results show that the spillover effects between commodity and stock markets intensify during shock periods such as ‘trade disputes between China and the United States’ and ‘COVID-19’. Volatility spillovers are relatively stronger than spillovers in skewness or spillovers in kurtosis;however, spillovers in higher-order moments seem to contain additional information. Shocks from the silver market influence realized moments of other markets. Soybean, corn, aluminium, and oil markets are affected by other markets. The contribution of wheat as a net transmitter to the system of spillovers between stock and commodity markets is only observed at higher-order realized moments. The results from OLS and quantile regressions show that the total spillovers are generally affected by the US stock market, economic uncertainties, and the COVID-19 outbreak.

11.
Asia-Pacific Journal of Business Administration ; 2022.
Article in English | Scopus | ID: covidwho-1922456

ABSTRACT

Purpose: This study aims to investigate the impact of the COVID-19 pandemic on both of stock prices and investor's sentiment in China during the onset of the COVID-19 crisis. Design/methodology/approach: In this study, the ADCC-GARCH model was used to analyze the asymmetric volatility and the time-varying conditional correlation among the Chinese stock market, the investors' sentiment and its variation. The authors relied on Diebold and Yilmaz (2012, 2014) methodology to construct network-associated measures. Then, the wavelet coherence model was applied to explore the co-movements between these variables. To check the robustness of the study results, the authors referred to the RavenPack COVID sentiments and the Chinese VIX, as other measures of the investor's sentiment using daily data from December 2019 to December 2021. Findings: Using the ADCC-GARCH model, a strong co-movement was found between the investor's sentiment and the Shanghai index returns during the COVID-19 pandemic. The study results provide a significant peak of connectivity between the investor's sentiment and the Chinese stock market return during the 2015–2016 and the end of 2019–2020 turmoil periods. These periods coincide, respectively, with the 2015 Chinese economy recession and the COVID-19 pandemic outbreak. Furthermore, the wavelet coherence analysis confirms the ADCC results, which revealed that the used proxies of the investor's sentiment can detect the Chinese investors' behavior especially during the health crisis. Practical implications: This study provides two main types of implications: on the one hand, for investors since it helps them to understand the economic outlook and accordingly design their portfolio strategy and allocate decisions to optimize their portfolios. On the other hand, for portfolios managers, who should pay attention to the volatility spillovers between investor sentiment and the Chinese stock market to predict the financial market dynamics during crises periods and hedge their portfolios. Originality/value: This study attempted to examine the time-varying interactions between the investor's sentiment proxies and the stock market dynamics. Findings showed that the investor's sentiment is considered a prominent channel of shock spillovers during the COVID-19 crisis, which typically confirms the behavioral contagion theory. © 2022, Emerald Publishing Limited.

12.
International Review of Financial Analysis ; : 102169, 2022.
Article in English | ScienceDirect | ID: covidwho-1799888

ABSTRACT

In this study, we construct China's aggregate sentiment indicator (SsPCA) based on the method of Huang et al. (2021a), which employs a new dimension reduction method of scaled principal component analysis (PCA), to aggregate useful information from individual sentiment proxies, and further examine its return predictability for the Chinese stock market. The empirical evidence suggests that SsPCA significantly improves the prediction accuracy for stock market returns both in and out of the sample, and also obtains considerable economic gain for a mean-variance investor. Additionally, the forecasting effect of SsPCA is superior to that of SPCA and SPLS, evaluated using the traditional PCA and partial least square methods, respectively. Moreover, relative to the period of the bull market, SsPCA exhibits better ability in forecasting stock market returns during the bear market. Finally, special events, such as the outbreak of coronavirus disease 2019 (COVID-19), also affect the predictive performance of the sentiment indicator.

13.
Finance Research Letters ; : 102848, 2022.
Article in English | ScienceDirect | ID: covidwho-1773324

ABSTRACT

We investigate short and long-run effects of commodities and the EMVID indices in stocks. It pre-dominantly compares the magnitude of the effect in China and the USA and analyzes the differences utilizing the QARDL method. It becomes evident that the impacts of the EMVID and commodity indexes vary depending on the stock market developments. The short-run results reveal that the US stocks are negatively affected by the extreme quantiles, while almost all quantiles are negatively affected by commodity shocks in the long-run before pandemic. During the COVID-19 outbreak, the EMVID index is positively correlated with the stocks for both countries.

14.
Financ Res Lett ; 46: 102351, 2022 May.
Article in English | MEDLINE | ID: covidwho-1322103

ABSTRACT

In this paper, we investigate the effects of margin purchases and short sales on the return volatility in the Chinese stock market during the COVID-19 outbreak. We present two main findings. First, we show that stocks with higher level of margin-trading activity exhibit higher return volatility. The COVID-19 outbreak amplifies the destabilizing effects of margin-trading activity. Second, no evidence shows that short selling destabilizes the stock market in general. However, we observe that intensified short-selling activity is associated with lower return volatility when infection risk is high during the COVID-19 crisis.

15.
Econ Anal Policy ; 71: 384-396, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-1293739

ABSTRACT

Using a daily foreign and institution flows data, this paper studies how institutional and foreign investors respond to the COVID-19 pandemic events in China. The results indicate that during the COVID-19 crisis foreign investors play a market stabilization role showing significant negative feedback trading, whereas institution investors do not stabilize the market. And compared to the pre-COVID-19 period, foreign investors even exhibit stronger negative feedback trading. Further analyses confirm that foreign investors' negative feedback is mainly driven by their response to negative returns. Moreover, both institutional and foreign investors' trading show stronger forecastability of future returns during the pandemic period. And the negative returns after foreigners' selling and positive returns after institutional buying are much stronger during the crisis period.

16.
Res Int Bus Finance ; 58: 101432, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1253552

ABSTRACT

This study quantitatively measures the Chinese stock market's reaction to sentiments regarding the Novel Coronavirus 2019 (COVID-19). Using 6.3 million items of textual data extracted from the official news media and Sina Weibo blogsite, we develop two COVID-19 sentiment indices that capture the moods related to COVID-19. Our sentiment indices are real-time and forward-looking indices in the stock market. We discover that stock returns and turnover rates were positively predicted by the COVID-19 sentiments during the period from December 17, 2019 to March 13, 2020. Consistent with this prediction, margin trading and short selling activities intensified proactively with growth sentiment. Overall, these results illustrate how the effects of the pandemic crisis were amplified by the sentiments.

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