Academic literature on the topic 'Volatilité (finances) – Chine – 1990-2020'

Commodity exports depend on global demand and prices, but the increasing volatility of real exchange rates (RER) introduces an additional factor. Thus, this paper studies the RER volatility dynamics, estimated through GARCH and IGARCH models for Brazil, Chile, New Zealand, and Uruguay from 1990 to 2013. We study the impact of RER volatility on total exports using Johansen?s methodology, including proxies for global demand and international prices. The results suggest that exports depend positively on global demand and international prices for all countries; however, conditional RER volatility resulted significant and negative only for Uruguay, in the short- and long-run.

Thailand is a significant global exporter of cassava, of which cassava chips are the main export products. Moreover, China was the most important export market for Thailand from 2000 to 2020. However, during that period, Thailand confronted fluctuations in the cassava product price, and cassava chips were a product with significant price volatility, adapting to changes in export volumes. This study aims to analyze the volatility of the price of cassava chips in Thailand from 2010 to 2020. The data were collected monthly from 2010 to 2020, including the price of cassava chips in Thailand (Y), the volume of cassava China imported from Thailand (X1), the price of the cassava chips that China imported from Thailand (X2), the price of the cassava starch that China imported from Thailand (X3), the substitute crop price for maize (X4), the substitute crop price for wheat (X5), and Thailand’s cassava product export volume (X6). The volatility and the factors affecting the volatility in the price of cassava chips were calculated using Bayesian GARCH-X. The results indicate that the increase in X1, X2, X3, X4, and X6 led to an increase in the rate of change in cassava chip price volatility. On the other hand, if the substitute crop price for wheat (X5) increases, then the rate of change in the volatility of the cassava chip price decreases. Therefore, the government’s formulation of an appropriate cassava policy should take volatility and the factors affecting price volatility into account. Additionally, the government’s formulation of agricultural policy needs to consider Thailand’s macro-environmental factors and its key trading partners, especially when these environmental factors signal changes in the price volatility of cassava.

The study of forecasting volatility of stocks has been discussed and investigated among scholars. Volatility plays important role in determining stock value as well as portfolio in stock market. This study investigates the use of GARCH model (generalized autoregressive conditional heteroskedasticity) in forecasting Islamic index stock in Asian countries. This study employs data from yahoo. finance including six countries namely India, Singapore, Japan, China, Malaysia, and Indonesia. There are 1304 data observation of daily closing price for the period between January 2016 and December 2020. The results of the study show that GARCH model can be employed as a mediation of forecasting sharia indexed stock. This implies that GARCH model can be used as forecasting steps in Islamic stock in Asian countries. Investors can take into account the model of GARCH in forecasting of Islamic stock market in Asian countries particularly India, Japan, China, Singapore, Malaysia and Indonesia

ABSTRAK Penelitian ini bertujuan untuk menguji spillover effect indeks saham syariah Amerika Serikat dan Cina terhadap indeks saham syariah ASEAN dengan menggunakan metode Nonlinier Autoregressive Distributed Lag (NARDL) untuk menemukan spillover effect yang bersifat asimetris selama pandemi Covid-19. Data yang diamati dimulai pada 1 Januari 2020 sampai dengan 30 September 2021 dengan total observasi sebanyak 336 data untuk masing-masing indeks saham. Penelitian ini mendapatkan beberapa temuan. Pertama, indeks saham syariah Amerika Serikat dan Cina memiliki pengaruh asimetris jangka pendek terhadap indeks saham syariah Indonesia, Malaysia dan Thailand selama pandemi Covid-19. Kedua, indeks saham syariah Amerika Serikat dan Cina hanya memiliki pengaruh asimetris jangka panjang terhadap indeks saham syariah Malaysia selama pandemi Covid-19. Ketiga, efek ketika terjadi penurunan indeks saham syariah Amerika Serikat dan Cina lebih besar dibandingkan pada saat terjadi kenaikan terhadap indeks saham syariah Malaysia selama pandemi Covid-19. Salah satu penyebab hubungan tersebut adalah karena adanya hubungan dagang yang sangat erat antara Amerika Serikat dan Cina terhadap Malaysia. Adapun implikasi dari penelitian ini adalah investor internasional dapat menjadikan hasil penelitian ini sebagai bahan pengambilan keputusan apabila terjadi kontraksi akibat krisis seperti pada saat pandemi Covid-19 terhadap indeks saham syariah Amerika Serikat dan Cina untuk mempertahankan maupun menjual portofolio investasi mereka. Kata Kunci: Spillover, Indeks Syariah, Asimetris, Covid-19. ABSTRACT This study aims to examine the spillover effect of Islamic stock indexes of the United States and China on the ASEAN Islamic stock index using the Nonlinear Autoregressive Distributed Lag (NARDL) method to find asymmetric spillover effects during the Covid-19 pandemic. The observed data starts on January 1, 2020, until September 30, 2021, with a total of 336 observations for each stock index. This study found some findings. First, the Islamic stock indexes of the United States and China have a short-term asymmetric influence on the Islamic stock indices of Indonesia, Malaysia, and Thailand during the Covid-19 pandemic. Second, the Islamic stock indexes of the United States and China have only a long-term asymmetric influence on Malaysia's sharia stock indexes during the Covid-19 pandemic. Third, the effect when there is a decline in Islamic stock indexes of the United States and China is greater than when there is an increase in the Malaysian sharia stock index during the Covid-19 pandemic. One of the reasons for this relationship is the very close trade relationship between the United States and China with Malaysia. The research implication of this study is that international investors can use the results of this research as a decision-making material in the event of a contraction due to the crisis (one of which is the Covid-19 pandemic) in the United States and China Islamic stock indexes to maintain or sell their investment portfolios. Keywords: Spillover, Islamic Index, Asymmetric, Covid-19. DAFTAR PUSTAKA Abdullahi, S. I. (2021). Islamic equities and covid-19 pandemic: Measuring Islamic stock indices correlation and volatility in period of crisis. Islamic Economic Studies, 29(1), 50-66. https://doi.org/10.1108/IES-09-2020-0037 Aslam, F., Mohmand, Y. T., Ferreira, P., Memon, B. A., Khan, M., & Khan, M. (2020). Network analysis of global stock markets at the beginning of the coronavirus disease (covid-19) outbreak. Borsa Istanbul Review, 20, 49–61. https://doi.org/10.1016/j.bir.2020.09.003 Azhar, J. A., Wulandari, R., & Kalijaga, U. I. N. S. (2021). Stock performance based on sharia stock screening: Comparasion between syariah stock indices of Indonesia and Malaysia. 1(1), 14–26. https://doi.org/10.20885/AMBR.vol1.iss1.art2 Baek, S., Mohanty, S. K., & Glambosky, M. (2020). Covid-19 and stock market volatility: An industry level analysis. Finance Research Letters, 37(January), 1-10. https://doi.org/https://doi.org/10.1016/j.frl.2020.101748 Dizioli, A., Guajardo, J., Klyuev, VladimirMano, R., & Raissi, M. (2016). Spillovers from China’s growth slowdown and rebalancing to the ASEAN-5 economies. IMF Working Papers, 16(170), 1. https://doi.org/10.5089/9781475524260.001 Forbes, K. J., & Rigobon, R. (2002). No contagion, only interdependence: Measuring stock market comovements. Journal of Finance, 57(5), 2223–2261. https://doi.org/10.1111/0022-1082.00494 Hasan, M. B., Mahi, M., Sarker, T., & Amin, M. R. (2021). Spillovers of the covid-19 pandemic: Impact on global economic activity, the stock market, and the energy sector. Journal of Risk and Financial Management, 14(5), 200. https://doi.org/10.3390/jrfm14050200 He, Q., Liu, J., Wang, S., & Yu, J. (2020). The impact of covid-19 on stock markets. Economic and Political Studies, 0(0), 275–288. https://doi.org/10.1080/20954816.2020.1757570 Hung, N. T. (2019). Return and volatility spillover across equity markets between China and Southeast Asian countries. Journal of Economics, Finance and Administrative Science, 24(47), 66–81. https://doi.org/10.1108/JEFAS-10-2018-0106 International Monetary Fund. (2021). Fault lines widen in the global recovery. World Economic Outlook Update, July 2021, 1–21. 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Retrieved from http://www.fruitnet.com/asiafruit/article/184345/record-trade-between-malaysia-and-china Lee, H. Y. (2012). Contagion in international stock markets during the sub prime mortgage crisis. International Journal of Economics and Financial Issues, 2(1), 41–53. Lee, K.-J., Lu, S.-L., & Shih, Y. (2018). Contagion effect of natural disaster and financial crisis events on international stock markets. Journal of Risk and Financial Management, 11(2), 16. https://doi.org/10.3390/jrfm11020016 Lento, C., & Gradojevic, N. (2021). S&P 500 index price spillovers around the covid-19 market meltdown. Journal of Risk and Financial Management, 14(7), 330. https://doi.org/10.3390/jrfm14070330 Liu, H., Manzoor, A., Wang, C., Zhang, L., & Manzoor, Z. (2020). The covid-19 outbreak and affected countries stock markets response. International Journal of Environmental Research and Public Health, 17(8), 1–19. https://doi.org/10.3390/ijerph17082800 Marçal, E. F., Prince, D. de, Zimmermann, B., Merlin, G., & Simões, O. (2020). Assessing global economic activity linkages: The role played by United States, Germany and China. EconomiA, 21(1), 38–56. https://doi.org/10.1016/j.econ.2020.01.001 Mata, M. N., Razali, M. N., Bentes, S. R., & Vieira, I. (2021). Volatility spillover effect of Aan-Asia’s property portfolio markets. Mathematics, 9(12), 1–20. https://doi.org/10.3390/math9121418 McMillan, D. G. (2020). Interrelation and spillover effects between stocks and bonds: Cross-market and cross-asset evidence. Studies in Economics and Finance, 37(3), 561-582. https://doi.org/10.1108/SEF-08-2019-0330 Panjaitan, Y., & Novel, R. (2021). Volatility spillover among Asian developed stock markets to Indonesia stock market during pandemic covid-19. Jurnal Keuangan dan Perbankan, 25(2), 342–354. https://doi.org/10.26905/jkdp.v25i2.5532 Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16, 289–326. Purbasari, I. (2019). Volatility spillover effects from the US and Japan to the ASEAN-5 markets and among the ASEAN-5 markets. Sains: Jurnal Manajemen dan Bisnis, 11(2), 293-331. https://doi.org/10.35448/jmb.v11i2.6064 Rahmayani, D., & Oktavilia, S. (2021). Does the covid-19 pandemic affect the stock market in Indonesia? Jurnal Ilmu Sosial dan Ilmu Politik, 24(1), 33–47. https://doi.org/10.22146/JSP.56432 Ramdhan, N., Yousop, N. L. M., Ahmad, Z., Abdullah, N. M. H., & Zabizi, A. Z. (2016). Stock market integration: The effect of leader and emerging market. Journal of Advanced Research in Business and Management Studies, 2(1), 1–10. Saleem, A., Bárczi, J., & Sági, J. (2021). Covid-19 and Islamic stock index: Evidence of market behavior and volatility persistence. Journal of Risk and Financial Management, 14(8), 389. https://doi.org/10.3390/jrfm14080389 Sari, L. K., Achsani, N. A., & Sartono, B. (2017). Volatility transmission of the main global stock return towards Indonesia. Bulletin of Monetary Economics and Banking, 20(2), 229–254. https://doi.org/10.21098/bemp.v20i2.813 Sekaran, U., & Bougie, R. (2018). Metode penelitian untuk bisnis. Jakarta: Salemba Empat. Setiawan, A., & Kartiasih, F. (2021). Contagion effect of Argentina and Turkey crisis to Asian countries, is it really happening? Jurnal Ekonomi dan Pembangunan Indonesia, 21(1), 59–76. https://doi.org/10.21002/jepi.v21i1.1333 Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2012). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. SSRN Electronic Journal, 1–61. https://doi.org/10.2139/ssrn.1807745 Suppakittiwong, T., & Aimprasittichai, S. (2015). A study of a relationship between the U.S. stock market and emerging stock markets in Southeast Asia. Unpublished undergraduate thesis. Sweden: Linnaeus University. Sznajderska, A., & Kapuściński, M. (2019). The spillover effects of chinese economy on Southeast Asia and Oceania. NBP Working Paper Issue 315. Retrieved from https://www.nbp.pl/publikacje/materialy_i_studia/315_en.pdf Thai Hung, N. (2019). Equity market integration of China and Southeast Asian Countries: Further Evidence from MGARCH-ADCC and wavelet coherence analysis. Quantitative Finance and Economics, 3(2), 201–220. https://doi.org/10.3934/qfe.2019.2.201 Thomson Reuters Practical Law. (2021). International trade in goods and services in Malaysia: Overview. Retrieved from https://uk.practicallaw.thomsonreuters.com/w-017-9602?transitionType=Default&contextData=(sc.Default)&firstPage=true Trade between Malaysia and China reached new high in 2020 despite Covid. (2021). Retrieved from https://www.freshplaza.com/article/9293748/trade-between-malaysia-and-china-reached-new-high-in-2020-despite-covid/ United States Census Bureau. (2021). Trade in goods with Malaysia. Retrieved from https://www.census.gov/foreign-trade/balance/c5570.html Vo, X. V., & Tran, T. T. A. (2019). Modelling volatility spillovers from the US equity market to ASEAN stock markets. Pacific Basin Finance Journal, 59(February 2020), https://doi.org/10.1016/j.pacfin.2019.101246 Wang, Q., & Han, X. (2021). Spillover effects of the United States economic slowdown induced by COVID-19 pandemic on energy, economy, and environment in other countries. Environmental Research, 196(February). https://doi.org/10.1016/j.envres.2021.110936 Wycislak, S. (2014). Contagion effect and organization. European Scientific Journal, 10(1), 17–26. https://doi.org/10.19044/esj.2014.v10n1p%25p Yan, B., Stuart, L., Tu, A., & Zhang, Q. (2020). Analysis of the effect of covid-19 on the stock market and investing strategies. SSRN Electronic Journal. https://doi.org/10.2139/SSRN.3563380 Yan, C. (2020). COVID-19 Outbreak and stock prices: Evidence from China. SSRN Electronic Journal. https://doi.org/10.2139/SSRN.3574374 Yujing, O. (2021). China-Malaysia diplomatic relations – sailing towards a brighter future. Retrieved from https://www.thestar.com.my/opinion/letters/2021/05/31/china-malaysia-diplomatic-relations---sailing-towards-a-brighter-future

This paper investigates the dynamic tail dependence risk between BRICS economies and the world energy market, in the context of the COVID-19 financial crisis of 2020, in order to determine optimal investment decisions based on risk metrics. For this purpose, we employ a combination of novel statistical techniques, including Vector Autoregressive (VAR), Markov-switching GJR-GARCH, and vine copula methods. Using a data set consisting of daily stock and world crude oil prices, we find evidence of a structure break in the volatility process, consisting of high and low persistence volatility processes, with a high persistence in the probabilities of transition between lower and higher volatility regimes, as well as the presence of leverage effects. Furthermore, our results based on the C-vine copula confirm the existence of two types of tail dependence: symmetric tail dependence between South Africa and China, South Africa and Russia, and South Africa and India, and asymmetric lower tail dependence between South Africa and Brazil, and South Africa and crude oil. For the purpose of diversification in these markets, we formulate an asset allocation problem using raw returns, MS GARCH returns, and C-vine and R-vine copula-based returns, and optimize it using a Particle Swarm optimization algorithm with a rebalancing strategy. The results demonstrate an inverse relationship between the risk contribution and asset allocation of South Africa and the crude oil market, supporting the existence of a lower tail dependence between them. This suggests that, when South African stocks are in distress, investors tend to shift their holdings in the oil market. Similar results are found between Russia and crude oil, as well as Brazil and crude oil. In the symmetric tail, South African asset allocation is found to have a well-diversified relationship with that of China, Russia, and India, suggesting that these three markets might be good investment destinations when things are not good in South Africa, and vice versa.

Investor sentiment is the result of trading behavior and irrational beliefs of investors leading to high volatility and market mispricing. This review aims to study the entire spectrum of articles in the domain of investor sentiment using a bibliometric analysis approach. To this end, the study analyzes a total of 1,919 articles published in the Scopus database between 1979 and 2022. The review uncovers major themes, leading authors, influencing articles, trend topics, top contributing countries, and affiliations. The review shows that the research in the domain of investor sentiment is growing exponentially with an annual growth rate of 15.88%, and the year 2020 witnessed the highest number of scientific productions accounting for 252 (13.68%) total publications. The results display that the USA and China are leading countries in terms of the total contribution and volume of studies from respective authors. The review also reveals that existing research in the field has mainly focused on themes such as market efficiency, asset pricing, stock returns, sentiment analysis, IPO underpricing, overreaction, and volatility, whereas Covid-19 and Bitcoin depicted as emerging themes from recent scholarly works.

The advent of the VUCA era and the development of digital finance (DF) present opportunities and challenges for manufacturing companies to seek sustainable innovation by increasing their organizational resilience (OR) to withstand crises. The production, flow, and acquisition of corporate knowledge are indispensable to the establishment of organizational resilience. In this paper, we analyze how to make manufacturing enterprises more courageous and innovative in the context of digital finance. We used a perspective of knowledge channel acquisitions to achieve this aim. Using a sample of 1965 manufacturing companies in China from 2013 to 2020, we analyzed whether greater enterprise knowledge (internal knowledge and external knowledge) can yield higher levels of innovation performance and whether organizational resilience plays a role in the context of digital finance. The results show that (1) both internal enterprise knowledge (IEK) and external enterprise knowledge (EEK) have a significant positive impact on the sustainable innovation performance of manufacturing enterprises; (2) organizational resilience has a mediation role in the process of promoting sustainable innovation performance through enterprise knowledge; (3) digital finance significantly enhances the impact of enterprise knowledge on long-term growth and financial volatility of organizational resilience, and significantly positively moderates the mediation effect of organizational resilience; and (4) digital finance support policies issued by the government significantly improve the sustainable innovation performance of manufacturing firms. Based on these results, manufacturing firms can improve innovation performance by enhancing organizational resilience. This paper contributes to this field of research by providing an analysis of manufacturing firms, presenting a new view on the improvement of innovation performance in the context of digital finance.

Since the first case was reported at the end of 2019, COVID-19 has spread throughout the world resulting in more than 2 million confirmed cases. The World Health Organization (WHO) also declared the COVID-19 disease as pandemic on 11 March 2020. The COVID-19 pandemic has also affected the global financial market, which includes Malaysia. This study aims to investigate the impact of the COVID-19 outbreak on the Malaysian stock market. The dependent variables used in this study were the Kuala Lumpur Composite Index (KLCI) and 13 other sectorial indices. The independent variables were (i) the number of COVID-19 cases in Malaysia, China, and USA; (ii) the number of deaths due to COVID-19 in Malaysia, China, and USA; (iii) the volatility index, and (iv) the Brent oil price. The sample period of this study covered from 31st December 2019 to 18th April 2020. The findings showed that higher numbers of COVID-19 cases in Malaysia tended to adversely affect the performance of the KLCI index and all sectorial indices, except for the Real Estate Investment Fund (REIT) index. The results also showed that the Brent oil price and the volatility index tended to affect the Malaysian stock market performance. The results of this study can help investors understand the impact of COVID-19 on different sectors in Malaysia.

With the continuous increase of China’s foreign-trade dependence on crude oil and the accelerating integration of the international crude oil market and the Chinese finance market, the spillover effect of international oil price fluctuation on China’s stock markets increasingly attracts the attention of the public. In order to explore the impact of international oil price fluctuation on China’s stock markets and the time-varying spillover differences of industry sectors, this study proposes three research hypotheses and constructs a multi-time scale analysis framework based on wavelet analysis and a time-varying t-Copula model. In this paper, we use the Shanghai Composite Index as the representative of a general trend of the stock market, and we use the stock index of the China Securities Industry as the counterpart of industrial sectors. Based on the data from 5 January 2005 to 31 May 2020, this paper measures and analyzes the spillover effect of international oil price fluctuation on China’s stock markets, under different volatility periods. The results show that, firstly, the spillover effect of international oil price fluctuation on the Chinese stock markets is different. In the short and medium volatility period, the changes in international oil price are ahead of the changes in the Chinese stock markets, while the latter is ahead of the former under long-term fluctuations. Secondly, the spillover effect of international oil price fluctuation on China’s industry stock indexes is persistent. As the time scale increases, the tail dependency will increase. Finally, the impact of risk events aggravates the volatility of the stock markets in the short-term, while the mid- to long-term impact mainly affects the volatility trend. Investment risk control can make overall arrangement on the basis of the characteristics of oil price impact under different fluctuation stages.

Purpose Recent empirical studies by Antonakakis, Chatziantoniou and Filis (2013), Brogaard and Detzel (2015) and Christou et al. (2017) present evidence, which supports the notion that a rise in economic policy uncertainty (EPU) will lead to a decline in stock prices. The purpose of this paper is to examine US categorical policy uncertainty on stock returns while controlling for implied volatility and downside risk. In addition to the domestic impacts of policy uncertainty, this paper also presents evidence that changes in US policy uncertainty promptly propagates to the global stock markets. Design/methodology/approach This study uses a GED-GARCH (1, 1) model to estimate changes of uncertainties in US monetary, fiscal and trade policies on stock returns for the sample period of January 1990–December 2018. Robustness test is conducted by using different set of data and modeling techniques. Findings This paper contributes to the literature in several aspects. First, testing of US aggregate data while controlling for downside risk and implied volatility, consistently, shows that responses of stock prices to US policy uncertainty changes, not only display a negative effect in the current period but also have at least a one-month time-lag. The evidence supports the uncertainty premium hypothesis. Second, extending the test to global data reveals that US policy uncertainty changes have a negative impact on markets in Europe, China and Japan. Third, testing the data in sectoral stock markets mainly displays statistically significant results with a negative sign. Fourth, the evidence consistently shows that changes in policy uncertainty present an inverse relation to the stock returns, regardless of whether uncertainty is moving upward or downward. Research limitations/implications The current research is limited to the markets in the USA, eurozone, China and Japan. This study can be extended to additional countries, such as emerging markets. Practical implications This paper provides a model that uses categorical policy uncertainty approach to explain stock price changes. The parametric estimates provide insightful information in advising investors for making portfolio decision. Social implications The estimated coefficients of changes in monetary policy uncertainty, fiscal policy uncertainty and trade policy uncertainty are informative in assisting policymakers to formulate effective financial policies. Originality/value This study extends the existing risk premium model in several directions. First, it separates the financial risk factors from the EPU innovations; second, instead of using EPU, this study investigates the effects from monetary policy, fiscal policy and trade policy uncertainties; third, in additional to an examination of the effects of US categorical policy uncertainties on its own markets, this study also investigates the spillover effects to global major markets; fourth, besides the aggregate stock markets, this study estimates the effects of US policy uncertainty innovations on the sectoral stock returns.

This chapter examines the relationship between the water sector of the equity markets. It includes the world market and markets of different individual countries such as China, Hong Kong, Singapore, Germany, France, the UK, Brazil, Chile, and the US for the period 2001-2020. Investment returns and volatility of these markets are analyzed to understand investment decision-making in these water markets. The OLS and quantile regressions show that China, Hong Kong, Singapore, Germany, France, the UK, Brazil, Chile, and the US are positively related to the world market. The results confirm simultaneous interactions between the world market and the other nine markets. The ARMA (1,1)-GARCH (1,1) model shows a high degree of persistency in the conditional volatility of stock returns for these water markets which means “explosive” volatility. Moreover, the VAR analyses show that the nine markets positively and negatively affect the world market. The findings may assist the international institutions while deciding investment in water portfolios.