Sectoral Stock Indices Research Articles

Volatility Spillover Effects in the Moroccan Interbank Sector before and during the COVID-19 Crisis

The objective of this paper is to analyze the volatility spillover effects in the Moroccan interbank sector before and during the COVID-19 pandemic crisis using the DY model. Specifically, this study assesses the impact of the recent COVID-19 outbreak on the transmission of volatility among Moroccan banks listed in the Moroccan stock market. The data sample frequency is daily and extends from 1 January 2012 to 31 December 2021, excluding holidays. The empirical results indicate that the volatility spillover index increased during the pandemic crisis. We also found varying degrees of interdependence and spillover effects between the six publicly traded Moroccan banks and the Moroccan banking sector stock index before and during the COVID-19 pandemic crisis.

Nonlinear dependence between China's carbon market and stock market: new evidence from quantile coherency and causality-in-quantiles.

This study examines the nonlinear dependence between carbon market and stock market in China under normal and extreme market conditions by employing two novel nonlinear approaches, namely, quantile coherency and causality-in-quantiles methods. Given our results on the overall and sector level of stock market, we find that there is a negative dependence between the two markets under bearish and normal market states in the short- and medium-term respectively, while the dependence becomes positive under bearish and bullish market states in the long-term. Furthermore, we also prove that the Granger causality from carbon market to stock market exists. However, no evident impacts from stock market to carbon market have been found. Additionally, at sector stock market, we discover heterogeneity across market conditions. And emission-intensive sector stock indices are more affected by carbon prices.

How COVID-19 Influences Indian Sectoral Stocks

Studies have documented the strong effect of the COVID-19 pandemic on different world economies. In this study, we examine the influence of COVID-19 cases in India on the country’s sectoral stock indices. Our results find that COVID-19 has had a negligible influence on the returns of these stocks; however, it causes them to fluctuate significantly. We provide insights for the government and local and international investors.

External Shocks and Volatility Overflow among the Exchange Rate of the Yen, Nikkei, TOPIX and Sectoral Stock Indices

In this paper, we examined the changes in volatility overflow among the exchange rate of the Japanese yen (JPY), the Nikkei Stock Average (Nikkei), the Tokyo Stock Price Index (TOPIX) and the TOPIX sectoral indices for the period of 10 February 2016 to 24 March 2017. We employed the exponential generalised autoregressive conditional heteroscedasticity (EGARCH) model, the cross-correlation function, and the daily logarithmic returns of JPY, Nikkei, TOPIX and the TOPIX components with a weight of 5% and more in estimations (banks, chemicals, electric appliances, information and communication, machinery and transportation equipment indices). The findings highlighted causality in variance (volatility spillover) among the variables. We revealed that volatility could also spread indirectly among the variables (from one variable to another through a third variable). We demonstrated how the impact of news about the results of the Brexit referendum (BR) and the United States presidential election (USE) in 2016 might spread among the variables indirectly within a week.

Volatility of Technology and Healthcare Sectors Before and During Covid-19 Pandemic

The study investigates the effect of the Covid-19 on the volatility of the technology and healthcare sector stock index in Malaysia. The two sectors pose considerable attention during the pandemic due to the increase in demand for healthcare products and digital services. The volatilities are estimated using the GARCH model for the period before and after the implementation of the nationwide movement order control using daily data from September 2019 to September 2020. The finding shows that the Covid-19 pandemic caused a volatility jump for the technology sector index in March 2020 but subsided afterward with estimated conditional volatility revert to normal in the middle of April 2020. However, during the high uncertainty period, the healthcare sector shows a steady increase in volatility beginning in March 2020 till the end of September 2020. The study confirms that there is a significant difference in the volatility of healthcare and technology sectors before and during the Covid-19 outbreak. The outbreak has a significant impact on increasing the volatilities for both sectors but is impacted in different magnitude.

Turizm Endeks Getirileri Arasındaki Oynaklık Geçişkenliği: BIST Turizm Endeksi ve Bazı Avrupa Ülkeleri Turizm Endeksleri Uygulaması

Turkey is one of the important countries in Europe in terms of tourism sector. In Turkey, which is in competition with the European Union countries Italy, Spain and Greece in terms of the tourism sector, the volatility of the volatility of the tourism sector stock indices in this competitive environment is also an important situation. The aim of this study is to reveal the effects of volatility of Spain tourism index BCNR.BC, Italy tourism index FTITLMS and Greece tourism index FTATTRA on Turkish tourism index volatility. In the study, the volatility spread between variables was analyzed using the daily return series between 19.06.2015-19.06.2020 with the BEKK-GARCH model. According to the empirical findings obtained, a bidirectional volatility spread from the BIST tourism index to the BIST tourism index, from the FTATTRA index to theFTATTRA index, was found. In addition, there is a one-way volatility interaction from the FTITLMS and BCNRBC indices to the BIST tourism index. No volatility interaction was found from BIST tourism index to FTITLMS and BCNRBC indices.

Asymmetric Impact of Bitcoin Sentiments on Sectoral Stock Returns

This study cross-checks the symmetric and asymmetric effects of investor’s optimistic and pessimistic sentiments of Bitcoin on 23 sectoral stock return indices (10 Islamic stock sectoral indices and one composite Islamic market index by Dow Jones Islamic market and 12 industrial indices by Kenneth R French). Results of Autoregressive Distributed Lag (ARDL) and Nonlinear ARDL models are supporting our conjecture that when investors’ are being optimistic (pessimistic) to Bitcoin they move part of their funds from stocks (Bitcoin) to Bitcoin (stocks). Second, we found asymmetric effects of both sentiment indices on the Islamic stock indices and conventional stock indices. Third, we found support for the decoupling hypothesis as Bitcoin sentiments are affecting conventional stock indices more than Islamic stock indices. Fourth, investors’ optimistic sentiments are robust than pessimistic sentiments explaining sectoral stock return indices. Fifth, insignificance of OBSI and PBSI in most of the sectoral stock indices are evidencing the hedging opportunity for Bitcoin investors.

Oil Volatility Spillover into Oil Dependent Equity-Sector Stock Returns: Evidence from Major Oil Producing Countries

In this paper, we study the effects of oil price volatility on the stock market relevant sectors from several oil producing countries. We investigate the interdependence between oil prices and sector stock indices within OPEC markets and selected major non-OPEC countries such as Russia and United States. By exploring the time-varying dynamics of oil prices and sector-stock indices on the sectoral reaction to oil price shocks we investigate how the shocks in oil prices affect the correlation dynamics of the different sectors. Our study finds that different sectors display heterogeneous dynamic correlation pattern with different oil price shocks origins in different countries. Specifically, the GARCH coefficients in several sectors, such as, industrial, energy and healthcare in some of oil-producing middle-eastern countries are not significant. In addition, the negative coefficients for some sectors in some of the countries indicate the existence of hedging opportunities for portfolio managers.

Stock Market Linkages between the Asean Countries, China and the US: A Fractional Integration/cointegration Approach

ABSTRACT This paper examines stock market integration between the five ASEAN countries and both the US and China in turn, over the period from November 2002 to August 2020. The linkages between both aggregate and financial sector stock indices (both weekly and monthly) are analyzed using fractional integration and fractional cointegration methods. Further, recursive cointegration analysis is carried out for the weekly series to study the impact of the 2007–8 global financial crisis and the 2015 China stock market crash on the pattern of stock market co-movement. The main findings are the following. All stock indices exhibit long-range dependence. There is cointegration between the five ASEAN countries and the US but almost none between the former and China, except between Indonesia and China in the case of the financial sector. The 2007–8 global financial crisis and the 2015 Chinese stock market plunge weakened the linkages between the ASEAN five and both China and the US. The implications of these results for market participants and policy makers are discussed.

Investigating the nexus between European major and sectoral stock indices, gold and oil during the COVID-19 pandemic.

This paper investigates the dynamic conditional linkages between the Eurostoxx50, and the Eurostoxx600 and its sub-indices with COVID-19 deaths, gold, and crude oil. The Dynamic Conditional Correlations (DCC) methodology is employed and the period examined spans from 22 January 2020 until 10 July 2020. Econometric outcomes reveal that the European stock indices are modestly-to-strongly linked with gold in a positive direction and this prevents them from abrupt falls during the pandemic. Nevertheless, weak positive linkages of indices with oil are detected. Sectors of major importance such as the energy sector, financial services, banks, automobiles and parts, and basic resources are mostly influenced by gold and oil. Notably, the impact of COVID-19 deaths on major European markets is rather indirect. These findings inform interested investors in order to ameliorate their risk–return tradeoff during the pandemic bear market.Supplementary InformationThe online version contains supplementary material available at 10.1007/s43546-021-00060-x.

Volatility Spillovers and Correlations between Oil Prices and Stock Sectors in Turkey: Implications on Portfolio Hedging and Diversification Opportunities

This study investigates volatility spillover effects as well as hedging and diversification opportunities between sectoral stock returns and world crude oil prices in Turkey using the weekly closing prices of the BIST 100 and twenty-three sectoral stock indices for the period 2002-2018. DCC modelling is employed to investigate volatility spillovers between sectoral stock returns and oil prices. Findings reveal significant volatility spillovers from the oil market to the BIST 100 and twelve stock sectors. Furthermore, optimal hedge ratios, optimal portfolio weights, hedging effectiveness, diversification effectiveness and risk-adjusted returns of oil-stock portfolios are computed and compared. The results indicate that diversification is a more effective strategy than hedging in terms of risk (variance) reductions and risk-adjusted returns in the Turkish stock market.

US Policy Responses to the COVID-19 Pandemic and Sectoral Stock Indices: A Fractional Integration Approach

This paper uses fractional integration methods to assess the impact of US policy responses (containment and health measures, income support policy, debt-relief policy, changes in the Effective Federal Funds Rate, monetary and fiscal announcements) to the COVID-19 pandemic on US sectoral stock indices for Technology, Telecom, Health Care, Real Estate, Consumer Staples, Consumer Discretionary, Industrials, Basic Materials, Energy and Utilities from 1 January 2020 to 11 June 2021. The results provide evidence of mean reversion for seven sectoral stock indices (Consumer Discretionary, Consumer Staples, Health, Industrials, Technology, Telecom and Utilities), with orders of integration significantly below (though close to) 1 under the assumption of white noise errors. By contrast, three indices (Basic Materials, Energy and Real Estate) are found to be highly persistent (d ≥ 1), with shocks having permanent effects. As for the policy responses, it appears that the containment and health restrictions, income support policy, and debit relief policy have had no impact. By contrast, changes in the Effect Federal Funds Rate have had a significant and positive effect on all sectors except Energy and Industrial, and similarly monetary and fiscal announcements have had a positive and significant effect in most cases. Finally, the higher mortality rate caused by the Covid-19 pandemic has affected negatively most sectoral stock indices.

A multi-criteria decision-making approach to rank the sectoral stock indices of national stock exchange of India based on their performances

<abstract> The ideal sector for an investment is a challenge for any capital market investor. This complexity is primarily attributed to the dynamic and volatile nature of public policies and macroeconomic factors that indirectly impact a sector's growth. In recent years, India in particular, has witnessed dynamic policies being implemented by the Government, such as Demonetization and Goods and Services Tax (GST), which led to sudden changes in the market forces. Thus, it is imperative that researchers focus on developing new scientific techniques for selecting the ideal sector to invest in capital markets. Understanding and analyzing a sector's behaviour is of prime importance to investors in any emerging capital market. This task appears to be complex as an investor needs to decide from a diverse set of sectors, where performance ranking can conflict with another for different variables. A volatile sector might be ranked higher on pure returns but would be ranked lower if risk-adjusted performance was considered. This is commonly referred to as a multiple criteria decision-making (MCDM) problem. In this paper, we consider the data of eleven Nifty sectoral indices from the National Stock Exchange (NSE) of India from January 2017 to December 2018. We apply three MCDM methods—COPRAS, SAW, and TOPSIS to rank the sectors and provide a holistic overview of their performance. Additionally, we propose a hybrid-ranking approach to solve the issue of divergent rankings from different MCDM techniques. We conclude that Nifty Financial service is the best performer in this volatile period. Once the rankings were obtained, we confirmed our results with actual fundamental events that took place in the economy. Through our research, potential investors can utilize our technique to rank the performance of sectoral indices for their specific region at any given time period. </abstract>

Volatility spillover impact of FII and MF net equity flows on the Indian sectoral stock indices: recent evidence using BEKK-GARCH

Volatility spillover impact of FII and MF net equity flows on the Indian sectoral stock indices: recent evidence using BEKK-GARCH

DETERMINANT ANALYSIS OF FINANCIAL SECTOR STOCK IN INDONESIA STOCKS EXCHANGE

These research had purposed to examine related to macroeconomic variables on financial sector stock index in Indonesia Stock Exchange. This research used Vector Error Correction Model (VECM) method with monthly data from financial sector stock index as the dependent variable and the GDP quarterly data, as well as monthly data on inflation, BI interest rates, exchange rates, the Fed interest rate, gold prices, oil prices,and also the S&amp;P 500 index as independent variable with data range from January 2014 to August 2019. These results that obtained from this research were the shocks in BI interest rate variable and the exchange rate which have positive responses in the long term, while the GDP, inflation, and Fed interest rates , gold prices, oil prices, and the S&amp;P 500 index responded negatively in the long term by the financial sector stock index. Beside that, the BI interest rate variable has the greatest contribution in changed of financials stock index.

DETERMINANT ANALYSIS IN PROPERTY STOCKS INDEX AT INDONESIA STOCK EXCHANGE

This research aims to determine those influence of inflation, interest rates, exchange rates, world oil prices and world gold prices against the property sector stock index which registered In Indonesia Stock Exchange. These population of research were all activities from monthly movement of property sector stock index, inflation, exchange rates, BI interest rates, world oil prices and world gold prices. The sample chosen method by purposive sampling where the researcher gathered its data based on proficiency strategies or personal considerations, selecting data based on these following criteria: 1) Availability of macro economic data that affects shares from property sector during January 2016 to December 2019; and 2) Availability of property stock index data from January 2016 till December 2019. The model used in this research was the Vector Error Correction Model (VECM). With The results showed that: 1) ISP responsiveness to inflation movements where stumbled or shocks that occur on inflation had positive influence towards ISP movements; 2) Responsiveness of ISP to instability or shocks that occur in exchange rates will negatively affect ISP movements; 3) Those responsiveness of ISP to the BI rate movement was responded positively; 4) Based on these results from research conducted, the ISP responded negatively on stumbled or shocks towards oil price movements; and 5) ISP responsiveness to movements or shocks to gold price had been responded positively by the ISP.

The Determinant of Mining Sector Stock Price Index at Indonesia Stock Exchange

This research has purposed to analyze these determinants from mining sector stock index at Indonesia Stock Exchange. This research used the Vector Error Correction Model and monthly data on mining sector stock index as dependent variable and the independent variables were inflation, BI interest rate, Gross Domestic Product, exchange rate, demand and supply of coal, coal prices and world crude oil prices from January 2014 to August 2019. These empirical results shows that shocks variable on inflation, coal supply & demand, coal prices and crude oil prices will be responded positively by mining sector stock index in the long term while shocks variable on GDP, BI interest rates and exchange rates will be responded negatively by mining sector stock index in long-term. It means all variables are determinant of mining sector stock price index at IDX. Coal demand variable would contribute dominantly to the fluctuation of mining sector stock index. The increased in coal demand will be followed by increased in mining sector stock index.

Causality-in-quantiles between crude oil and stock markets: Evidence from emerging economies

This study investigates the asymmetric effect of crude oil shocks on emerging sectoral stock indices using a non-parametric causality-in-quantiles approach. This study considers the origin of the oil shock i.e. demand shock or supply shock to investigate its impact on various sectors in mean and volatility. We find that the impact of crude oil is heterogeneous across shocks (demand or supply), market states (bullish, bearish and normal) and to a limited extent across sectors. Observing a similar pattern of crude oil's impact on emerging sectors, we argue that the influence of crude oil shocks extends beyond energy-intensive sectors.

Dynamic Nexuses between Macroeconomic Variables and Sectoral Stock Indices: Reflection from Indian Manufacturing Industry

Determination of significant sector specific macroeconomic factors under the board manufacturing industry is an important task. In Indian context, using the monthly data on five major manufacturing sector specific indices (such as BSE-Basic Materials, BSE-Consumer Discretionary Goods and Services, BSE-Fast Moving Consumer Goods, BSE-Health Care and BSE-Industrials) and the macroeconomic variables (gold price, index of industrial production, wholesale price index, money supply, foreign portfolio investment ratio (FPIR), rate of interest, real effective exchange rate and crude oil price and economic policy uncertainty) for the period September, 2005 to November, 2016, the present study attempted to explore the significant sector specific macroeconomic variables in long run as well as short run. The empirical results obtained by applying the ARDL-UECM model suggested that economic policy uncertainty, FPIR and price factor were observed to be the most important determinants of all the five sectoral stock indices for the study period.

Relationship Between Oil Price Movements and Stock Returns of Oil Firms in Oil Importing Economies

This article investigates the impact of oil price shocks on the stock returns of companies of the oil sector in oil-importing economies. The study considers oil stocks of top five oil-importing economies, that is, India, USA, China, Japan and Korea from 2007–2019. The oil price is considered as the independent variable, whereas the oil sector stock index return is considered as dependent variable. Based on the existing literature, some control variables like stock index return, inflation, interest rates, gross domestic product (GDP) and dummy for US-China trade war are included. Empirical evidence from the returns of oil sector stock index indicates that there is a significant and positive relationship between oil prices and oil sector’s stock returns. The result also highlights a strong relationship between stock market index and oil sector stock index. GDP of the country also leads to a positive impact on returns of oil stocks, although there is no significant impact of interest rates and inflation on the returns of oil stocks.