Sectoral Indices Research Articles

COVID 19 Outbreak and Tokyo 2020 Olympic Games: A Perspective from Japan’s Economy and Capital Market

This study highlights the key impacts of hosting an international sports event, Tokyo 2020 Olympic Games, during the period of deadliest contagious disease outbreak in history, COVID 19. The perspective is analysed in terms of the performance of capital market, investment market and sectoral market by the indexes of TOPIX, Stock Market, Bond Market, Foreign Exchange, FTSE, MSCI, and sectoral index of Air Transportation, Construction, Pharmaceutical which shows different range of fluctuation.

Changes in Inflation and Exchange Rates on Investment Decisions in Sectoral Shares on the Indonesia Stock Exchange

This research was conducted on the basis of different perceptions regarding the influence of domestic macroeconomics on stock prices. The independent variables used in this study are inflation and exchange rates, while the dependent variable used is the share price of the Indonesia Stock Exchange's Sectoral Index. This study uses monthly data from January 2018 to December 2020. The analysis technique used is multiple regression analysis. There are three findings in this research. First, inflation has a partial effect on most of the sectoral indices except for the Basic Industry Sector Index, the Financial Sector Index and the Trade Sector Index. Second, the Exchange Rate has a partial effect on most of the Sectoral Indices except for the Mining Sector Index and the Trade Sector Index. Third, inflation is the most dominant variable affecting the eight sectoral indices, while the rest is dominated by exchange rates.

Multifractal cross-correlations between green bonds and financial assets

We analyze multifractality for green bonds, stock sector indices, and US economic sector bonds. Green bonds and US bonds show non-linear cross-correlations. We perform Multifractal Detrended Cross-Correlations Analysis (MF-DCCA) to analyze multifractal cross-correlations and the weak version of the Efficient Market Hypothesis (EMH). Our findings are relevant to academics, financial professionals and the general public. Although green bonds are bonds used exclusively to finance sustainable investments, they are still inefficient assets. We find that bond indices for consumer staples and equity indices for information technology and the real state sector can be used to hedge investments in green bonds.

VOLATILITY SPILLOVER AND PANDEMIC – ANALYSIS OF SELECTED SECTORAL INDICES IN INDIA

The COVID-19 pandemic has impacted economies worldwide, and it has been reflected in their stock markets, as well. The effect was evident in the Indian stock markets, yet the nature and level of this impact are not very clear. This paper examines the short- and long-term spillover in the volatility between coronavirus cases on the broader market index, Nifty 50, and the indices of selected sectors: information technology, healthcare, and pharmaceuticals. Data for the period from January 2020 to July 2022 has been analyzed. The Dynamic Conditional Correlation GARCH model was used for analyzing the volatility spillover of coronavirus cases on Nifty 50, Nifty IT, Nifty Healthcare, and Nifty Pharma. The results show that there has been a significant long-term volatility spillover of infections on the broader market index, Nifty 50. However, there is no long-term persistence of COVID-19 on the sectoral indices. Only Pharma and Healthcare have exhibited significant short-term persistence. All the indices were negatively correlated with case numbers. Even though the sectoral indices did not exhibit significant long-term volatility spillover, they were positively correlated with the broader market index, Nifty 50, which in turn showed the significant long-term persistence of COVID-19. The results of the study are useful to policymakers and investors to understand the level of market impact due to the pandemic.

FINANCIAL SECTOR DEVELOPMENT AND REAL SECTOR GROWTH – ASSOCIATION, SPILLOVER AND CAUSALITY DURING PRE COVID AND COVID REGIMES

In this paper, we propose an alternative approach to understanding the relationship between financial sector development and real sector growth in India. We use stock market sectoral indices available on National Stock Exchange (NSE) like Capital Goods Index, FMCG Index, Energy Index, Infra Index, Metal Index, Realty Index, and Auto Index to represent the real sector. To represent the financial sector, we consider Bank Index and Financial Services Index separately. The proposed framework examines the relationships at a granular level to understand the extent of association, spillover, and causality. We also analyze the relationship between the financial sector and the real sector in Pre COVID and COVID periods separately. Our research methodology includes the use of Detrended Cross-Correlation Analysis (DCCA), Wavelet Multiple Correlation (WMC), Wavelet Multiple Cross Correlation (WMCC), Diebold-Yilmaz spillover Framework, and Non-Linear Causality Test. Our granular approach has enabled us to examine the relationships in different periods and we observe that the results change. The intensity of the relationships also is different during the COVID period as compared to Pre COVID period.

COVID-19 related stringencies and financial market volatility: sectoral evidence from India

PurposeThis study aims to examine the impact of the stringency of COVID-19 protocols on the volatility of sectoral indices during the period 03:2020–05:2021. Specifically, this study investigates the role of economic disturbances on sectoral volatility by applying a range of conditional volatility techniques.Design/methodology/approachFor this analysis, two approaches were adopted. The first approach considers COVID stringency as a factor in the conditional variance equation of sectoral indices. In contrast, the second approach considers the stringency indicator as a possible determinant of their estimated conditional volatility.FindingsResults show that the stringency of the protocols throughout the pandemic phase led to an instantaneous spike followed by a gradual decrease in estimated volatility of all the sectoral indices except pharma and health care. Specific sectors such as bank, FMCG, consumer durables, financial services, IT, media and private banks respond to protocols expeditiously compared to other sectors.Originality/valueThe key contribution of this study to the existing literature is the innovative approach. The inclusion of the COVID stringency index as a regressor in the variance equation of the conditional volatility techniques was a distinctive approach for assessing the volatility dynamics with the stringency of COVID protocols. Furthermore, this study also adopts an alternative approach that estimates the conditional volatility of the indices and then tests the effect of the stringencies on estimated volatility in a regression framework.

The Month Effect in the Baltic and Nordic Stock Markets at Market-Level and Sector-Level

The purpose of this study is to analyze and compare the trends in the expression of the month effect in the Nasdaq Baltic and Nasdaq Nordic stock markets, as well as to examine whether the seasonal stock price fluctuations occur in all industrial sectors of these markets or are specific to certain sectors only. The OMX Baltic Benchmark, OMX Baltic, and OMX Nordic 40 indexes, which reflect the situation in the Baltic and Nordic stock markets, were used in the study to assess seasonality at the market level. To assess the seasonality in separate sectors of the Baltic and Nordic markets, we used sectoral indexes calculated in these markets. The data sample covers the period from January 2, 2004 through December 31, 2019. The methodology of the research used to examine seasonality in daily returns entails estimating a regression with dummies and GARCH (1,1) to capture month effects. Although the results of OLS and GARCH (1,1) analysis were quite different, they proved the existence of the month effect in both the Baltic and Nordic stock markets. The results of the analysis of seasonal fluctuations in stock prices at sector-level evidenced that month effects appear both in Baltic market and Nordic market, which allows earning abnormal returns in particular months for those who invested in stock of certain sectors. Our research has evidenced that trends in the volatility of stock prices in separate months in the Baltic countries are not stable and are characterized by greater instability as compared to the Nordic countries.

Future outlook and influencing factors analysis of natural gas consumption in Bangladesh: An economic and policy perspectives

The development of mechanization and technology has triggered the rising energy consumption in various sectors. The study objective is to investigate the relationship between gas consumption share, energy intensity, economic structure share, per capita gross domestic value, and population at the sectorial level from 1994 to 2020. This study analyzes the factors in three ways: first, the study applies decomposition analysis between key factors. Second, an appropriate decoupling method is applied to investigate the impacting factors to check the driving factors affecting the decoupling using the logarithmic mean Divisia index method. Third, based on aggregated and sectorial variations, the ratio decomposition of each sector is estimated. The results show that the economic activity effect is the main driving factor in raising gas consumption, which increased by 15.11 crore Tk./million during 1994–2020. The energy intensity trend declined by 14.87 Mtoe/crore Tk., which shows an imperative role in natural gas consumption efficiency for production and in economy. The economic structure share provided a record decline by 52.79 crores Tk. during the COVID-19 situation while a significant increase in gas consumption was found until 2013, which could be significant under decomposition changes. Three decoupling states such as expansive negative decoupling, expansive coupling and weak decoupling were found in which the decoupling relationship was gradually a dominated by a weak decoupling. The sectorial index provides a maximum of weak decoupling in which energy-saving technology gap change was found in power, captive power, industry, tea estate, compressed natural gas, and fertilizer sectors. Finally, the scenarios analyzed that natural gas consumption estimates maximum gross domestic product and conserves more energy in the future. Briefly, the decoupling process and its leading factors were obvious among nine major sectors.

Moroccan Stock Exchange market topology in crisis and non-crisis periods

This paper seeks to investigate the dynamics within the Moroccan Stock Exchange (MSE) market topology in crisis and non-crisis periods using daily historical log returns of sectoral indices covering the period from January 4, 1993 to September 9, 2021. The study applies the Agglomerative Hierarchical Clustering (AHC) implemented on the Dynamic Time Warping (DTW) distance matrix over ten sub-periods covering numerous crises, from Subprime mortgage crisis to European debt crisis and finally COVID-19 crisis. The obtained clustering results are gathered into a network to display the cumulated interconnections between the sectoral indices. The findings showed that the Casablanca Stock Exchange (CSE) market clusters composition is dynamic during the studied period. Indeed, some sectoral indices demonstrated evidence of strong similarities by gathering in the same cluster over numerous sub-periods as the couples Electrical & Electronic Equipment and Transport or as Banks and Construction & Building Materials sectoral indices. Moreover, the interconnections of CSE sectoral indices are trend dependent. According to the obtained network, the Oil and Gas demonstrated its centrality.

The effect of the COVID-19 epidemic on Moroccan sectoral indices: The entropy approach

The current study investigates the impact of the Coronavirus 2019 (COVID-19) pandemic on the volatility of Moroccan stock market sectoral indices. Shannon entropy with multiple estimators and Rényi entropy for different scales were calculated from February 1, 2019 to May 1, 2022, to measure volatility in the Banking, Oil and Gas, Construction and Building Materials, Beverage, Food Producers and Processors, Distributors, and Mining sector’s indices. In this regard, this study uses three periods to quantify the uncertainty in Moroccan sectoral indices before, during, and after the first year of the COVID-19 pandemic in Morocco. The empirical results from Shannon and Rényi entropies indicated higher volatility during the COVID-19 pandemic for all sectoral indices except Oil and Gas. However, the consumer staples sectors have shown a form of resilience compared to other sectors. Indeed, the impact of COVID-19 on the consumer staples sectoral indices’ volatilities was negligible compared to other sectors. In addition, investing in a portfolio composed of Mining or Construction and Building Materials stocks was risky due to the increased volatility before and during the epidemic. However, after the COVID-19 pandemic, the entropy level corresponding to all sectors has rearranged except the Beverage sector, which kept the lowest entropy during the three periods. Thus, it seems that the Beverage sector was a safe investment for the three periods. The findings are crucial for governments, businesses, private and public authorities, and investors to create recovery action plans for sensitive sectors and give investors trust to make smarter investment decisions.

An Empirical Study of the Movement of Sectoral Indices and Macroeconomic Variables in the Indian Stock Market

The goal of this research is to look at how the Indian stock market sectoral indices respond to three macroeconomic variables: oil price (OP), gold price (GP) and exchange rate (ER) between 2016 and 2020. The data of sectoral indices were collected from the Bombay Stock Exchange. The underlying series is evaluated as non-stationary at the level, but stationary in the first difference, using the augmented Dickey–Fuller unit root test. The multivariate co-integration analysis and vector error correction model indicates that there are long-term links between macroeconomic variables and sectoral indices in the information technology sector. Meanwhile, the research using the vector auto regression model approach shows that there are short-run correlations between macroeconomic variables and sectoral indices, namely Basic Materials, Fast Moving Consumer Goods, Finance, Healthcare, Information Technology, Auto, Bankex, Power and Reality. The results document that OP, GP and ER simultaneously have a significant effect on sectoral indices in the Indian stock market. To stabilise the stock market post-COVID-19, the authorities are advised to put economic policies sector-wise to accelerate the economic growth and to maintain fiscal discipline. The authorities need to stabilise the aforementioned macroeconomic variables to accelerate the economic growth as the ER has a significant negative impact on all sectors.

Is greenness an optimal hedge for sectoral stock indices?

The paper examines the role of green bonds in hedging the risk against industry portfolios and other major asset classes. It mainly focuses on how the greenness of the portfolio reduces the risk of green portfolios containing green bonds and 11 industrial sectors and major financial assets from October 2014 to November 2021. The results show that the risk of green portfolios is lower than that of unhedged (non-green) portfolios. Furthermore, our study provides evidence that the hedging effectiveness of green portfolios improves during the COVID–19 pandemic. Finally, the results show that investors across the risk aversion spectrum gain higher utility after considering the transaction costs while investing in green portfolios. These results are new additions to prior literature that can interest investors, fund managers, and policymakers.

Impact of the Covid-19 Pandemic on the Standing of Companies Listed on the Warsaw Stock Exchange

Abstract Objective The impact of the Covid-19 pandemic can be observed in many aspects of the functioning of people, economic entities, organisations and countries. One of the areas where this phenomenon has left its mark remains the stock markets. Company listings are influenced by both investor emotions and the economic and financial condition of individual companies. The aim of this study is to assess the impact of the Covid-19 pandemic on individual industries represented by companies listed on the Warsaw Stock Exchange. Methodology In order to achieve this goal, an analysis was made of the value of changes in the so-called sector indices in the period from the beginning of 2020 to the end of the first half of 2022. This approach to the study will make it possible to determine which industries were most significantly affected by the economic change and what the nature of the possible change was. Quarterly data was used in the research. Findings The results obtained made it possible to note that among the thirteen analysed sectors, we can observe those that lost their value as a result of the Covid-19 pandemic (WIG-medicines, WIG-food, WIG-banks, WIG-clothing), but also those that significantly increased their value in the period under study (WIG-motorisation, WIG-construction, WIG-energy, WIG-IT). Value Added The study conducted will allow for a better understanding of how investors react to crisis events and how this translates into the listing of companies on the stock market. Recommendations The research results obtained require further analysis to establish deeper links between the Covid-19 pandemic and individual sectors of companies listed on the Warsaw Stock Exchange, which will be the subject of the author’s further studies.

Spillover Connectedness among Global Uncertainties and Sectorial Indices of Pakistan: Evidence from Quantile Connectedness Approach

This study empirically examines the spillovers from global uncertainties to the sectoral indices of the Pakistan stock market (PSX). Furthermore, we select three major sectoral indices, i.e., the energy, financial, and material composite indices. These indices represent a massive capital volume of PSX. We utilize the data from 10 May 2002 to 27 June 2022 to examine the outbreak due to the global financial crisis (GFC) of 2007–2008 and the impact of the world’s great pandemic, of COVID-19. Additionally, we applied a novel econometric estimation approach: quantile connectedness. We found that connectedness is strong in the case of highly positive changes (above the 20% quantile) and highly negative changes (below the 80% quantile). Additionally, the study also found that materials sector is the least connected at level of 1.58%. In contrast, the financial sector was a strong transmitter of spillovers during the entire study period at connectedness of 54.59%. Regarding graphical results, we found that economic policy uncertainty (EPU) and crude oil index (WTI) are net transmitters, especially during the financial crisis and COVID-19, whereas WTI transmitting impact was significantly dominant during GFC 2007–2008. Conversely, the index MSCI remains the recipient of the spillover during the entire study period, where the remitting effect was observed as dominant during the GFC, and COVID-19 outbreak. The energy sector was found to be more recipient during the GFC, with additional turn transmitters of the shocks after the COVID-19 pandemic. The study recommends that portfolio managers and individual investors consider the materials sector for their investment due to the least connectivity. Similarly, investors need to invest carefully in the financial sector because it is a net transmitter of spillovers to other sectors.

Analyzing the current state of the Russian economy at the macro-, meso- and micro-levels

Subject. The article examines the issues of economic policy and analysis of the current state of the economy at the macro-, meso- and micro-levels. Objectives. The purpose is to underpin theoretical aspects and methodology for comprehensive analysis of the current state of the economy at the macro-, meso- and micro-levels, to develop some aspects of the methodology to analyze the implemented economic policy. Methods. The study rests on general scientific principles and methods of research, like abstraction, generalization of approaches of domestic and foreign authors to economic policy and analysis of economic condition of economic entities. Results. The study summarizes the directions of sanctions at the macro- and meso-levels, explores the directions of damping sanctions of the policy of the State and enterprises. I offer a methodology for assessing the current state of the economy. It includes three stages. At the first stage, macroeconomic indicators are assessed, including indicators of economic growth, unemployment, inflation, foreign economic activity, etc. At the second stage, sectoral indicators are evaluated, like stock indices, indices of production growth, business confidence. At the third stage, indicators of companies included in sectoral stock indices are calculated. The methodology was tested at all three levels of the analysis, and indicators for enterprises representing industries were calculated. Conclusions. The study enabled to assess the signs of sustainability of economic systems, structural changes in the economy, to analyze the anti-crisis policy and sustainability of economic entities.

Sentimental Herding in Stock Market: Evidence from India

The present study examines herd behaviour in the Indian equity market using daily prices of 11 broad market indices, 12 sectoral indices, 16 strategic indices and 11 thematic indices from 1 January 2016 to 31 March 2022. For examining herd behaviour, daily returns, overnight returns, intraday spread, absolute market return and squared market return are calculated. Nifty 500 is used as a proxy index for the whole market. The regression models suggested by Christie and Huang (1995) and Chang et al. (2000) are used to calculate Cross-Sectional Standard Deviation (CSSD) and Cross-Sectional Absolute Deviation (CSAD) respectively, which measure the equity return dispersions. It is observed that herding exists in the Indian equity market when we calculate return dispersions using intraday spread. However, no herd presence is found when return dispersions are calculated through daily return, overnight return, absolute market return and squared market return. These results may be useful for investors, policy makers and regulatory bodies. Investors might design their investment strategy while making investment decision. Regulators might be able to formulate their policies to ensure market efficiency in the Indian equity market.

Inflation and west African sectoral stock price indices: An asymmetric kernel method analysis

Our work puts into perspective the relationship between inflation and West African sectoral indices between November 2001 and January 2020 using the asymmetric kernel method. The sectoral indices considered for the analysis include retail, finance, industry, utilities, agriculture, transportation, and other sectors. Our work reveals that while all sectors are sensitive to inflation, the utilities and agriculture sectors are more sensitive to changes in inflation. Moreover, we discover that the relationship between inflation and sectoral stock market indices is rather non-linear to support the hypothesis that the relationship between inflation and stock market indices varies across different inflationary economies. These results imply that investors modify the structure of their investment portfolio according to the variation in the levels of inflation to the extent that this variation ultimately affects future dividends.

Air quality index and the Chinese stock market volatility: Evidence from both market and sector indices

This paper mainly examines whether the air quality index can forecast the Chinese stock market volatility. By comparing the predictability of air quality index, leverage components, jump components, and overnight information, we find that air quality index is more efficient to predict the stock market volatility, during medium-term and long-term horizons. Importantly, from both market and sector indices, we find the air quality index is still more informative than the leverage components, jump components, and overnight information for forecasting the stock market volatility. In addition, leverage components have better performances during a longer horizon for both market and sector indices. This paper tries to provide new evidence for stock market volatility prediction based on the Chinese aggregate stock market and different stock sectors.

Asymmetric spillover effects of Covid-19 on the performance of the Islamic finance industry: A wave analysis and forecasting

This paper investigates the spillover effects of the waves of Covid-19 that affected the performance of the Islamic financial sector index (KMI 30) concerning Pakistan's stock exchange. The daily data is used on confirmed registered cases of Covid-19 and the KMI 30 stock prices from February 2020 to June 2022. The data is distributed into five segments on the basis of Covid-19 waves. The asymmetric GJR-GARCH is used to capture the effect of Covid-19 during each wave and E-GARCH is used to see the positive and negative impacts of Covid-19 on KMI through spillover effects. The E-GARCH model also serves to forecast the conditional variance. The Chow structural break point and Bai and Perron tests identify the structural breaks in each wave. Results of structural break testing confirm the presence breaks in each wave. Meanwhile volatility modeling results indicate there is an asymmetric effect in the return series. The E-GARCH model results reveal that there is return and volatility spillover effect from Covid-19 to KMI 30 in each wave. In future the conditional volatility remains less than the expected volatility as predicted by the forecasting statistics. We respond to policy calls by sharing our novel research in not only combating, but also assisting the required urgency of planning for future of Covid-19 outbreaks.

Are there bubbles in sectoral indices? Evidence from national stock exchange

Are there bubbles in sectoral indices? Evidence from national stock exchange