Range Volatility Spillover across Sectoral Stock Indices during COVID 19 Pandemic: Evidence from Indian Stock Market

PurposeThis purpose of this study is to empirically investigate the investors overreaction and underreaction behaviours across the sectoral stock indices in the Indonesian stock market.Design/methodology/approachNine weekly sectoral stock indices, comprising agriculture; mining; basic industry and chemicals; miscellaneous industry; consumer goods industry; property and real estate; infrastructure, utilities and transportation; finance; and trade, service and investment for the period 2009-2012 were analysed using the paired dependent sample t-test. To provide more insightful empirical evidence, the presence of market anomaly of investor’s overreaction and underreaction was examined on five observations with different vulnerable times.FindingsThe study documented that the overreaction anomaly was present among the winner portfolios in the entire sectoral indices. With the exception of the sectoral index of basic industry and chemicals on the loser portfolio, the study documented the presence of underreaction anomaly among all other sectoral indices in Indonesia. These findings implied that the investors might be able to gain significant profits investing their monies in the sectoral stock market in Indonesia by implementing the contrarian strategy.Originality/valueOriginality in this paper lies in the discussion of overreaction of investors in Indonesia where the stock market has great potential and has different characteristics and different problems from other regions.

This study investigates the shock transmission and volatility spillover between nine Indian stock market sectoral indices with both foreign institutional investors (FII) and mutual funds (MF) net equity flows using the BEKK-GARCH model. We use daily data covering the period from 1 January 2010 to 31 May 2019. Significant volatility spillover was observed from FII net equity inflows to five sectoral equity indices, while there was no volatility spillover from MF flows to any sectoral indices except telecom. Further, there was the presence of shock transmission from FII flows to five sectoral indices, but for MF flows, shock transmission was observed only in healthcare. Findings suggest that FII flows influence the stock market volatility, but MF flows are not having a significant impact.

Purpose ― This paper aims to examine the extent to which monetary policy shocks (domestic and international) will affect the movement of the sectoral stock index in Malaysia.Methods ― The monetary policy shocks are identified using a structural vector autoregressive (SVAR) model to examine the propagation of both monetary policy shocks (domestic and international) on sectoral stock prices.Findings ― The main results show that foreign monetary shocks significantly affect four sectoral stock indices: industrial and services, plantation, telecommunications, and utilities. In contrast, domestic monetary shocks impact three sectoral indices: industrial and services, technology, and utilities. However, domestic monetary policy shocks have a more dominant effect on the sectoral stock market in terms of magnitude.Implication ― The analysis results provide policymakers, particularly Bank Negara Malaysia (BNM), with valuable insights into which sectors are most sensitive to monetary policy fluctuations. Additionally, the results are beneficial for investors, as the analysis can help them manage their assets more effectively by identifying which sectoral stock indices are most affected by both domestic and international monetary policy shocks, and by guiding them to make more accurate investment decisions.Originality — First, it focuses specifically on sectoral indices, examining all 13 in Malaysia through the lens of theory, with particular emphasis on impulse-response analysis, which explores the cumulative effects of both domestic and foreign monetary policy shocks on these indices. Secondly, the study employs a lagged analysis using the SVAR model, providing a theoretical framework for comparison with other relevant studies.

Purpose – The aim of this study is to examine the relationship between oil prices and stock markets at the aggregate and sector level in countries which have different characteristics. Design/methodology/approach – The relationship among stock markets, sectoral stock indices and oil price changes are examined for Russia and Canada which are net oil exporters and United States and Japan which are net oil importers by using Johansen cointegration test. Findings – The findings of this study show that there are significant and mostly positive relationships between Russian MOEX stock market indices and crude oil prices. However; significant Johansen cointegration between Brent Crude Oil prices and most of the Canadian, U.S. and Japanese stock market aggregate and sectoral indices are not reported. Discussion – According to the findings, it can be stated that the long term relationship between stock market indices and crude oil prices is related to the changing conditions in the profitability of the corporations, inflation and monetary policy as a reaction to moving oil prices.

PurposeThis paper aims to identify various macroeconomic variables that affect the stock market performance of developed and emerging economies. It also investigates the effect of these factors on the stock markets of both economies. The impact of these variables on broad market indices and sectoral indices is investigated and compared too.Design/methodology/approachThe publications for the study were retrieved from databases such as Emerald Insight, EBSCO, ScienceDirect and JSTOR using the keywords “Macroeconomic variables” and “Stock market” or “Stock market performance.” The result demonstrated a growing corpus of scholarly work in the domain of stock market. The study was carried out separately for each macroeconomic indicator. Given a large number of articles under consideration, the authors began by reading the titles and abstracts of all publications to identify those that were relevant. The papers are evaluated in Excel and the articles for review range from 1972 to 2021.FindingsThe authors found that gross domestic product (GDP), FDI (Foreign Direct Investment) and FII (Foreign Institutional Investment) have a positive effect on both emerging and developed economies’ stock market while gold price has a negative effect. Interest rates had a negative impact on both economies except for a few developing countries. The relationship with oil prices was positive for oil exporting countries while negative for oil importing countries. Inflation, money supply and GDP are the macroeconomic variables that have the same effect on sectoral indices as they do on broad market indices. The impact was sector-specific for the remaining variables.Research limitations/implicationsThis paper gives an overview of relation and effect covering variety of macroeconomic variables and stock market indices. Still, there is a scope for further research to analyze the effect on thematic, strategy and sectoral indices. A longer time horizon with new variables, such as bank deposit growth rate, nonperforming assets of banks, consumer confidence index and investor sentiment, can be studied using high-frequency data. This research may help stakeholders adopt and manage their policies during a crisis or economic slump.Practical implicationsThis study will assist investors, researchers and educators in the fields of economics and finance in understanding how macroeconomic factors affect the stock market. Furthermore, this study can guide in portfolio diversification strategy across multiple sectors by examining the impact of macroeconomic factors specific to sectoral indices. This paper provides insight into society and researchers since it integrates a number of macroeconomic variables and their interaction with the stock market. It may also help pension funds and mutual fund firms to hedge their funds and allocate equity portfolios.Originality/valueWith respect to India, this study looked at new macroeconomic variables and sectors. It contrasted the impact of these variables in developed and developing economies. The effect of broad and sectoral stock indexes was also investigated and compared. The authors examined how these variables responded during crisis and economic downturns by using articles from a longer time frame. This research also looked into how changing the frequency of data for the variables altered stock performance. This paper emphasized the need for more research into thematic, strategy and broad market indices, such as small-cap and mid-cap indices.

This study investigates the relationship between inflation and sectoral stock indices in India, focusing on HDFC, ICICI, Infosys, and Tata Motors, against the backdrop of limited and inconclusive evidence in emerging markets. Monthly data from 2014 to May 2024 on inflation, GDP growth, and sectoral indices were analyzed using Ordinary Least Squares regression, Kendall’s tau-b correlation, and SARIMA forecasting with SPSS and Python. Results show statistically insignificant coefficients (p > 0.05) and very low R-squared values (<0.005), suggesting that inflation has negligible explanatory power over stock prices. Correlation and visual analyses further confirm weak, inconsistent relationships, with firm- and sector-specific variations. The study concludes that inflation alone does not significantly influence Indian stock indices, and broader macroeconomic variables such as interest rates, fiscal policy, global cues, and firm fundamentals better explain market dynamics. Future research should adopt panel models incorporating diverse indicators like crude oil prices, FDI, repo rates, and employment indices to yield more robust insights.

Bu çalışmada Ocak 2011-Haziran 2019 dönemi için, güven ve borsa endeksleri arasındaki sektörel bazlı ilişkiler araştırılmaktadır. Finansal hizmet güven endeksi, hizmet sektörü güven endeksi, inşaat sektörü güven endeksi, perakende ticaret sektörü güven ve borsa endeksleri değişkenlerine ait aylık veriler, ilgili dönemde ilk olarak, Hacker ve Hatemi-J (2006) testiyle simetrik nedensellik, ikinci olarak, Hatemi-J (2012) testiyle asimetrik nedensellik ilişkisi açılarından incelenmiştir. Yapılan testler sonucunda edinilen bulgulara göre; Türkiye’de sektörel güven endeksleri ile ilgili Borsa İstanbul (BİST) sektör endeksleri arasında simetrik bir nedensellik ilişkinin varlığı tespit edilememiştir. Buna karşın, bu değişkenler arasında asimetrik bir nedensellik ilişkisi saptanmıştır. Diğer bir ifadeyle, sektörel güven endeksleri ile borsa sektör endeksleri arasında doğrudan bir nedensellik ilişkisi bulunmazken, bu değişkenlerin bileşenleri üzerinden bir nedensellik ilişkisi bulunmaktadır. Anahtar Kelimeler: Güven Endeksi, Borsa Sektör Endeksi, Simetrik Nedensellik, Asimetrik Nedensellik JEL Sınıflandırması: G19, G23, G40

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

This study investigates the signs of herding behavior during the COVID-19 pandemic in the Indonesian Stock Exchange. Various studies found no herding in Indonesian stock markets during the COVID-19 pandemic, but we believe those studies have a limited methodology to capture the herding behavior. We believe that herding appears in a short time during the pandemic period, so we have to reexamine the existence of herding behavior using sectoral stock indexes rather than the stock market-wide index (IHSG) and using the rolling regression technique to capture the possibilities of herding that might be existing during short window period in COVID-19 pandemic time. This study uses a model Chang et al. suggested (2000). Variables such as return dispersion (CSAD), absolute market return, and market squared return are employed in the analysis. We use the closing price of 715 stocks, nine sectoral stock indexes in IDX, and the closing price of IHSG from January 2, 2020, until April 30, 2021. The results show that herding cannot be found in the full sample of the market-wide stock index (IHSG) and sectoral indexes. The rolling regression indicates that herding was found for several days from January 2020 to December 2021.

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

This study employs the Maximal Overlap Discrete Wavelet Transform technique to analyze the wavelet-based correlations between Bitcoin, bond markets, and thirteen sectoral stock indices in India over the period from 2017 to 2023, focusing on the comparison of pre-and post-COVID-19 pandemic effects. The aim is to investigate the dynamic interrelationships and to understand the impact of the COVID-19 pandemic on these financial assets. The study period is divided into pre-COVID-19 and post-COVID-19. Findings from the study reveal a minimal negative correlation between Bitcoin, bond markets, and the sectoral stock indices in the pre-COVID era, indicating a lack of significant interdependence among these assets. However, the scenario changes markedly in the post-COVID period, shifting towards a positive correlation. This shift suggests that the COVID-19 pandemic has altered the relationship dynamics, leading to a more interconnected financial environment where movements in Bitcoin have begun to show a significant positive correlation with the movements in bond and sectoral stock indices in India. The study contributes to the existing literature by providing empirical evidence of how external shocks, such as the COVID-19 pandemic, can influence the correlation patterns among different financial assets. It highlights the importance of considering the changing dynamics in financial market correlations for investors, policymakers, and researchers in portfolio diversification, risk management, and financial stability analysis. Further, it underscores the role of alternative investments like Bitcoin in the evolving market landscape, particularly in response to global crises.

The basic thrust of this article is to examine how shocks and volatility are transmitted across sector indices. This article employs the autoregressive asymmetric BEKK-GARCH model. The study is based on daily data from the National Stock Exchange (NSE) of India from January 2004 to January 2014. Volatility spillover was found to be bidirectional among the two pro-cyclical sectors: Finance and IT. But, there was a unidirectional shock and volatility spillover from the non-cyclical FMCG sector to both the pro-cyclical sectors. The FMCG sector has remained almost unaffected by the spillover from the other sectors. Moreover, the evidence of asymmetric spillover has been found to be present in most of the case. Second, correlations between the sectors were found to be higher during the period of global financial crisis. But no such evidence was found in the context of the Euro zone debt crisis. Understanding the dynamics of shocks and volatility transmission is necessary for risk management in general and for optimal portfolio allocation and hedging strategy in particular. To the best of our knowledge, this is the first study on Indian stock market which has analysed the dynamics of shock and volatility transmission across sector indices.

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

Sectoral Trends and Cycles in Germany

We examine the comovements between the output indexes of three German sectors (manufacturing, mining, and agriculture) and the three corresponding sectoral stock market indexes. It is found that data with and without seasonal adjustment give mixed results on the long-run interaction between the sectoral indexes. Compared with data that are non-seasonally adjusted, the adjusted data offer weaker evidence on the cointegration relationship between a) the sectoral output indexes, b) sectoral stock indexes, and c) individual pairs of real and financial indexes. On short-run comovement, seasonally adjusted data offer stronger evidence on the presence of common synchronized and non-synchronized cyclical components.