Sector Stock Research Articles

Herding Behavior in Stock Market: An Empirical Study of Energy Sector of BRICS Nations

This paper attempts to study the herding behaviour of Energy sector stocks toward the Market & equal-weighted average portfolio of the sector of BRICS. This study uses Closing price data from January 1st 2017 to December 31st 2022, of all fossil fuel companies from the energy sector of BRICS for those data was available. Those Companies were removed from a sample which was listed during the study period or delisted at any time during the study period. Nine companies selected from Brazil, 11 from Russia, one from India, 33 from China & 3 from South Africa are taken as a sample in this study. CSAD by Chang et al. (2000) & CSSD by Christie and Huang (1995) methodology for analysis of the herding behaviour is used in this study. The results show the herding behaviour during the study period in some countries of BRICS using the CSSD method & CSAD. Mostly found in China.

Can machine learning identify sector-level financial ratios that predict sector returns?

Academics and practitioners use fundamental ratios to evaluate an industry's financial and operating performance. WRDS has large firm-level and sector/industry-level databases that provide over 70 financial ratios that are applied in finance classes to compare and assess relative financial performance. However, there has been a lack of sophisticated econometric methods assessing these ratios' importance in predicting sector-level stock return performance. Using Elastic Net methods, we identify financial ratios that significantly forecast out-of-sample sector stock returns and find that these predictive ratios vary across sectors. We form long and long-short portfolios that consistently outperform the market over-time. Long portfolios generate significant alpha and large utility gains, boost the Sharpe and Sortino ratios, and a cumulative investment portfolio exceeds the market benchmark by five times. Long-short portfolios generate Fama-French 4-factor and 6-factor alphas between 4–9% and cumulative investment gains from six to fourteen times. Our research establishes that machine learning can identify financial ratios that significantly predict sector returns and generate profitable portfolio allocation.

Sectoral risk contagion and quantile network connectedness on Chinese stock sectors after the COVID-19 outbreak

PurposeThis study aims to explore the risk spillover effects among different sectors of the Chinese stock market after the outbreak of COVID-19 from both Internet sentiment and price fluctuations.Design/methodology/approachThe authors develop four indicators used for risk contagion analysis, including Internet investors and news sentiments constructed by the FinBERT model, together with realized and jump volatilities yielded by high-frequency data. The authors also apply the time-varying parameter vector autoregressive (TVP-VAR) model-based and the tail-based connectedness framework to investigate the interdependence of tail risk during catastrophic events.FindingsThe empirical analysis provides meaningful results related to the COVID-19 pandemic, stock market conditions and tail behavior. The results show that after the outbreak of COVID-19, the connectivity between risk spillovers in China's stock market has grown, indicating the increased instability of the connected system and enhanced connectivity in the tail. The changes in network structure during COVID-19 pandemic are not only reflected by the increased spillover connectivity but also by the closer relationships between some industries. The authors also found that major public events could significantly impact total connectedness. In addition, spillovers and network structures vary with market conditions and tend to exhibit a highly connected network structure during extreme market status.Originality/valueThe results confirm the connectivity between sentiments and volatilities spillovers in China's stock market, especially in the tails. The conclusion further expands the practical application and theoretical framework of behavioral finance and also lays a theoretical basis for investors to focus on the practical application of volatility prediction and risk management across stock sectors.

Impacts of climate pact on global oil and gas sector stocks

PurposeThe purpose of this study is to examine the impacts of the Glasgow Climate Pact on global oil and gas sector stocks. Further, this study also examines if the nations' Climate Change Performance Index (CCPI) and World Energy Trilemma Index (WETI) drive the abnormal returns around the event.Design/methodology/approachThe authors apply the event study analysis to 691 global oil and gas firms across 52 countries. Further, they apply the cross-sectional examination of cumulative abnormal returns (CARs) across 502 firms.FindingsThe emerging markets experienced significant negative abnormal returns on the event day. The CCPI negatively affects longer pre-event CARs, while WETI significantly negatively associates with CARs during longer pre- and post-event windows. Volatility is negatively related to pre- and post-event abnormal returns, while past returns positively drive pre-event period CARs but negatively drive post-event window CARs. This study finds an interesting association between liquidity (CACL) and CARs, as CACL positively drives pre-event CARs, but post-event CARs are negatively associated with CACL. The CARs do not significantly correlate with leverage, size and book-to-market ratio.Practical implicationsThis study's findings on the impact of climate risks on financial markets have significant implications for global regulatory bodies. Policymakers should reduce stock volatility and enhance environmental disclosures by publicly traded companies to accurately price and assess the potential impacts of climate risks. Governments should examine the effects of environmental restrictions on investor behavior, especially in developing countries with limited access to capital. Therefore, policymakers need to consider the far-reaching impacts of environmental regulations while introducing them.Originality/valueClimate risks are expected to impact the global financial market significantly. Prior studies provide limited evidence on how such climate pacts impact the oil and gas sector. Hence, this study, while bridging this gap, provides important implications for policymakers and stakeholders, particularly the emerging markets that are more sensitive.

Pengaruh harga minyak, inflasi, suku bunga, dan kurs terhadap indeks saham sektoral IDXEnergy

Since 2020, energy commodity prices have shown recovery after falling due to the impact of COVID-19. However, during this recovery period, the Russia-Ukraine war occurred. Russia was sanctioned by an energy embargo which further pushed the price of energy commodities, including oil. On the other hand, the events of the Russian-Ukrainian war also caused turmoil in macroeconomic factors such as inflation, interest rates, and exchange rates. This study examines the effect of oil prices and macroeconomic factors on the energy sector stock index. The independent variables used in this study are oil prices and macroeconomic factors such as inflation, interest rates, and exchange rates. The period used in this study is the period from 2020 to 2022. The sampling technique used is a saturated sample where the entire population will be sampled. The data analysis technique used is multiple linear regression. The results showed that partial oil prices and exchange rates had no significant effect. In contrast, the inflation variable had a significant positive effect, and interest rates had a significant negative effect. An increase in inflation will reduce the value of wealth, so investors should invest in stocks in the energy sector when there is an increase in inflation. Conversely, an increase in interest rates makes investment alternatives in deposits more attractive with a lower level of risk than stocks.

Network connectedness between China's crude oil futures and sector stock indices

The financialization and international influence of China's crude oil market are increasing with the listing of China's crude oil futures (INE). In this context, we use the time-frequency connectedness network model to analyse the dynamic spillover effect between Chinese crude oil futures and sector stock indices, and compare it with American crude oil futures (WTI), where the study period includes the COVID-19, the European energy crisis, the Russia-Ukraine conflict and its like. The empirical results demonstrate that the total spillover effect of the crude oil and stock markets is mainly generated by high frequency (1–5 days). Extreme events in crude oil markets such as the Saudi Arabia oil field attack and the negative WTI price led to significant changes in the connectedness network of the system, increasing spillover risk and reducing system stability, but it recovers quickly. Moreover, the heterogeneity of spillover effect from crude oil futures to sector stock indices exists with energy industry and crude oil market the strongest, and meanwhile the spillover effects between crude oil and sector stock indices are smaller than those among sector stock indices in general. Further, China's sector stocks are more closely related to INE (crude oil futures listed on Shanghai International Energy Exchange) than WTI. Specifically, the spillover effect between WTI and INE is asymmetric, that is, the spillover effect from WTI to INE is significantly stronger than from INE to WTI. Finally, Dynamic portfolio weights indicate that assets with low connectedness are beneficial for balancing risk and return. These new findings suggest some useful implications: Regulators should pay close attention to cross-market risk and abnormal vibration of INE, and stock investors in China had better not regard crude oil futures as a hedging market.

Pengaruh Return On Asset Dan Earning Per Share Terhadap Harga Saham Sektor Pertambangan Yang Terdaftar Di Jakarta Islamic Index Periode 2016-2021

The purpose of conducting this research is to analyze and find out how the influence of return on assets and earnings per share has on mining sector stock prices listed on the Jakarta Islamic Index for the period 2016 – 2021. This research uses quantitative methods and panel data regression analysis methods. The samples used were 7 companies with a total of 6 years of data, namely 42 data, using a purposive sampling technique. The results showed that the variable return on assets partially has a significant effect on stock prices, while the earnings per share variable partially has no significant effect on stock prices. Simultaneously, the variables return on assets and earnings per share have a significant influence on the mining sector stock prices listed on the Jakarta Islamic Index for the period 2016–2021 with a coefficient of determination for this model of 93.61%.

Sectoral evidence on Indonesian economic performance after the pandemic

The Indonesian economy has a long history of steady growth punctuated by times of turmoil and crisis. Recently Indonesia has faced the COVID-19 pandemic, inflation, contractionary U.S. monetary policy, and fluctuating commodity prices. To examine how the economy is faring since the pandemic began, this paper compares sectoral stock returns since COVID-19 hit the Indonesian economy with forecasted returns based on macroeconomic variables. The results indicate that coal, iron and steel, health care, and pharmaceuticals are outperforming more than three years after the coronavirus crisis began. Tobacco, industrials, and sectors related to construction are underperforming. The regression evidence also indicates that Indonesian sectors are primarily exposed to the Indonesian stock market. Coal, iron and steel and natural resources stocks are less exposed to the Indonesian stock market and more exposed to the world stock market. Almost no sectors exhibit exposure to contractionary U.S. monetary policy. The importance of the Indonesian stock market in explaining stock returns reflects the fact that the Indonesian economy is largely driven by domestic demand. To increase its resilience, Indonesia should also nurture labor-intensive exports.

Investigating the Effects of Natural Disasters on the Stock Market on a Sectoral Basis: The Case of 2023 Kahramanmaraş/Türkiye Earthquake

This study aims to examine the effects of two earthquakes in Kahramanmaraş/Türkiye on February 06, 2023 on Borsa Istanbul (BIST) stock markets on a sectoral basis. In this context, whether there is a statistically significant difference between sectoral stock returns before and after the earthquake is investigated. The study divides 18 BIST sectoral index returns into two sub-samples, pre-earthquake and post-earthquake and analyzed by the event study method. For this purpose, Paired Samples t-Test, a parametric test, and the Wilcoxon Signed Rank Test, the non-parametric equivalent of this test, are used. According to the research results, no statistically significant difference was found between the pre-and post-earthquake returns of BIST sector indices. The findings show that, in the case of investing in BIST sectoral indices, abnormal returns cannot be obtained depending on the earthquake event. Accordingly, BIST sectoral indices are an efficient market in a semi-strong form.

Using US Stock Sectors to Diversify, Hedge, and Provide Safe Havens for NFT Coins

This paper explores risk management strategies for investments in Nonfungible Token (NFT) coins through their diversification within the S&P 500 industry sectors. Given the significant decline in NFT coin values in 2022, understanding these strategies is critical for investors. This study focused on four major NFT coins (Enjin coin (ENJ), MANA, Theta coin (THETA), and the Tezos coin (XTZ)) and employed ETFs representing the major S&P 500 sectors for analysis. Dynamic conditional correlation GARCH models have been used, to estimate correlations between the NFT coins and US industry sector ETFs. Our findings showed that while most S&P 500 sectors offered diversification benefits in the pre-COVID period, all of them did during the COVID period. However, these sectors are generally weak safe havens and poor hedges. Portfolio analysis suggests an optimal NFT coin weighting of 10–30%, based on the Sharpe ratio. This study aims to pave the way for informed decision-making in the dynamic NFT market.

The “Christmas Effect” on defensive accelerated stocks

The Christmas event in December 2022 is accompanied by an increase in inflation and also an increase in interest rates. The objective of this study is to examine the Christmas effect on optimal returns for investors. To analyze this phenomenon, this study carries out several stages, which are testing the market efficiency and estimating whether there are abnormal returns or not throughout the Christmas period. The consumer non-cyclical sector stocks in the accelerating trading board are used as the sample. The observation period is from 28 November 2022 to 20 January 2023 and is divided into two sub-periods. This study finds that market condition is inefficient before the Christmas event, resulting in higher abnormal returns and risks.

The relationship between oil prices and energy sector stocks in the global recession issue

Changes in world oil prices as a result of global issues have had a certain impact on the capital market in Indonesia. This study aims to examine the relationship between stock prices in the energy sector and fluctuations in world oil prices. Observations were made from January to April 2023 with a sample of 76 firms in the energy sector. The result of the analysis shows that stock prices in the energy sector have high variability throughout the observation period. In addition, this study finds that energy sector stock prices have a positive relationship with world oil prices.

The Impact of Carbon And Energy Prices on The Return of Energy Sector Stock in Selected Asia-Pacific Countires

The stock market is very important in the country's economy, namely as a source of corporate funding and especially in investments that have the aim of increasing the welfare of investors and companies. The purpose of this study is to analyze the effect of the rate of return on carbon costs, Brent crude oil, palm oil, interest rates, and exchange rates on the rate of return on energy stock prices in Asia-Pacific countries from 1st January 2016 to end of December 2021. In this study, the phenomena were explored utilizing quantitative approaches to collect data and test previously determined hypotheses. The panel data model is used, as well as the VECM (Vector Error Correlation Model) test. The results show that the influence of CO2 return on energy sector returns is negative in the short term but positive in the long term. Return on energy industry and return on Brent oil have both short-term and long-term unfavorable effects. The return of the use of palm oil has an advantageous long-term and short-term impact on the energy industry's return. The exchange rate has only a short-term negative relationship with the return of energy. Lastly, there is no long-term or short-term correlation between interest rates and the return on energy. The implication of this result is that industries must switch to using environmentally friendly devices and governments must declare regulations to emitters producers.

The Volatility of Stock Market in Indonesia During Covid-19 Crisis : Evidence from Consumer Goods Industry

This study aims to measure the volatility of stock in consumer goods industry. The analysis in this study utilize index value of consumer goods sectoral stock in 260 days. Using the paired t-test, it was discovered that stock index of consumer goods has significant change after the announcement of Covid-19 first case in Indonesia. The volatility of stock index was raised during the pandemic as measured from its standard deviation. Furthermore, the estimation of GARCH model revealed that consumer goods stock experienced a great volatility during Covid-19 crisis. The value of volatility persistence is 0,917 or close to 1, it means that the volatility was long-lasting as long as the economic crisis. The result of study could give the information for stock investor to be careful with their investment fund during the crisis. Meanwhile, the consumer goods companies can observe this result as consideration in determining the effective strategy in managing the company’s finances in the midst of an economic crisis.

A Study on the Effect of Portfolio Allocation on Mutual Funds

There are hundreds of mutual funds in the market, each offering different returns. The investors always look at funds which give high returns and have low risk. Thus while making a portfolio the asset management company should make investment allocations where returns are definite and to give justified returns for every rupee the investors pay, considering the different risks.
 
 The objective of the study was to find the short-term effects of portfolio allocation on the performance of mutual funds. The data for the study was consisted of the portfolio allocations and the performance statistics of one hundred and fifty-nine open-ended mutual funds, of which fifty were diversified debt/ income funds and one hundred and nine were diversified equity funds. These funds were further classified into different mutual fund schemes. Each of the mutual funds had a different portfolio and investments were made in different instruments like bonds, certificates of deposit, commercial papers, etc. (in case of debt) and in different sectors like technology, chemicals, services, etc. (in case of equity).
 
 The findings from the study indicate that, for debt funds, allocation in bonds and government securities tend to impact the performance of the fund, while for equity funds, allocation in engineering, energy, and service sector stocks tend to impact the performance of the fund.
 
 Keywords: asset management company, portfolio allocations, returns, performance, debt funds, equity funds.

Do gold and the US dollar diversify global sectoral risk? Evidence from connectedness and dynamic conditional correlation measures

The use of Information and Communication Technology (ICT) in fund management coupled with financial liberalization prompts us to explore the global sectoral connectedness and risk management potential of gold and the US dollar. The asymmetric interdependence (and behaviour) of financial markets (and their participants) further motivates us to understand the upside and downside market connections along with their mean-based connections. Variance decomposition-based spillover measures in vector auto-regressive space are used for that purpose. The mean-based total and directional spillover measures show that the global stock markets are highly connected at the sectoral level, reflecting higher odds of global sectoral shock transmission. The directional spillover measures further reveal that the industrial and financial sectors are systematically important sectors for transmitting global sectoral shocks. Their asymmetric and time-varying counterparts suggest that global sectoral connectedness dominates in downside markets and during crisis events. Specifically, the late European Debt Crisis, the Brexit referendum, the US-China trade war, and the COVID-19 pandemic are characterized by asymmetric and higher global sectoral shock transmission. We also show that the inclusion of gold and the US dollar with global sectoral stocks has the potential to diversify the global sectoral risk.

Invest Value Analysis Based on Risk, Profit and Market

In 2022, the post-pandemic period, the health sector stocks had a big difference in price performance between different stocks. Some stocks rose significantly because of the vaccines and specific drugs for covid-19, while others' growth slowed down or even had negative profit margins because people were afraid to go to the hospital which cause a reduction of other drugs' sales volume. In the health sectors, there're companies that research and development of drugs, distribute drugs, make medical apparatus and instruments, and even have some "grocery stores" like CVS. It might be difficult to find which stocks are worth the cost of implementation in the post-pandemic period and the special increase because Covid-19 has ended. This paper will analyze 3 stocks as an example to show the investment decisions between different investors. By using risk analysis, profit analysis, and market analysis, this paper will show the investment value of 3 stocks: CVS, MCK, and WBA. These analyses are based on PE, PB, ROA, ROE, profit margin, and many other ratios in 2022. This article will help people choose the health sector stocks. In the conclusion, MCK has the most investment value in 2023 and MCK has a stable income with low risk. WBA may be a bad choice.

Forecasting Taiwan stock returns via crude oil and gold futures

This study aims to predict Taiwan stock returns through gold and crude oil futures prices using monthly data from TAIEX and 19 stock sector indexes from January 1996 to December 2020. By using a 60-month rolling window horizon, we compare the forecast performances of various regression models, where the forecast performances are measured by MAE (mean absolute error) and ROS2 (out-of-sample R-square). In addition to using spot returns and the first principal component of futures returns on gold and crude oil, five traditional financial variables (dividend to price ratio, earnings to price ratio, market price to book value ratio, long-term yield, and short-term yield) are added to the regression model to explain and predict stock returns. Given that the regression models have included these traditional financial variables, the empirical results reveal that adding gold or crude oil price information to the model substantially improves its explanatory ability. Additionally, except during periods of high stock returns, the forecast ability of crude oil price information on stock returns is significantly better than traditional forecast variables. Furthermore, although gold prices are not as accurate as crude oil prices in predicting stock returns, their predictive capabilities are often better than the traditional financial variables.

Implications of war on the food, beverage, and tobacco industry in South Korea

The Food, Beverage & Tobacco (F&B) industry is an essential sector in the competitive economy. Procurement of production factors mainly depends on sales forecasting and the supply chain of raw materials. However, the conflict between Russia and Ukraine has jeopardized the global supply chain. As the conflict worsened, the world faced a food crisis, which was already a significant challenge due to the Covid-19 pandemic. Understanding how conflict-related disruptions in global food markets might affect the stock return of the F&B industry of South Korea, this study forecasts the stock returns on the KOSDAQ F&B sector. This paper highlights that the conflict resulted in immediate and far-reaching consequences on the global food supply chain and future crop harvesting in South Korea. As numerous algorithms have been widely used in predicting stock market returns, we use Autoregressive Integrated Moving Average (ARIMA) model for the prediction. Using daily returns from the KOSDAQ F&B industry from January 1999 to October 2022, the study proposes an ARIMA (2,2,3) model to forecast future movements of the stock returns. With an RMSE of 0.012, the prediction performance holds good using the ARIMA model. The results show a negative trend observed in the F&B sector returns for a few months, implying that sector stock returns decline as the conflict between Russia and Ukraine becomes more pronounced. This study also suggests that South Korea has massive scope to stabilize the demand for healthy, safe food, give more attention to domestic agribusiness, and make itself a self-sufficient agri-economy.

Hedge and safe-haven attributes of faith-based stocks vis-à-vis cryptocurrency environmental attention: a multi-scale quantile regression analysis

ABSTRACT The attractiveness of the equities of the Islamic faith-compliant companies as a hedge or possible diversifier has been underscored; however, there is a lack of empirical research on their safe-haven and hedge attributes against changes in the level of cryptocurrency environmental attention (ICEA). We examine whether various distributions of the ICEA possess a significant predictive power on various quantiles of Islamic sectoral stock returns by employing weekly data on the ICEA and Shariah-compliant stocks from 10 sectors of economic activity and base their multi-scale analysis on the complete ensemble empirical mode decomposition (CEEMDAN) approach. We present the asymmetric causality-in-means and quantile-on-quantile regression between the ICEA and Islamic stocks. The empirical results show a significant predictive power of the ICEA on various quantiles of Islamic sectoral stocks in the medium- and long term. We find that the safe-haven and hedging attributes of investments in Islamic stocks are sector-dependent across the medium- and long-term scales. Hence, our findings emphasize that based on market states, possible safe-haven attributes, diversification opportunities, and hedges for cross-sectoral investments with Islamic stocks are viable along various investment horizons for diverse levels of cryptocurrency environmental attention. These findings provide original valuable insights for portfolio management and improving financial stability.