Defensive Stocks Research Articles

Does Investment in Defensive Stocks Act as a Buffer during Market Downturns?

The study examines the performance of defensive stocks during market downturns in the Indian stock market. The research focuses on the period from January 2000 to December 2023. In this study selected stocks from the Fast-Moving Consumer Goods (FMCG) sector (HUL, ITC, Britannia Industries) and Pharma sector (Sun Pharmaceuticals Industries, Dr Reddy Laboratories and Cipla) have been taken into consideration. Five key metrics are covered to assess the stock’s performance: Stock return, Correlation, Beta Compound Annual Growth Rate (CAGR), and Dividend yield. For stock return a comparison is made between stock market return and selected stock return, also the average return of each stock is calculated and compared with the average market return during market downturns. Correlation has been used to understand if there is a relationship between stock returns and nifty returns. Beta has been used to understand the sensitivity of the stock in relation to the market and Compound Annual Growth Rate has been used to analyze the long-term stability of each stock. The average dividend yield is calculated to understand the extra return that an investor can get on his investments on top of capital gain. The study findings revealed that incorporating stocks from the Fast-Moving Consumer Goods (FMCG) and Pharmaceutical (Pharma) sectors protects investors against market downturns, Additionally, the research highlights the long-term stability of returns associated with defensive stocks, making them a valuable component for investors seeking portfolio diversification and a buffer against market fluctuations. Keywords: Defensive Stocks, Market Downturns, Stock Market Return, Beta, CAGR, FMCG, Pharma.

Clustering Defensive Shariah-compliant Stocks Using Financial Performance as the Indicator

Malaysian stocks, including Shariah-compliant stocks, have experienced turbulence last year. Although there are defensive stocks, the well-performing ones are not easily identified. Researchers have proposed various metrics to identify defensive stocks. However, most of the approaches require human intervention. In this study, we focus on Shariah-compliant stocks and propose to automate the labeling of stocks in terms of their financial performance via clustering. The study aims to identify the optimal clustering method to label the clusters. This was achieved by first employing k-Means, Agglomerative, and Mean Shift clustering to group similar stocks before labeling. When labeling, the criteria to distinguish well-performing defensive Shariah-compliant stocks were high dividend yield, low price-earnings ratio, low Beta value, and low price-to-book value. After labelling each stock with its financial performance (Low, Medium, High), we performed classification using Logistic Regression, k-Nearest Neighbors, Support Vector Machine, Decision Tree, and Random Forest to verify the credibility of the labels. Based on the results, the clusters created by k-Means clustering outperformed the rest in matching accuracy. Further investigation was conducted on the k-Means data set by dividing the data according to sector and classifying each sector’s data separately. Logistic Regression outperformed other classification algorithms with an accuracy of 71.5%. The findings also suggested accuracy increased when stocks were classified according to sectors. Further considerations include performing outlier analysis on the data to select well-performing stocks.

Perbandingan Kinerja Sub Sektor Makanan-Minuman dan Farmasi pada Kasus Pertama Covid-19 di Indonesia


 
 
 
 Research aim : This study aims to prove whether the consumer goods sector is a sector that is immune to the Covid-19 pandemic, considering that investment in this sector is an investment in defensive stocks.
 Design/Methode/Approach : Apply an event study approach, this study will compare the abnormal returns on stocks in the food-beverage and pharmaceutical sub-sector before and after the first case of Covid-19 entered Indonesia.
 Research Finding : This study showed a significant differences in positive abnormal returns before and after the first case of Covid-19 in the stocks of the food-beverage sub-sector. However, it is different from the pharmaceutical sub-sector. It has a positive abnormal return difference before and after the first case of Covid-19, but it is not significant statistically.
 Theoretical contribution/Originality : In addition to being influenced by internal factors, stock performance is also influenced by external factors and even external factors outside the market, such as the Covid-19 Pandemic. The Covid-19 Pandemic has impacted a country's economy due to anticipatory policies undertaken to reduce the spread of the virus, including work-from-home and social distancing.
 Practitionel/Policy implication : Investments in the Consumer Goods sector, in this case, the food-beverage and pharmaceutical sub-sector during the Covid-19 Pandemic, need to be included in the stock portfolio because its performance is stable and tends to increase. Investment in Consumer Goods sector stocks is essential as a defensive stock to stabilize the stock portfolio's performance. Especially during the Covid-19 period, the primary basic human needs are still needed, especially health and the need for PPE (Personal Protective Equipment), vaccines, and medicines the Pandemic.
 Research limitation : The event window is too short, namely, only five days before the event day and five days after the event. It is recommended that the number of days the event window can be extended so that the abnormal return reaction to the event of the first case of Covid-19 can be better analyzed. 
 
 
 
 

Impact of global macroeconomic factors on spillovers among Australian sector markets: Fresh findings from a wavelet‐based analysis

AbstractThis study investigates the spillover dynamics among 10 Australian sectoral indices and their connectedness to global factors, including the WTI crude oil price, oil market volatility, Australian exchange rate, U.S. stock market volatility index and Infectious Disease Tracker Index. Using data from May 14, 2007 to March 31, 2022, this study applies the time‐varying parameter vector autoregressive model to study their static and dynamic connectedness, wavelet coherence analysis to investigate the time‐frequency co‐movement of global macroeconomic factors with Australian sector stock indices and wavelet decomposition‐based Granger causality. The results show that aggressive stocks (Industrials, Consumer Discretionary and Financials) are net transmitters, while defensive stocks (Health, Information Technology, Communication and Utilities) are net receivers of spillovers. The coronavirus pandemic has increased systemic risk, causing radical changes in net connectedness. Additionally, global macroeconomic factors drive the connectedness of the Australian sectoral indices, with oil and exchange rates moving in phase, and oil volatility, stock volatility and the Infectious Disease Tracker Index moving in antiphase. Global stock and oil market volatility has a significant impact on the Australian sector's returns over short‐, medium‐ and long‐term horizons. This study provides valuable insights to investors and policymakers by carefully examining the relationships between global factors and Australian sectoral indices.

Effect of the BI Rate, Inflation and Exchange Rates on Consumer Goods Stock Prices

In the midst of the current economic conditions, with an increase in Bank Indonesia's interest rates, consumer sector stocks became the main choice for investors, because they are defensive stocks. Investors tend to accumulate stocks in this sector, after the post-Covid economic recovery has occurred, the public has the potential to increase consumption, this is expected to have an impact on the condition of consumer goods stocks. The capital market has a very important role for all sectors, both private, government and society in general. Investors must pay attention to macroeconomic variables including Bank Indonesia interest rates, inflation and the Rupiah exchange rate. Under these conditions, research was conducted with the aim of analyzing, testing and concluding the influence of the BI Rate, Inflation, and the Rupiah exchange rate on consumer goods stock prices on the Indonesian Stock Exchange for the period 2018 – 2022. Using secondary data on companies listed on the Indonesia Stock Exchange, has complete financial reports, has stock price information from January 2018 to October 2022. Analysis data is processed using multiple linear regression and classical assumption tests with quantitative analysis techniques using SPSS 25. The results show simultaneously the influence of the BI Rate, Inflation, Rupiah exchange rate against consumer goods stock prices.

The Mirror of Malaysia Real Estate Investment Trust Stock Return in the Short-Run Dynamics

The formation of Islamic capital market under the subcomponent of Islamic financial system scratch a milestones development of Islamic finance in Malaysia. The Islamic capital market operates in mirror with convention capital market in expending, deepening and broadening Malaysia financial system. Malaysia is one of the REIT markets that value both the Islamic and conventional practices, such flexibility makes the attract not only to the local investor but also Islamic investors and foreign investor. The major source that generates income for REIT is the rental of the commercial real estate invested and hold as portfolio by the REIT management company. Furthermore, Malaysia REIT is known to be defensive stocks which consist of cyclic income producing assets that has some potential of asset appreciation. On the other hand, it witnessed by the moderation of Malaysia government bond yields created a lower pressure on the REIT stock price and analyst’s report highlighted the uncertainties on global crude oil prices and inflation is main concerned to REIT investors. In addition, the revision of 2019 tax system in Malaysia furnished a long run affected the dividend payout and volatility of REIT stock price. Therefore, this impact on the REIT stock liquidity and trading volume experiencing anil liquid trading. Therefore, the impact of external forces towards the mirror of two type of Malaysia REITs is significant to the investors, policy makers and government to outline the short-run relationship and facilitate future growth. The Vector auto regression model, granger causality and variance decomposition employed in this study to analyze the mirror of two types Malaysia REIT stock return. The empirical finding shows that the variability of dividend yield is vital explanatory variables to explain the both type of REIT stock return in Malaysia followed by interest rate for Islamic REIT stock return. The mirror of conventional REIT further implicated that trading volume and global crude oil price are useful to forecasting the changes in the stock return. Nutshell, this study provides a discussion of Malaysia REIT stock return behavior and it should be given necessary attention by researchers in ensuring the newly develop Islamic REIT are competitive and stability as the conventional REIT.

The behaviour of U.S. stocks to financial and health risks

AbstractThis article examines the hedging effectiveness of U.S. stocks against uncertainties due to equity market (financial risk) and pandemics (health risk), including Covid‐19 pandemic. Consequently, we consider two categories of U.S. stocks—defensive and non‐defensive stocks drawn from 10 different sectors and distinctly analysed over two data samples—pre‐ and post‐Covid periods. We construct a predictive panel data model that simultaneously accounts for both heterogeneity and common correlated effects and also complementarily determine the predictive power of accounting for uncertainties in the valuation of U.S. stocks. We find that hedging effectiveness is driven by the types of stocks and measures of uncertainty. Defensive stocks provide a good hedge for pandemic‐induced uncertainty, and the hedging effectiveness is higher during calm market conditions as compared to turbulent conditions, while both categories lack hedging capability in the face of equity‐induced uncertainty. Finally, we find that the inclusion of uncertainty in the predictive model of U.S. stock returns improves its forecasts and this conclusion is robust to alternative measures of uncertainty and multiple forecast horizons.

The impact of macroeconomic variable movements on stock price index performance in consumer goods industry sector companies: Evidence from Indonesia

This research essentially aims to examine the extent to which macroeconomic variables (including inflation, exchange rate, and interest rate) have a significant influence on stock price index and the level of significance for that influence. The researchers focused more on consumer goods industry companies that are listed on the Indonesian Stock Exchange (IDX) within 2015 until 2019, with consideration for the stock price of consumer goods companies listed on the Indonesia Stock Exchange (IDX) as claimed to be the most defensive stock. This study finds that inflation, exchange rate, and interest rate, as composite variables, have a significant influence on stock price index. A partial test revealed that inflation, and exchange rate have negative significant influence on stock price index, while interest rate is found to be nonsignificant.

Understanding Defensive Stocks with Company Fundamentals and Dividend Policy Variables as Moderation

The purpose of this study was to determine the effect of Return on Equity, Firm Size, Debt Equity Ratio and Price Earning Ratio on return defensive stocks with Dividend Policy as Variable Moderation in Manufacturing Companies. The study population was manufacturing sector companies listed on the Indonesia Stock Exchange from 2015 to 2018. There were 61 companies sampled using purposive sampling techniques. The analytical method uses multiple linear analysis and moderated Regression analysis. The results showed the Firm Size variable had a significant positive effect and the DER variable had no significant positive effect while the ROE and PER variables had no significant negative effect on return defensive stocks. The MRA test states that the Dividend Payout Ratio variable strengthens the effect of Firm Size on return defensive stocks while the ROE, DER and PER variables are weakened by the effect on return defensive stocks by dividend policy. Future studies are expected to use other variables that might increase or decrease stock returns.

Determinants of Dividends in the Telecommunications Sector

Purpose – T elecommunications stocks are known to be defensive stocks, which are less susceptible to volatility in the global financial markets and usually pay higher dividends than in other industries. In this context, this paper intends to study the influence of some specific characteristics of these companies on the payment of dividends . Design/methodology/approach – To achieve the proposed objective, the panel data methodology was used, specifically the GMM estimation method for a sample consisting of 34 companies listed in Western Europe and North America in the period between 2007 and 2016 and in the sub-period between 2008 and 2013 , which comprises the global financial crisis. Findings – The results show that specific factors such as investment in fixed capital, indebtedness, price to book value ratio, free cash flow (FCF), liquidity , and dividends paid in the previous year are decisive in explaining the dividends distributed in the entire period. For the financial crisis period , the sign and significance of the variables remain almost unchanged, suggesting that these companies pay dividends regardless of economic cycles, covering the absence of FCF with adequate liquidity levels to satisfy investors during recessive periods. Originality/value – Our study contributes to a better understanding of the telecommunications sector and the dividend policy carried out by managers in this sector, and it can assist in the analyses of investors, other managers, financial analysts , and researchers on the subject.

Determinants and Prediction Accuracy of Price Multiples for South East Asia: Conventional and Machine Learning Analysis

The present study evaluates determinants of price multiples and their prediction accuracy using ordinary least square (OLS) regression and machine learning-based shrinkage methods for the South East Asian markets. Price multiples examined in the research are price to earnings (P/Es), price to book (P/B), and price to sales (P/S). Data has been collected from Thomson Reuters Eikon. The study recommends that the P/B ratio is the best price multiple for developing a price-based valuation model. Beside fundamental determinants of the multiple, various firm-level control variables, namely, firm size, cash holding, strategic holding, stock price volatility, firms’ engagement in Environment, Social, and Governance (ESG) activities, dividend yield, and net profit margin impact firm’s P/B multiple. Positive coefficients of consumer non-cyclical and healthcare dummies indicate a preference for defensive stocks by the investors. Application of machine learning-based shrinkage methods ensures the accuracy of prediction even with out-of-sample forecasting.

Portfolio Optimization for Stock Market in Ghana Using Value-at-Risk (VaR)

The study was conducted to identify the performing stocks as well as examine the portfolio optimization with associated Value at Risk (VaR) for some selected stocks on the Ghana Stock Exchange (GSE). A historical data of 15 companies categorized into Financial Stock Index (FSI) and Composite Index (CI) from 2000 to 2017 were obtained from Bank of Ghana (BoG), Ghana Stock Exchange (GSE) and Gold Coast Security (GCS). From the study, ETI, HFC, SIC, TOTAL, FML, UNIL and GOIL stocks were identified to be over performing on the Ghana Stock Exchange. Also, CAL, EBG, ALW, AYRTN, GOIL were identified as aggressive stocks; GCB, SCB, TOTAL, GGBL as defensive stocks; and ETI, HFC, SIC, FML, PZC, UNIL as inversely moving towards the market return. The optimal portfolio asset allocation, for the minimum VaR portfolio showed a marginal diversification in other stocks in the cases of FSI, but greater portion was invested in HFC. However, in the case of CI displayed no indication of diversification in the portfolio as 67.30% of investors invested in AYRTN and only 32.70% in the remaining securities. The study then proceeded to find the optimal portfolio with risk-free asset for both indexes. It was recommended that further study should extend the approaches used by considering Conditional Value at Risk (CVaR) as the VaR measure does not give any information about potential losses in the worst cases.

IMPACT OF CONSUMER SENTIMENT ON DEFENSIVE AND AGGRESSIVE STOCK RETURNS: INDIAN EVIDENCE

This paper aims to study predictive ability of consumer sentiment of individual stocks. We consider two proxies for sentiment. One is explicit (Index of Consumer Sentiment, ICS), second is implicit (Broad Market Indicator, SP contrarily no such relation exists between explicit sentiment indicator and stocks. We find causation from ICS to S&PBSE500. Both the sentiment indicators have causal relation with aggressive stocks but not with defensive stocks. Result show that only ICS has short-term predictive power of aggressive stocks. We find significant negative relation between consumer sentiment and aggressive stock returns in the following month. This implies high consumer optimism in current month results in price shrink of aggressive stocks in following month. We conclude that implicit sentiment indicator has no predictive ability of stocks and explicit sentiment indicator is able to predict only small number of aggressive stocks. We suggest investors not to follow sentiment indicators blindly because these indicators predictive ability is very limited that too with select aggressive stocks. We find aggressive stocks have high volatility and gain investor attention during optimistic and pessimistic market conditions.

Comparing between Investing in Food, Telecommunications, and Transportation Industries in Thailand

This paper attempt to answer which is a good investment in Thailand if the only choice is between food, telecom, and transport industries respectively. To compare which is an acceptable investment, The Capital Asset Pricing Model (CAPM) used to look at expected returns during 1 January 2008–1 January 2018. Beta is used to measure the risk of investment. In the Sharpe the higher ratio, the better the portfolio by using the historical data to determine the good investment. The food industry is a better investment than SET and Thailand 10 year bond for the Thai market. Because the food industry is defensive stocks, it tends to have stable performance in economic downturns and upturns. This paper looking at a forecast of a daily expected a return by using the expected return from CAPM and Beta this paper found that Transport industry is a good forecast investment in Thailand because with the “transport network project” from the Thai government to improve the transport in Bangkok. And Transport industry is cyclical stocks they are sensitive to economic fluctuations and tends to exhibit more radical swings, correlated with the overall business cycle.

Fractality in market risk structure: Dow Jones Industrial components case

We examine the Dow Jones Industrial Average index components with respect to the capital asset pricing model (CAPM), specifically its scaling properties in the sense of different investment horizons. To do so, we use the novel methods of fractal regressions based on the detrended cross-correlation analysis and the detrending moving-average cross-correlation analysis. We report three standard groups of stocks – aggressive, defensive and market-following – which are rather uniformly represented. For most of the stocks, the β parameter of the CAPM does not vary significantly across scales. There are two groups of exceptions. One of aggressive stocks which are even more aggressive for short investment horizons. These do not provide portfolio diversification benefits but allow for high profits above the market returns and even more so for the short investment horizons. And the other group of more defensive stocks which become very defensive in the long term. These stocks do not deliver short term profits but can serve as strong risk diversifiers. Apart from these direct results, our analysis opens several interesting questions and future research directions, both technical and experimental, which we discuss in more detail.

Are polish healthcare stocks defensive?

The main aim of this article is to verify whether the companies operating in Polish healthcare industry could be included into the group of so called defensive companies. The value of such companies during recession does not decline or the declines are significantly lower compared to the major stock indexes. The analysis carried out in the article is conducted amongst companies from healthcare sector listed on the Warsaw Stock Exchange (WSE). In the article an analysis is presented comparing risk ratios of defensive stocks and whole stock market such as beta coefficient (β). The analysis is based on daily data intervals from the period 2012–2014. The article is based on the assumption that Polish healthcare industry companies may be portrayed as defensive and the results of the study suggest to support this point of view. Therefore, the stocks of such companies can be considered by investors as interesting assets for building diversified portfolios and working on investment strategies.

Measuring the Systematic Risk of Stocks Using the Capital Asset Pricing Model

Among the paramount information in the stock market is the awareness of the systematic risk of stocks which plays essential role in investment choices. This paper measured the systematic risk of seven stocks on the Ghana Stock Exchange (GSE) using monthly closing prices and the 91 day T-bill from the period 2011 to 2015. The CAPM was employed in measuring the systematic risk of the stocks. The results revealed that, CAL, FML and TLW were defensive stocks since each had a market beta less than one (1). PBC, CLYD, EGL and UNIL had the same systematic risk as the market since each recorded a market beta of one (1). All the seven stocks each had a positive market beta implying that they move in a similar manner as the market. The compensation for investing in each of the stock was approximately at 3%. The diversifiable risk associated with each of the stock was very low since few of the returns were scattered along the regression line.

Ryzyko rynkowe akcji spółek notowanych na giełdach w strefie euro

Artykuł opisuje zagadnienie ryzyka rynkowego akcji spółek notowanych na giełdach w strefie euro. Głównym celem artykułu jest prezentacja badań pokazujących zmiany w procesie inwestowania po wprowadzeniu waluty euro oraz wskazanie poziomu ryzyka systematycznego, rynkowego, niepodlegającego dywersyfikacji dla głównych spółek notowanych na giełdach strefy euro w okresie 2010–2013 z wykorzystaniem narzędzi nowoczesnej teorii portfelowej.Przeprowadzone badanie polegało na podzieleniu akcji europejskich blue chipów z indeksu EURO STOXX 50, na agresywne i defensywne w oparciu o oszacowanie parametru beta na podstawie modelu jednoindeksowego Sharpe’a. Wyniki badania wskazały, że 12 analizowanych akcji to akcje spółek defensywnych, czyli uznawanych za bezpieczne, zaś akcje 10 spółek można uznać za agresywne, czyli wybierane przez inwestorów ze skłonnością do ryzyka.

Risk Factors in Energy Utility Returns: An Augmented-Four-Factor Model

In this paper we utilise the risk factors from both the finance and energy economics literatures to develop an improved asset pricing model (the Augmented-Four-Factor Model or AFFM) in the context of the European energy utility sector. In addition, we undertake inter-sectoral and inter-temporal analyses using the risk factors in our AFFM. Our results show our AFFM captures the greatest proportion of returns relative to other models. Further, stock market risk factors (most notably the market, size, value and momentum premia) explain a much greater proportion of average returns than term and commodity risk factors. Our inter-sectoral results show that, relative to other sectors, energy utilities are defensive stocks over the period analysed (1996 to 2013). However, our inter-temporal analysis shows that market beta has been increasing through time, from 0.710 in 1996 to 1.037 in 2013; the European energy utility sector is becoming increasingly exposed to systematic risk. Further, despite regulatory changes, designed to counteract the dominance of big energy utilities, the size premium has increased over time. Finally, the value and momentum premia are evident one to two years after the three EU energy sector liberalisation packages of 1996 and 1998, 2003, and 2009. In particular, the energy sector becomes extremely distressed following the third liberalisation package.

Value-weighted price return index for plantation sector of Colombo Stock Exchange of Sri Lanka

Plantation sector plays a vital role in Colombo Stock Exchange (CSE) in Sri Lanka. This study constructed a Plantation Sector Index (PSI) for comparing the performance of the sector during war and post-war periods. Results indicated a significant decline in PSI during war period and a growth in post-war period. Further, the comparison of PSI with All Share Price Index (ASPI) of CSE showed PSI's defensive stock behaviour during the two periods. Finally, the study employed best-fitted ARIMA (1,1,0) model and seasonal ARIMA (0,1,1) × (0,1,1)30 model of post-war period to forecast PSI compared to Holt-Winters method. Holt-Winters method provided a significantly best prediction for PSI during post-war period with the level (α = 0.2), trend (β = 0.2) and the seasonal (γ = 0.2) components under 95% confidence interval. Therefore, PSI would be recommended for financial analyses, and investment decision making in plantation sector.