Big Stocks Research Articles

Cross-section without factors: a string model for expected returns

Many asset pricing models assume that expected returns are driven by common factors. We formulate a model where returns are driven by a string, and no-arbitrage restricts each expected return to capture the asset's granular exposure to all other asset returns: a correlation premium. The model predicts fresh properties for big stocks, which display higher connectivity in bad times, but also work as correlation hedges: they contribute to a negative fraction of the correlation premium, and portfolios that are more exposed to them command a lower premium. The string model performs at least as well as many existing linear factor models.

Do I slamic S tocks Outperform C onv entional S tocks During C risis Periods? A Global Comparison

Purpose: This study examines the performance of Islamic and Conventional stock indices during the Covid-19 pandemic crises. The aim of the study is to find the existence of safe havens in Islamic stock indices.
 Design/methodology/approach: The study uses mean and cumulative return values and the GARCH (1 1) model to examine the volatility performance of stock returns and the impact of Covid-19 on both indices.
 Findings: Our findings indicate that Islamic stock indices tend to outperform conventional indices during crisis periods, particularly in developing economies and in the short term. However, conventional stock indices exhibit stronger performance in the long run and post-crisis periods. Moreover, the study reveals that the effects of Covid-19 cases and deaths on both indices vary across countries. Additionally, Islamic stock returns demonstrate lower volatility compared to previous shocks and returns, whereas conventional indices experience higher volatility, particularly in developing countries. Therefore, the s tudy establishes that I slamic indices can serve as safe havens for investors in certain countries, but not universally.
 Research limitations/implications: The study can be extended and more effective by adding more crisis events and a number of years to examine long-term stock moments. The study can be helpful for investors in designing investment portfolios, especially in times of crisis where the majority of investors try to find safe havens for investment.
 Originality/value: This study is the first to examine the impact of recent crises on Islamic and conventional stock indices in the world's big stock markets. The study is also the first one to use the longest data period among the recent studies to differentiate the performance of Islamic and conventional indices.

Lottery preference, short-sale constraint, and the salience effect: Evidence from China

This paper documents the significant and robust salience theory (ST) effect in China, which differs from the findings in the literature. First, the upside-ST effect from stocks with salient upsides is stronger than the downside-ST effect from stocks with salient downsides; the opposite pattern is documented in the US market. We demonstrate that this pattern is due to strong lottery preference and short-sale constraint in China, where investors are prone to engage in salient thinking when they bet on lottery stocks; meanwhile, short-sale constraint prevents rational investors from correcting salience-induced mispricing. Second, the salience effect remains strong in big stocks and high institutional ownership stocks. Our findings are consistent with the existing evidence that fund managers cater to fund investors' lottery preferences to hold lottery stocks. Our study provides new insights into the sources of the salience effect in China, especially salience's interaction with investor behaviors and the market's institutional characteristics.

Machine learning and the cross-section of emerging market stock returns

This paper compares various machine learning models to predict the cross-section of emerging market stock returns. We document that allowing for non-linearities and interactions leads to economically and statistically superior out-of-sample returns compared to traditional linear models. Although we find that both linear and machine learning models show higher predictability for stocks associated with higher limits to arbitrage, we also show that this effect is less pronounced for non-linear models. Furthermore, significant net returns can be achieved when accounting for transaction costs, short-selling constraints, and limiting our investment universe to big stocks only.

RIM-based value premium and factor pricing using value-price divergence

We document that value-to-price, the ratio of Residual-Income-Model-based valuation to market price, subsumes the power of book-to-market ratio and many other value or quality measures in predicting stock returns. Long-short value-to-price portfolios hedge against momentum, revitalize the seemingly missing value premium over past decades, and generate significant returns after adjusting for common factors. The value-price-divergence (VPD) factor constructed from the average returns of these portfolios within small and big stocks is not spanned by these known factors. Max Sharpe ratio and constrained R-squared tests reveal that VPD is a better substitute for the traditional value factor and that a four-factor model using the VPD, market, momentum, and size factors outperforms most extant benchmarks in explaining the cross-section of expected equity returns, including value-to-price portfolios as test assets. The findings remain robust under alternative specifications of equity cost of capital.

Two faces of the size effect

This study finds that the size effect has two faces that are predictable from forward-looking signals: conditional on an up signal, small stocks outperform big stocks; conditional on a down signal, big stocks outperform small stocks. Managing size strategies according to the two faces achieves significant performance improvements unexplained by common risk factors. Moreover, the two-faced size effect remains robust to stylized facts that invalidate the unconditional size effect. The conditional performance is consistent with the evidence that the prices of small stocks respond slowly to information shocks and is mainly driven by the conditional difference in cash-flow shocks between small and big stocks. Overall, our findings not only show that both small-minus-big and big-minus-small premiums exist but also highlight the necessity of accounting for these two faces when assessing the size effect.

Application of Fama-French five factor model in US clothing industry during COVID-19

During the COVID crisis, the US clothing industry has suffered a great plunge due to vast store closures and business discontinuation. People must understand in what aspects this crisis impacted on the clothing industry. This paper aims to analyze the impact of COVID-19 on US clothing industry return and risk. We used data in a one-year span before and during COVID-19, respectively, from the Kenneth French Data Library. This study applies the Fama & French 5-factor asset pricing model and adopts the multiple linear regression method for analysis. We tried to identify which factors in the model explained the COVID returns and how their explanatory power changes before and during COVID. It is interesting to evaluate that size, value, and investment factors were all insignificant before the crisis, but all turned significant during COVID-19. Also, discovering that growth stocks outperformed value stocks during the crisis was not the case before the crisis. It could be attributed to investors' speculation intent becoming stronger amid the distressing environment of the pandemic. Firms in clothing industries were investing conservatively due to a shortage in cash flows in extreme uncertainty. Small stocks performed better than big stocks during the crisis. It speculates that bigger-size firms were shattered more as they occupied greater market share and thus undertook more loss than smaller-size firms. In short, during the COVID period, small stocks, growth stocks, and conservative stocks performed more strongly and were thus more favourable to investors.

Herd behaviour in an emerging market: an evidence of calendar and size effects

PurposeThis study aims to examine investors’ herd behaviour for various calendar events and size-based stock portfolios in Pakistan. The authors consider three calendar effects, crisis (COVID-19 and financial crisis 2018–19), announcement of political news and popular calendar anomalies (month-of-the-year and day-of-the-week), and investigate the impact of stock size on calendar effect in terms of investors’ herd behaviour.Design/methodology/approachThe study uses non-linear specification to capture herd behaviour using firm-level daily data for 496 stocks listed on Pakistan Stock Exchange over the period 2001–2020.FindingsThe results indicate herd formation during periods of COVID-19, financial crisis, political news announcements and January (month-of-the-year). The authors also observe significant herding for the biggest and smallest size stocks over complete period. However, the authors find more pronounced herding in big stocks during January as compared to the more noticeable herding in small stocks over complete period. The findings suggest that herding in small stocks is not the main cause of January herding and hint on the prevalence of significant institutional herding during January.Practical implicationsThe stock prices destabilize because of the mimicking behaviour during crisis periods, days of political announcements and month of January. Implementation of insider trading laws and transparent information environment can help in reducing these effects and increasing market efficiency.Originality/valueThe authors consider the recent COVID period in our analysis. In addition, we provide new evidence on the possible impact of stock size on calendar effect in terms of herd behaviour, which, to the best of the authors’ knowledge, has not yet been documented in literature.

The Wisdom of the Robinhood Crowd

ABSTRACTRobinhood investors increased their holdings in the March 2020 COVID bear market, indicating an absence of collective panic and margin calls. This steadfastness was rewarded in the subsequent bull market. Despite unusual interest in some “experience” stocks (e.g., cannabis stocks), they tilted primarily toward stocks with high past share volume and dollar‐trading volume (themselves mostly big stocks). From mid‐2018 to mid‐2020, an aggregated crowd consensus portfolio (a proxy for the household‐equal‐weighted portfolio) had both good timing and good alpha.

Pakistan: a study of market's returns and anomalies

Purpose This paper aims to expand foreign investors' understanding of potential return enhancement and risk diversification advantages offered by equity market of Pakistan through comparing its performance to performances in other markets and investigating what matters for investing in Pakistan's market.Design/methodology/approachComparative analysis of Pakistan Stock Exchange is performed using data for 22 developed and 22 emerging markets over the period 1993–2019. Cross-sectional analysis is performed using data for 130 non-financial firms from Pakistan and Carhart (1997) and Fama and French (2015) models are applied. The role of liquidity with five-factor model is analyzed using turnover rate and Amihud (2002) illiquidity cost as liquidity measures.FindingsPakistan's equity offers substantial diversification benefits if added to developed market portfolios. However, observed large returns come together with inverted premia for most traditional factors indicating that investors may want to invest preferably in big stocks with low book-to-market and momentum. Finally, global investors can invest in high yielding stocks with low liquidity risk owing to positive connection between liquidity and returns.Practical implicationsThis study will provide investment model for foreign investors to enhance their portfolio returns. Policy makers in Pakistan must identify regulatory steps to facilitate foreign investments.Originality/valueTo the best of the authors' knowledge, this is the first study which identifies efficiency gains offered by Pakistan's equity for global investors.

Impact of climate change on BIST 30 index using VAR model

Purpose- Global warming has caused an increase in the frequency and severity of extreme weather events in many parts of the world, including Turkey, over the past several decades. This study examines the effects of weather disasters on the Borsa Istanbul stock market from 2009 to 2019 using the BIST 30 Index. Methodology- In the study, the short–term relationship between the Borsa Istanbul Stock Exchange (BIST30) index and climate change for the period January 2009 – December 2019 was analyzed using the VAR model, and Granger causality test, effect-response test and variance Decoupling tests were applied, respectively. In climate change we take 2 variable which are temperature and precipitation. Findings – The impact of weather-related calamities on stock market volatility and returns has been found to be insignificant. BIST30 index has no effect of climate change and vice versa. A one-way relationship found between Temperature and the precipitation, and a short-term positive effect-response was found between these variables. Conclusion – In conclusion we can say that climate change is one of the harsh reality which starts in recent years, and we can’t ignore it. It has been determined that the BIST 30 index has not been impacted by climate change in Turkey. which mean 30 best performance companies but maybe it affects small companies and big stock exchanges like Nasdaq, FTSE, and others.

Goat Husbandry: An Opportunity to Strengthen Rural Economy in Devipatan Region (Trans-Ghaghara) of Uttar Pradesh

Agriculture is the main economic activity in India which mostly practiced in association with livestock husbandry. Goat is one the most important species of livestock which reared by the poor and socio-economically backward section of rural population. Great market demand for livestock product, diversification of agriculture, rising unemployment level, nutritional requirements, lack of capital to purchase the big ruminants and lack of labour to rear the big animal have fuelled the growth of goat rearing in India. Present study has been under taken to understand the distribution of goat population in time and space, their density and share in total livestock and explore the causes of growth of goat husbandry, in the form of milk and meat production, employment and income generation. The role of goat rearing in rural socio economic transformation has been also explored for development of strategy for alleviation of rural poverty and women economic empowerment in the study area. Devipatan region in Eastern Uttar Pradesh has been selected as the study area to conduct the study. The study has revealed that goat has increased by 21.74 percent in the study area. It also revealed that 20.69 percent Hindu and 78.16 percent are Muslims are rearing goat. The caste-wise involvement shows that there are 20.00 percent Schedule caste, 71.92 other backward castes and 7.69 High caste goat farmers. The cost –income analysis showed positive performance with income over total production cost at least Rs.11854.00 per female goat per annum which varies with stock size up to Rs.14000.00 for big stock size (more than 12 female adult goat). Moreover, nutrition intake is also improved through consumption of milk produced and indirectly helps in saving expenditure for purchasing milk from outside. 71.79 percent responded in positive for improvement in nutrition intake. Economic women empowerment through this occupation is also enhanced as believed by 83 percent of respondents.

Does the low-risk anomaly exist in the Indian equity market? A test using alternative risk measures

PurposeThis study aims to investigate the risk-return trade-off in the Indian equity market at both the aggregate equity market level and in the cross-sections of stock return using alternative risk measures.Design/methodology/approachThe study uses weekly and monthly data of 3,085 Bombay Stock Exchange-listed stocks spanning over 20 years from January 2000 to December 2019. The study evaluates the risk-return trade-off at the aggregate equity market level using the value-weighted and the equal-weighted broader portfolios. Eight different risk proxies belonging to the conventional, downside and extreme risk categories are considered to analyse the cross-sectional risk-return relationship.FindingsThe results show a positive equity premium on the value-weighted portfolio; however, the equal-weighted portfolio of these stocks shows an average return lower than the return on the 91-day Treasury Bills. The inverted size premium mainly causes this anomaly in the Indian equity market as the small stocks have lower returns than big stocks. The study presents a strong negative risk-return relationship across different risk proxies. However, under the subsample of more liquid stocks, the low-risk anomaly regarding other risk proxies becomes moderate except the beta-anomaly. This anomalous relationship seems to be caused by small and less liquid stocks having low institutional ownership and higher short-selling constraints.Practical implicationsThe findings have important implications for investors, managers and practitioners. Investors can incorporate the effects of different highlighted anomalies in their investment strategies to fetch higher returns. Managers can also use these findings in their capital budgeting decisions, resource allocations and other diverse range of direct and indirect decisions, particularly in emerging markets such as India. The findings provide insights to practitioners while valuing the firms.Originality/valueThe study is among the earlier attempts to examine the risk-return trade-off in an emerging equity market at both the aggregate equity market level and in the cross-sections of stock returns using alternative measures of risk and expected returns.

Towards a Solution to the Variety in Accounting Practices of Extractive Firms under IFRS

AbstractAccounting for exploration and evaluation (E&E) costs is one of the last major issues to remain largely unregulated by International Financial Reporting Standards (IFRS), even though extractive firms are an important part of several big stock markets. Under a temporary permissive standard (IFRS 6), which has been in place since 2004, firms use a wide range of accounting policies for E&E costs, thus undermining comparability. We review the IFRS annual reports of a large number of firms, looking for different policies. We identify many distinguishable methods of accounting. Along with this, we discover that disclosures are often confusing, partly because of the lack of definitions in IFRS 6. To aid insight into this complexity, we prepare a classification of these methods and give real examples of each. We then assess the methods in the context of IFRS 6 and other relevant parts of IFRS. We find that nearly all the methods comply with IFRS. This leads us to a proposal for narrowing the variety of practice by withdrawing IFRS 6, and putting E&E costs within the scope of IAS 38 Intangible Assets. As part of this, IAS 38 could be further revised to extend the scope of capitalisation of other development costs, thereby addressing one of the criticisms of current reporting practice and bringing IAS 38 more into line with the latest version of the Conceptual Framework.

Towards a Solution to the International Variety in the Accounting Practices of Extractive Firms Under IFRS

Accounting for exploration and evaluation (E&E) costs is one of the last major issues to remain largely unregulated by International Financial Reporting Standards (IFRS), even though extractive firms are an important part of several big stock markets. Under a temporary permissive standard (IFRS 6), which has been in place since 2004, firms use a wide range of accounting policies for E&E costs, thus undermining comparability. We review the IFRS annual reports of a large number of firms, looking for different policies. We identify many distinguishable methods of accounting. Along with this, we discover that disclosures are often confusing, partly because of the lack of definitions in IFRS 6. To aid insight into this complexity, we prepare a classification of these methods and give real examples of each. We then assess the methods in the context of IFRS 6 and other relevant parts of IFRS. We find that nearly all the methods comply with IFRS. This leads us to a proposal for narrowing the variety of practice by withdrawing IFRS 6, and putting E&E costs within the scope of IAS 38 Intangible Assets. As part of this, IAS 38 could be further revised to extend the scope of capitalisation of other development costs, thereby addressing one of the criticisms of current reporting practice and bringing IAS 38 more into line with the latest version of the Conceptual Framework.

Utilización de Simulación de Eventos Discretos para analizar una propuesta de mejora en los costos de almacenamiento

El almacenamiento prolongado en cualquier empresa es un problema, porque aumenta los costos de uso del almacén, además, la mercancía que se almacena por un tiempo prolongado puede resultar dañada, razón por la cual se planea este estudio. Donde se muestra la implementación de un modelo de simulación de eventos discretos para analizar unas posibles mejoras en los costos de almacenamiento en una compañía de tecnología móvil, con el objetivo de proponer mejoras que reduzcan los costos actuales del sistema. Para ello, se seleccionaron los 3 productos con mayor rotación. Se utilizó el software Arena® para modelar el sistema a partir de datos históricos de las demandas y los pedidos realizados en los períodos anteriores. Luego de aplicar el modelo se encontró que una buena estrategia para reducir costos es modificar la cantidad solicitada, más específicamente aumentar la de los productos 1 y 2, y reducir la del producto 3. En los resultados se pudo dar cuenta de que la mayoría de los desabastecimientos en el inventario son de los dos primeros productos. Por tanto, se propusieron diferentes propuestas para cada uno de los productos; Por tanto, se concluye que la propuesta 1 es la más recomendada de utilizar, ya que no es muy invasiva y no afecta la relación de clientes y proveedores

SENTIMENTAL HERDING: THE ROLE OF COVID-19 CRISIS IN THE EGYPTIAN STOCK MARKET

This study aims to investigate the existence of herding behaviour during COVID-19 crisis in the Egyptian stock market by using firm-level data and employing different testing methodologies. The study also investigates the existence of herding behaviour during COVID-19 crisis at the level of portfolios divided based on the size and the value factors. The study used the nonlinear model proposed by Chang, Cheng and Khorana (2000) and the state-space model developed by Hwang and Salmon (2004) to measure herding behaviour. The study found that the nonlinear model proposed by Chang et al. (2000) lead to results indicating evidence of herding during COVID-19 crisis. However, there was no evidence of herding behaviour during COVID-19 crisis when using the state-space model developed by Hwang and Salmon (2004). As for the level of portfolios, the study found evidence of herding during COVID-19 crisis only when using (Chang et al., 2000) methodology, at the level of the portfolio of stocks with low and high (B/M) ratio and the portfolio of big stocks only during COVID-19 crisis.

Fundamental anomalies and the size puzzle in China: A data mining approach

The paper documents the profitable fundamental-based anomalies in China's A-share market and proposes the fundamental-related size puzzle which is converse to prior literature on the US stock market: these anomalies are systematically more pronounced among big stocks than among small stocks. Using the bootstrap approach to control for data mining, the fundamental-related size puzzle strengthens. Further evidence points to the widely perceived view about China's A-share market that for small stocks subject to severe shell-value fluctuations due to IPO constraints, fundamental information is less relevant and hardly incorporated into prices even upon earnings arrival.

COVID-19 crisis as a systematic risk: an empirical study in the egyptian stock market

"This paper examines the ability of beta (β) to measure the systematic risks posed by the COVID-19 crisis and analyzes the impact of the COVID-19 crisis on stock returns for a sample of 50 stocks, grouped on the basis of size and value in the Egyptian Stock Market. CAPM beta of the stock was used to represent the systematic risk stocks, market capitalization was used to construct the large and small stocks portfolios and the book-to-market equity ratio was used to construct high medium and small portfolios. The results showed that systematic risks measured by beta increased after COVID-19 crisis for all sample stocks, the portfolios consisting of stocks with high and medium B/M ratio and the portfolios consisting of small capitalization stocks and big capitalization stocks. However, the COVID-19 crisis has no effect on systematic risks for the portfolio consisting of stocks with low B/M ratio. The results also indicated that stock returns decreased after the COVID-19 crisis for all sample stocks, the portfolios consisting of stocks with low B/M ratio and the portfolios consisting of big stocks. However, the COVID-19 crisis does not affect stock returns for the portfolios consisting of stocks with high and medium B/M ratio and the portfolios consisting of small stocks. "

A DCM-based NIR sensor for selective and sensitive detection of Zn2+ in living cells.

Zinc ion is the 2nd abundant transition metal element in human's body. It is responsible for many physiological and biological functioning in the body, such as growth of people, immunity, endocrine, etc. The deficiency of zinc could result in an increasing risk for growth retardation, neurological disorder and infectious disease. Thus, developing a nondestructive method for detecting Zn2+ in living systems is important. Here we reported a 2-(2-methyl-4H-ylidene)- malononitrile (DCM)-based NIR probe DF-Zn for selective and sensitive detection of Zn2+. The probe DF-Zn is cell-permeable and stable at broad pH range. DF-Zn showed a fast response to Zn2+, big stock's shift, and "nude-eye" recognition for Zn2+. Moreover, the selective binding of probe DF-Zn to Zn2+ was reversible. With the addition of EDTA in buffer solution, reversible response of probe to Zn2+ could be observed in MCF-7 cells imaging.