Stock Market Returns Research Articles

Comparative analysis of small and medium-sized enterprises (SMES) versus large companies during the COVID-19 pandemic: Evidence from Moroccan financial market

The COVID-19 pandemic significantly affected global financial markets, and Morocco proved no exception. This article analyzes the impact of the pandemic-related announcement on the stock market returns of small and medium-sized enterprises (SMEs) and large companies listed on the Casablanca Stock Exchange. Using event study methodology. This research reveals that SMEs suffered more significant and prolonged declines in stock market returns than large companies, which demonstrated greater resilience. The results underline the importance of adopting crisis management strategies tailored to the specific characteristics of companies according to their capitalization. This offers insights for decision-makers, investors and managers seeking to navigate through periods of major economic turbulence.

Research on the Applicability and Extensions of the Fama-French Three-Factor Model Evidence from Tech Market ETF

In this paper, the Nasdaq 100 Index (ETF) is selected as a representative of the technology sector, and the dominant factors affecting the performance of stock returns in the technology market are explored through data processing and regressions of its monthly returns from 2014 to 2023.In this study, the Nasdaq 100 Index (ETF) is used as a proxy for the technology sector. The study investigates the dominant factors affecting the performance of the technology market stock returns. This study adds 10 extended factors to the Fama-French three-factor model,with the aim of finding the variables which strongly impact on NDX returns. Each factor was tested and screened through multiple time series regression, multiple covariance analysis, and stepwise regression. Finally, the Fama-French two-factor extended model with the largest R-squared value and the strongest explanatory power for NDX returns was constructed. Its independent variables include market returns and premiums, SMB, HML, interest rate changes, and industrial production index changes. Compared to the original Fama-French three-factor model (R-squared 0.871), the reconstructed Fama two-factor extended model has a better fitting which has an R-squared of 0.885, which illustrates the effect of the newly added factors on the technology market stock portfolio and provides an empirical evidence on that the new model is an improvement for the technology market stock portfolio.

Exploring the Nexus between Macroeconomic Variables and Stock Market Returns in Nepal: An ARDL Bounds Testing Approach

Background: Investors and policymakers must understand how macroeconomic variables (MEVs) affect stock market behavior to maximize portfolios and maintain economic stability. Hence, it is crucial to establish a nexus between MEVs and stock market returns (SMRs). Objectives: This study seeks to assess the effects of MEV on SMRs in the long and short run. Methods: This paper analyzed the cointegrating relationship between MEVs and SMRs using a time series data set from 1994 to 2023. This study used the ARDL bounds testing approach. Results: The results confirm a cointegrating association between MEVs and SMRs in the Nepalese stock market. The error correction (ECT -1) term is significantly negative, suggesting a persistent correlation between the variables. The study also shows that interest rates negatively affect SMRs over time. Real GDP (LRGDP), inflation (LINFR), and exchange rate (LEXR) have negative but statistically insignificant associations with SMRs. However, the money supply (LMS) positively correlates with SMRs. Conclusion: The study’s findings provide practical advice for policymakers. For instance, lower interest rates increase the appeal of stocks by reducing the opportunity costs of holding bank deposits and credit costs. Therefore, policymakers are advised to maintain lower interest rates to cultivate a more appealing investment environment. Furthermore, policymakers should prioritize regulating inflation and preserving a robust foreign exchange rate to boost investors’ SMRs.

The dynamic connectedness between oil price shocks and emerging market economies stock markets: Evidence from new approaches

This paper uses the dynamic connectedness framework to investigate the interrelationship between the decomposed oil supply, demand and risk shocks that Ready (2018) developed and the stock market returns of emerging market economies. For this purpose, we use daily data from 11 October 2001 to 5 April 2021. Novel empirical methodologies, including wavelet quantile correlation (WQC), cross-quantilogram analysis, nonparametric causality-in-quantile approaches, contemporaneous R2 connectedness approach and generalized R2 connectedness approaches, are employed. The results show that oil price fluctuations significantly impact the economic performance of emerging market economies, reflecting historical events. Demand price shocks are regarded as net transmitters within the system, whereas supply and risk price shocks are net receivers of spillovers. Concurrently, our findings indicate a considerable degree of dynamic connectedness among the stock markets of emerging market economies. In particular, the stock markets of Brazil, Mexico, and Argentina have been identified as net transmitters of spillovers. In contrast, the stock markets of Turkey, South Korea, Malaysia, Indonesia and India are classified as net receivers of spillovers. Furthermore, we examine and document the advantages of diversified portfolios that include all sector indices, including oil price shocks and emerging market economy stock markets, in terms of portfolio performance. The insights offered here are valuable for investors and policymakers striving to enhance their strategic approaches in today's interconnected global financial context. The results show that oil price fluctuations significantly impact the economic performance of emerging market economies and reflect historical events. Demand shocks affecting the stock market indices of Brazil, Argentina and Mexico tend to act as net spillover transmitters. In contrast, supply shocks affecting the stock market indices of Indonesia, South Korea, India, Turkey and Malaysia mainly act as net spillover receivers. Net pairwise interconnectedness analysis reveals that, except for crisis periods, interactions between financial markets or macroeconomic indicators are evenly distributed. Thus, systemic risk is lower, and markets act independently. Empirical findings obtained using WQC generally show the presence of negative correlations at long-time scales and low quantiles, which is considered an indicator of the safe-haven feature associated with the asset in question. The hedge feature is observed to be evident only at long time scales. The results of the cross-quantilogram analysis show mixed evidence of correlation in all stock indices, especially in the weekly lag structure, compared to daily and monthly lags. Finally, non-parametric Granger causality test results show that stock returns are insensitive to oil price fluctuations, making these markets attractive for investors seeking diversification strategies. These findings provide valuable recommendations for investors seeking sustainable equities in a volatile oil market.

Advancing Stock Market Return Forecasting with LSTM Models and Financial Indicators

Advancing Stock Market Return Forecasting with LSTM Models and Financial Indicators

Comparative Analysis of Risk Premium and Stock Market Returns in Indonesia: A Case Study of Normal and COVID-19 Pandemic Periods

This research examines the effect of market risk premium (risk premium) on market returns (JCI). In addition, this study aims to see the effect of premium risk on market returns during the COVID-19 Pandemic. The data used in this study is secondary (JCI data and Deposit Interest Rates) for the period January 2010 – September 2023. The method used in this study is the GARCH method (1.1). The results of this study show a positive and significant influence of risk premium on market returns (JCI). During the COVID-19 Pandemic, risk premiums negatively and significantly affected JCI returns or the Indonesian stock market.

Multiple Behavioral Conditions of the Forward Exchange Rates and Stock Market Return in the South Asian Stock Markets During COVID-19: A Novel MT-QARDL Approach

This study examines the short- and long-term effects of multiple quantiles of forward exchange rate premiums (FERPs) and COVID-19 cases on the quantiles of stock market returns (SMRs). We extend the Quantile Autoregressive Distributive Lag (QARDL) model, and the Multiple Threshold Non-linear Autoregressive Distributive Lag (NARDL) model propose a new Multiple Threshold Quantile Autoregressive Distributive Lag (MT-QARDL) approach. Unlike MT-NARDL, QARDL, and NARDL, the MT-QARDL model, which integrates the MT-NARDL model and the quantile regression methodology, captures both short- and long-term locational and sign-based asymmetries. For instance, at lower quantiles for Indian and Sri Lankan SMRs, bearish FERP exerts a positive influence, while bullish FERP has a negative effect during COVID-19. Conversely, bullish FERP negatively affects lower quantiles of SMRs of Bangladesh, India, and Sri Lanka, whereas bearish FERP either yields an opposite effect or remain statistically insignificant during COVID-19. The findings underscore long-term sign-based asymmetries due to the differential bearish and bullish FERP impact during COVID-19. However, in the long term, location-based asymmetries also existed as bullish FERP negative influence the SMRs of India, Bangladesh and Sri Lanka at higher quantiles but SMRs at lower quantiles insignificantly respond to the bullish FERP fluctuations during COVID-19.

Predicting Nigerian Stock Market Returns Based on Daily Business News Headlines

This study predicts daily returns of the Nigerian Stock Exchange (NSE) using Nigerian daily news headline. The Vanguard newspaper is used as the source of information, to collate 11 years (2February 2, 2012 to September 29, 2023) of daily news headlines and data on the daily returns All-Shares Index (ASI) of the Nigerian Stock Exchange NSE was collared from the website https://ng.investing.com/indices/nse-all-share-historical-data. Text mining techniques such as Term Frequency-Inverse Document Frequency (TF-IDF) are applied to pre-determine important words and sentences and their influences on daily market returns. N-gram sentences are used to build bigrams and trigrams, which helps us determine their positive and negative returns. The result shows that when words such arabia, crypto, renewal, paris, and tradermoni appear in news headlines, there is negative returns in the stock market, but when words such as lawmakers, multinationals, ebonyi, constraints and double appear in the news headline, there is positive return. For bi-gram sentences when sentences such as price dip, earning rise, tax compliance, and econbank partners appear, there is often negative return, on the other hand when sentences such as trustfunds pensions, inter agency, business insurance, index rise and forex supply appear in the news headline, there is often positive return. And for tri-gram sentences, when sentences such as profit taking NSE, government private sector, cross boarder trade, cargo tracking note, and capital market sec, there is often negative return in NSE, on the other hand, when sentence such as poor purchasing power, naira watch cbn, mtn google empower, google empower smes and external reserve hit appear in the news headlines, there is often a positive returns in the stock market. Three machine-learning models were used to build the predictive models. The models were logistic regression with a prediction accuracy of 0.52, Support Vector Machine (SVM) with an accuracy of 0.51, and K-nearest Neighbour (KNN) with an accuracy of 0.99, indicating higher prediction evidence of news headlines by the KNN model for the NSE index over the alternative models. We limited fitting the models using only unigrams and left fitting models using bigrams and trigram sentences for future research.

Climate investments, stock markets, and the open economy

Abstract We analyze the effect of green patents on G7 stock market returns. First, we build a small IS-LM model to identify the relevant channels, augmented with open-economy channels and the Green Tobin’s q (Faria et al., 2022). The model highlights that the intertemporal impacts of greening on stock returns are ambiguous. We then turn to an estimated global vector autoregressive model to more rigorously analyze the effect of monetary and green patenting shocks across the G7. Both shocks influence green patents through real and financial markets. As regards green patent shocks, results suggest that a tension exists over time between promoting pollution reduction and energy efficiency and the profitability of (green and brown) companies in the aggregate. We perform a variety of robustness exercises around our main results. Our results provide something of a challenge to the literature and call for more research effort to understand the various channels that might explain this dynamic—and in turn whether any particular policy recommendations follow.

Abnormal Stock Market Returns to Business Model Extension Announcements: Value Drivers & Moderators

The value-creation potential of business model extensions (BME) in incumbent companies remains a subject of ongoing debate and is currently not substantiated by market-value focused empirical research. Especially the moderating role of economic uncertainty and the interplay with traditional product-industry diversification have not been empirically examined. This study aims to close that gap. We utilize an event study setup to measure the value-creating effect of BME and its moderators. Using a unique dataset of joint ventures in the high-tech industry industry, we measure the effects of BME and its moderators on abnormal stock market returns. Our findings indicate that BME leads to higher abnormal stock market returns. This effect is further amplified under company-level, industry-level, and macroeconomic uncertainty. Additionally, we discover that, under these uncertainties, combinations of BME and product-industry diversification are value-creating, whereas product-industry diversification alone tends to be value-destroying.

The cost of political instability in Greece

ABSTRACT This paper examines the relationship between political instability, economic growth, and Greece's overall stock market index (ASE) returns from 1970 to 2018. The aim is to measure and quantify the impact of political instability on economic growth and the overall stock market returns. The analysis includes six different variables as proxies that quantify political instability. A new Socio-Political Instability index is constructed from these variables by employing the principal component analysis. The empirical part employs GARCH, GARCH-M, Granger causality tests and OLS regressions. The paper provides new insightful results and a new measure of political instability for Greece.

Dynamic Linkages Between U.S and Indian Equity Markets: An Empirical Study

In this study, we investigate the dynamic linkages between US and Indian equity markets by examining the daily Total Return Index values of NIFTY 50 and NASDAQ Composite over a decade ending October 2024. While the indices are not found to be cointegrated, suggesting potential long-term diversification benefits, they exhibit significant short-term correlations. Through various statistical analyses including regression, correlation, and variance tests, we find strong positive associations between the markets, with NASDAQ Composite movements explaining approximately 89% of variations in NIFTY 50 Total Return Index (TRI). The study reveals distinct volatility patterns, with the Indian market showing higher price fluctuations but stronger absolute growth compared to its US counterpart. Despite the strong correlation, both markets maintain unique characteristics influenced by their respective economic fundamentals. The findings demonstrate the evolving nature of market integration between developed and emerging economies, offering valuable insights for international portfolio diversification strategies and risk management in an increasingly interconnected global financial system. Keywords: Market Integration, Volatility Spillover, Portfolio Diversification, Stock Market Returns, Emerging Markets, Cross-market Correlation

Fear, extreme fear and U.S. stock market returns

This paper investigates the multiscale co-movement between the levels and changes in VIX and SKEW indices and the returns of the S&P 500 market indices at the aggregate and sector levels of data. By utilizing the wavelet localized multiple correlation (WLMC) method over the most recent time period (January 3, 2006 - October 26, 2023), we demonstrate that very short-term market participants, such as traders and speculators, are watchful about the combined information from the VIX and SKEW levels; while the changes in VIX and SKEW are more informative for stock returns in the medium- to long-term, which should concern the decisions of investors and portfolio managers. We also show that VIX in general exerts a more dominant influence on the S&P 500 Index returns than SKEW, but more for VIX changes than for VIX levels. The very short-run informativeness of VIX and SKEW for stock returns is markedly pronounced around the European debt crisis (2012) and the COVID-19 meltdown (2020). The stock sector analysis reveals that defensive sectors are sensitive to the SKEW index, whereas the cyclical sectors are predominantly related to the fluctuations in the VIX index. Overall, our findings provide useful new insights into the stock market sentiment and the resulting market participants’ behavior at the market microstructure level. As such, they may be of interest not only to traders and investors, but also to financial analysts and government policy-makers in their attempts to understand the multiscale relationship between monetary policy and the stock market.

Causality relationships between climate policy uncertainty, renewable energy stocks, and oil prices: a mixed-frequency causality analysis

This paper investigates the predictive relationships among climate policy uncertainty (CPU), oil prices, and renewable energy (RE) stock market returns, particularly highlighting the challenges posed by the varying data frequencies of these variables. The study utilizes a comprehensive dataset comprising monthly CPU, daily oil prices, and RE stock returns, sourced globally. By applying a mixed-frequency causality test (MFCT), the analysis reveals significant predictability across different time horizons, particularly highlighting the strong influence of oil prices on RE stock returns over short-term horizons, while CPU demonstrates a more pronounced effect over medium to long-term horizons. In contrast, the application of the classical Granger causality test on low-frequency (monthly) data indicates an insignificant relationship between CPU and RE stocks, suggesting that traditional models may overlook important predictive dynamics. The analysis was conducted using Matlab code, and the findings provide valuable insights for policymakers in designing effective climate policies and for investors in optimizing portfolio strategies and hedging against risks.

Impact of Inflation Stock Market Returns

This research paper examines the impact of inflation on stock market returns, focusing on the Indian stock market. Utilizing a comprehensive methodological approach, we analyse the relationship between inflation and stock market performance through various quantitative techniques including trend analysis, regression analysis, histograms, growth percentage models, and descriptive statistics. The trend analysis reveals patterns and shifts in stock market returns in response to changing inflation rates. Regression analysis is employed to quantify the strength and nature of the relationship between inflation and stock market returns, providing insights into the degree to which inflationary pressures affect market performance. The findings of this study indicate a multifaceted relationship between inflation and stock market returns. While high inflation periods generally correlate with increased market volatility and lower returns, the impact varies across different sectors and economic conditions. Our analysis also includes the significance of monetary and fiscal policies in moderating the effects of inflation on the stock market. This research contributes valuable insights for investors, policymakers, and financial analysts, by having a detailed analysis of Inflation-Stock market study. The study's results can inform investment strategies and policy decisions aimed at mitigating the adverse effects of inflation on stock market performance and enhancing market resilience. The purpose of the study is to investigate he correlation, understand the investor behaviour and recommend the insights from the study.

The silicon valley bank collapse, deposit insurance concentration, and stock market returns

The silicon valley bank collapse, deposit insurance concentration, and stock market returns

Monetary Policy Instruments and Stock Market Returns Volatility in Nigeria

The study examines monetary policies instruments impact on stock market volatility in Nigeria for the period of 1993-2022. The study identified the independent variables, namely; reserve requirement (RR), cash reserve ratio (CRR), discount rate (DR) and money supply (MS) which were analyzed in relation to stock market volatility proxied with all share index volatility (ASIV). The data was analyzed with descriptive statistics, correlation matrix several diagnostics tests (VIF, validity test, ADF and Johansen tests) and the multiple regression analysis. The findings revealed that RR, CRR and MS have significant effect on ASIV while DR has insignificant effect on ASIV in Nigeria. It was concluded that reserve requirement, discount rate and money supply exert significant effect on Nigerian economy. Thus, it thereby recommended that management of CBN should put modalities in place to aggressively control ASIV in Nigeria. CBN should put measures in place to increase CRR. This will provide banks opportunity to fund economic transaction in the Nigerian economy, thereby reducing ASIV.

Industry return volatility and spillover effects in stock market under climate risk perception

ABSTRACT Utilizing alternative dimension reduction methods, this study constructs three Climate Risk Perception Indices (CRPIs) to quantify the impact of investor climate change sentiment on industry return volatility in the Chinese stock market. There are several findings in this study including (1) the CRPIs effectively capture the trend of climate change in China over the past decade. (2) The investor’s attention to climate change positively influences short-term stock market returns, exhibiting seasonal characteristics and industry heterogeneity. (3) The attention serves as an information sender for stocks in Telecommunication, Oil & Petrochemicals, and Environmental Protection. (4) The total spillover effect among climate-sensitive industries is significantly higher during extreme climate events. These conclusions provide empirical evidence for the stock market to respond effectively to climate risks.

Asymmetric impact of the COVID-19 on the Moroccan stock exchange

PurposeThis study aims to investigate the asymmetric impact of the COVID-19 pandemic on the stock market returns of companies listed on the Casablanca Stock Exchange.Design/methodology/approachTo achieve this objective, we utilized the SymCovid series, which comprises two sub-series: one representing the deterioration of the pandemic situation (NEG) and the other representing the improvement of the pandemic situation (POS). We employed the Nonlinear Autoregressive Distributed Lag model, incorporating Bounds Testing as proposed by Pesaran and Shin (1999) and Pesaran et al. (2001), to explore the asymmetry of the pandemic’s impact on stock prices listed on the Casablanca stock exchange.FindingsOur analysis using the NARDL econometric model reveals an asymmetric effect of COVID-19 on stock prices. Notably, we observe that stock prices react more strongly to a worsening pandemic situation than to an improvement, on average. Furthermore, our main findings indicate that while the improvement in the pandemic situation has no significant long-term impact on stock prices, it does exhibit a significant positive effect in the short term. Conversely, the deterioration in the pandemic situation has a more pronounced negative effect on stock prices in the long term than the short term.Originality/valueOur study fills a gap in the existing literature by focusing on the impact of the COVID-19 pandemic on stock returns in the context of the Casablanca Stock Exchange, which has been relatively understudied compared to other regions such as Asia, Europe and the Americas. We go beyond previous research by examining whether stock returns exhibit asymmetric responses to changes in the pandemic situation, highlighting potentially unique dynamics in emerging market economies during crises and providing valuable information for investors, policymakers and researchers.

The Impact of COVID19 Spread on the Listed Egyptian Banks Stock Market Returns

The Impact of COVID19 Spread on the Listed Egyptian Banks Stock Market Returns