US Stock Market Research Articles

Moderating effect of gross domestic production on the association between share ownership of CEO and strategic risk-taking of airlines

Purpose: The purpose of this research is to examine the moderating effect of gross domestic product on the relation-ship between share ownership and strategic risk-taking of airlines. Theoretical foundation of this work is upper echelon theory and contingency theory. Design/methodology/approach: The sample of this work is publicly traded airlines in the US stock market: NASDAQ, AMEX, and NYSE. For data collection, this work employed Annual 10-K, Bureau of economic analysis, Compustat, and Execucomp using SIC code 4512. 15 airlines were used and the study period is 1999-2019. For testing the research hypotheses, this study implemented multiple linear regression analysis. Findings: The results indicated that gross domestic product positively moderates the relationship between share ownership of CEO and strategic risk-taking of airlines. Research limitations/implications: The practical implication of this work is for the information provision of share-holders and potential investors for airline stocks. Originality/value: This research is worthy by elucidating the moderating effect of gross domestic product regarding top managers' decision making domain.

On the linkage of momentum and reversal – evidence from the G7 stock markets

This paper studies the linkage of momentum and reversal in the G7 stock markets. We confirm Conrad and Yavuz’s (Rev Financ 21(2):555–581, 2017) finding that momentum is not linked to subsequent return reversal in the US stock market. In the stock markets of the remaining G7 countries, our results object the decoupling of momentum and return reversal. In these stock markets, the two return anomalies are linked to each other. In particular, momentum is followed by return reversal in the stock markets of Germany, the UK, Japan, Canada, France, and Italy. These observations obtain for momentum portfolios which are made up of different risk profiles with respect to size and book-to-market ratio. Our results hold true both in raw returns and in risk-adjusted returns.

Russia-Ukraine War The Impact of Energy Market Fluctuation on the US Stock Market

Russia-Ukraine War The Impact of Energy Market Fluctuation on the US Stock Market

Investing in US Timberland Companies

Are common stocks issued by timberland companies a good investment? Portfolios of large US timberland corporations are compared to simultaneous investments in a diversified US common stock index. Over a 20-year sample period it turns out that the US timberland corporations, on average, perform about as well as the highly diversified US stock market index. It is surprising that the timberland companies do not outperform the stock market indexes because, in order to encourage tree planting, the US Congress has almost completely exempted timberland companies from paying federal income taxes. Furthermore, it is scientifically impossible to assess the value of the large amounts of photosynthesis that the timberland companies produce. As a result of these two ambiguities, it is difficult to state decisively that the timberland companies are better investments than a diversified portfolio of common stocks. However, valuing timberland companies is more practical than endeavoring to value the trees directly.

A crisis like no other? Financial market analogies of the COVID-19-cum-Ukraine war crisis

In this paper, we examine the dynamic behaviour of the US stock market due to the subsequent impact of the COVID-19 outbreak and the war in Ukraine. To that end, we analyse daily data of Dow Jones Industrial Average returns from 2 January 1900 to 31 October 2022. Firstly, we identify past crisis episodes similar to the current situation. Then, we compare the volatility dynamics, variation-fluctuation correlation functions, and correlation with uncertainty indicators with those induced by the COVID-19 epidemic and the subsequent Russo-Ukrainian conflict. Our findings suggest that the consecutive occurrence of these unexpected events has had more severe adverse effects on the US stock market than those recorded in similar past episodes. Additionally, we found that the events are highly correlated with indicators of economic policy uncertainty and financial market fear.

A Comparative Study of CAPM Based on the US Stock Market

The capital asset pricing model (CAPM) is a highly useful and relatively simple equation used in this study for calculating the volatilities, also known as beta, of different stocks in four different industries in the S&P 500 Index and a 1-year T-Bill. The beta values of the stocks in each industry were added together to find the total beta for each industry. An overall decreasing trend in industry beta values near the end of the 2022 can be seen for banking and media & entertainment, while transportation increased a little and retail remained relatively constant, with transportation having beta values closest to one. Changes in industries with beta values near one will better reflect the overall market, as the markets beta is assumed to be one. The purpose of this research is to compare the risks and sensitivities of these four industries after the COVID pandemic, and the results show that as the pandemic subsides, beta values have begun to shift closer towards one.

Examining the Adaptation of the Fama-French Three-Factor and Five-Factor Models in the US Market

The adaptability of the Fama-French three-factor and five-factor models in distinct markets is currently a key research topic. Some researchers are investigating whether the FF3FM and FF5FM are reasonable frameworks for explaining excess returns in stock markets by testing them with data from different markets. This paper mainly explores the adaptability of FF3FM and FF5FM in the US stock market, and adds CAPM to the comparison. This article uses the daily factors’ data and the daily average value weighted returns in 6 portfolios formed on size and book-to-market in the Kenneth French database website to construct a linear regression model to study the explanatory power of FF3FM and FF5FM in the US stock market. In order to determine whether these factors are parts of an effective asset pricing model, this paper assesses the efficacy, robustness, and reliability of factors in explaining asset returns using the Durbin-Watson test, the correlation matrix, and the sub-period analysis, which also confirm whether these factors have statistical significance, economic significance, and stability. It is found that the explanatory power of FF5FM is stronger than that of FF3FM in the US stock market. While both profitability and investment factors have relatively modest explanatory power, size and value factors offer significant explanatory power for stock returns.

The S&P 500 sectoral indices responses to economic news sentiment

AbstractThis study explores the dynamic relationship between economic news sentiment and the US stock market using a non‐linear empirical framework. The analysis focuses on both sectoral indices and the aggregate stock market index from November 2011 to November 2021. Using causality tests and a rolling window detrended cross‐correlation coefficient, the study reveals several key findings. First, the causal effect of investor sentiment on sectoral returns varies over time, with each sector responding differently. Second, while no evidence of dependence exists for time scales less than 2 months, a positive relationship emerges for time scales greater than 6 months, except for the utilities sector, which is found to be negative. Third, the study shows that the relationships between all pairs of variables are time‐dependent. Finally, economic news sentiment might have a varying impact on market inefficiency over different periods, making it challenging to predict market behaviour based on sentiment data.

Financial Integration of the European, North America, Asiatic and Japanese stock markets from 2003 to present times

We apply an integration/segmentation analysis between the European (EU) market and the North America stock market (US and Canada), the Asian Stock Market (AS) and the Japanese (JP) market. The analysis is carried out from 2003 until the present time. We apply the Jorion and Schwartz (1986) methodology and extend the work of Brooks et al. (2009) using a simpler Capital Asset Price Model (CAPM) and the Market return downloaded from the Fama French website for the time period analysed. Our results in this empirical study show integration between the European portfolios and the US stock market and the Asian Portfolios and the US stock market in the full time period analysed. Although the methods applied in this paper have been already introduced in the literature, this is the first time that they are applied systematically to compare the integration and segmentation between different economies and a given portfolio set. This systematic approach helps to establish the conclusiveness of their forecasts.

Stock market prices and Dividends in the US: Bubbles or Long-run equilibria relationships?

This paper presents a novel approach to identifying potential bubbles in the US stock market by employing alternative time series methods based on long memory, including fractional integration and cointegration, as well as duration dependence non-parametric models. To test for duration dependence, the paper employs a unique non-parametric hazard function estimation method, using monotonic P-splines, which enables the estimation of a coherent and sophisticated Bayesian confidence interval for the function. By analyzing historical data of real US stock index from January 1871 to November 2022, the results reveal strong evidence of bubbles in the US stock market. It is worth noting that this is the first time a fractional integration approach and a novel non-parametric hazard function have been utilized to test for rational speculative bubbles in the US stock market, making this paper a significant contribution to the field.

Tail risk transmission from the United States to emerging stock Markets: Empirical evidence from multivariate quantile analysis

This paper explores the transmission of risk from the United States equity market to the equity markets of the BRICS countries using a multivariate quantile process. The focus is on the contagion effect at the extreme quantiles, both upside and downside. In addition, a pseudo-impulse-response function (PIRF) analysis is conducted to investigate the responses of the five emerging stock markets to a shock in the US market. We conduct an empirical study against the backdrop of the COVID-19 event and the Russia-Ukraine conflict, finding that risk spillovers between the US stock market and the five emerging stock markets are significantly enhanced during the COVID-19 period. Moreover, a shock in the US market produces a stronger and more persistent negative effect at the downside quantiles compared to upside quantiles. However, we find little evidence of cross-market risk spillovers among the investigated variables during the Russia-Ukraine conflict period. We also discuss the implications of these findings for investors and policymakers in terms of portfolio holdings and policy coordination.

Algorithmic Trading Strategies: Leveraging Machine Learning Models for Enhanced Performance in the US Stock Market

Algorithmic Trading Strategies: Leveraging Machine Learning Models for Enhanced Performance in the US Stock Market

Measuring the risk and return of Indonesia's and United States Stock Index

This research investigates the relationship between the returns of selected Indonesian and US stock market indexes and their risks so as to guide new investors on how to choose their investments wisely. A quantitative descriptive method was used using performance data from three Indonesian and three US stock indexes over ten years to calculate an average return. The Sharpe Index was used to measure each index's risk. The results show that the average stock return for each index in the US is higher than the Indonesia indexes, while the level of risk in the US, on average, is lower. Investors are advised to invest in index categories with higher returns and low risk to increase the chance of gaining better returns while managing their risk to be as low as possible.

The tail risk safe haven property of China's energy futures against US market implied volatility

This paper analyses the tail risk contagion of US market implied volatility (USIV) on China's energy futures (CEF) markets, exploring how to utilize operations in the CEF to achieve a safe haven. Leveraging CEF characteristics to simultaneously take both long-/short-positions and engage in long-/short-run investment horizons, this paper defines eight different CEF safe haven attributes to counteract the tail risk of extreme increases in USIV. Using trading data from March 27, 2018, to October 30, 2023, the empirical results show that, first, in the analysis of the entire sample period, China's coking coal futures can serve as a weak safe haven, aiding long-position investors in mitigating the tail risks associated with US gold and stock market implied volatility. Coking coal futures also assist short-position investors in countering US stock market implied volatility tail risk. Second, in the sub-period analysis, the safe haven attributes of CEF exhibit strong heterogeneity and asymmetry across different periods. Finally, the time span during which CEF exhibits a particular safe haven attribute does not persist for an extended period.

Tug of war with noise traders? Evidence from the G7 stock markets

This paper studies the tug of war between overnight noise trading and daytime arbitrage in the G7 stock markets. We confirm Akbas, Boehmer, Jiang, and Koch (2022) reporting that this tug of war predicts future returns in the US stock market. We verify this result also in the Canadian stock market. In contrast, for the stock markets of France, Germany, Italy, the UK, and Japan, this tug of war is not predictive for future returns. These country-wise findings are documented in average raw returns and prevail upon risk adjustment along both Carhart (1997) four factors and Fama and French (2018) six factors. A microstructure perspective on the tug of war suggests that the split evidence between the US and Canadian stock markets and the remaining G7 stock markets is due to institutional and regulatory differences which restrict daytime institutional arbitrage in the European stock markets and Japan.

ANALYZING THE IMPACT OF FIRM-SPECIFIC FACTORS ON SUSTAINABILITY PRACTICES: UNRAVELING THE MODERATING EFFECT OF LIQUIDITY

This study aims to investigate the relationships between characteristics of firm-specific & the implementation of sustainable corporate practices, and exploring the moderating effect of liquidity to acknowledge the essential role of financial flow in shaping the sustainable approach of businesses in United States. In the proposed study secondary data of 10 listed chemical industries in US stock market has been gathered over a ten-year period of time from 2013-2022. Data is collected from annual reports, sustainability reports and CSR report of chemical industries. Firm specifics are measured with firm age and return on asset (ROA), corporate governance with CEO duality and board size whereas, sustainable practice have been examined by social and community expenses. The results provides the significant and valuable information in reaching the conclusion and making the suitable decisions. The study’s finding indicates that there is significant impact of ROA, CEO duality and board size upon the sustainable business practices. However, firm age has negative significant effect on both firm specifics and sustainability. Similarly, the results offered certain valuable clues for future researchers.

The differential impact of distracted auditors in managing portfolio of financially distressed audit clients on audit quality: the role of professional skepticism

This study hypothesizes that distracted auditors affect audit quality. As a result of resources scarcity, auditors pay more attention to financially distressed audit clients rather than non-financially distressed audit clients at the same audit client portfolio which eventually leads to differences in audit quality. In this context, earnings restatement of audit clients is used as a distraction event of auditors. Distracted auditor is measured by the percentage of the audit fees of financially distressed audit clients to total audit fees and audit quality is proxied by total accruals. The data is obtained from firms listed on the US stock market over eleven years between 2010 and 2020. The results indicate that financially distressed audit clients of distracted auditors receive higher audit quality than non-financially distressed audit clients of the same audit client portfolio. Further analysis suggests that this difference in audit quality between financially distressed audit clients and non-financially distressed audit clients decreases with skeptical auditors. This study introduces a new comprehensive approach to measure professional skepticism using KAMs disclosure. The results are robust to different measurements of distracted auditors, audit quality and professional skepticism. Overall, the empirical analyses suggest that distracted auditors have a decreasing differential impact on audit quality by professional skepticism.

ChatGPT and the banking business: Insights from the US stock market on potential implications for banks

Technological advances in artificial intelligence, such as ChatGPT, promise significant potential for automation in the banking sector, but might also be associated with uncertainties and potential disadvantages for banks. By empirically analyzing US stock market reactions to ChatGPT’s launch, this study extracts the expectations of market participants to gauge potential future implications of ChatGPT for banks. The results indicate a significant negative stock market reaction of US bank stocks, with notable disparities between different bank types. Using cross-sectional regressions, we find that the negative market reaction is more pronounced for deposit-dependent and large banks.

BOOK REVIEW:The Ownership Dividend: The Coming Paradigm Shift in the US Stock Marketby Daniel Peris

BOOK REVIEW:<i>The Ownership Dividend: The Coming Paradigm Shift in the US Stock Market</i>by Daniel Peris

Long-Run Linkages Between us Stock Prices and Cryptocurrencies: A Fractional Cointegration Analysis

AbstractThis paper applies fractional integration and cointegration methods to examine respectively the univariate properties of the four main cryptocurrencies in terms of market capitalization (BTC, ETH, USDT, BNB) and of four US stock market indices (S&amp;P500, NASDAQ, Dow Jones and MSCI for emerging markets) as well as the possible existence of long-run linkages between them. Daily data from 9 November 2017 to 28 June 2022 are used for the analysis. The results provide evidence of market efficiency in the case of the cryptocurrencies but not of the stock market indices considered. The results also indicate that in most cases there are no long-run equilibrium relationships linking the assets in question, which implies that cryptocurrencies can be a useful tool for investors to diversify and hedge when required in the case of the US markets.