US Markets Research Articles

A Fundamental and Technical Analysis of the US and Chinese Stock Markets

This paper provides a comprehensive comparison between the stock markets of the United States and China, the two largest economies globally. The study examines key aspects such as market mechanisms, investor strategies, and market efficiencies. The U.S. stock market, characterized by its large market capitalization and robust growth, operates through dealer and auction market mechanisms with a strong regulatory framework and high openness to foreign investors. In contrast, the Chinese stock market, having developed more recently, primarily uses auction market mechanisms and imposes daily price limits to manage volatility. Historical developments show the U.S. market's long history of financial development and crisis management, while China's market has seen rapid development since economic reforms began in 1978. The analysis of market efficiency through fundamental and technical analysis reveals that the U.S. market more effectively reflects company performance in stock prices compared to the Chinese market, which still shows areas for potential improvement. This comparison highlights the distinct characteristics and developmental paths of the U.S. and Chinese stock markets, providing valuable insights for investors and policymakers in understanding the differences and guiding future market development and investment strategies.

Strategies for selecting trading partners based on economic complexity of international trade networks: A comparison between Chinese and the US markets

Selecting suitable trading partners in the globalized trade landscape remains critical. Traditional selection processes driven by factors like comparative advantage and trade costs are cumbersome and incomplete. Economic complexity offers a more precise measure of a country’s economic development and product capacity, facilitating future-oriented choices. Leveraging international trade data from 2001 to 2015, this paper employs economic complexity theories to analyze Chinese and the US’ trade networks in the global market. It explores multi-level considerations for exporting countries’ partner selection, revealing varying product diversification challenges and market clustering tendencies. China shows increasing overall product proximity relationships, specifically notable in textile-related products, while the US exhibits decreasing product proximities. Additionally, trading positions and product dependencies vary across markets. Some countries, like Japan and Germany, maintain stable positions, while others fluctuate. Notably, countries like Nigeria, Bangladesh, and Cambodia have higher positions in the Chinese market, suggesting promising long-term trade partnerships. Conversely, countries like Yemen, Kazakhstan, Kuwait, and Sudan have higher positions in the US market, indicating significant disparities. Products that are needed in the Chinese market and occupy higher complexity positions are primarily concentrated in the field of non-ferrous metals, while the US market relies more on raw materials. This highlights distinct market dynamics, particularly pronounced in the US market. Hence, there is a greater likelihood of obtaining better economic benefits by trading these products in their respective markets.

HPR27 Optimizing Drug Market Exclusivity in the US and EU Markets

HPR27 Optimizing Drug Market Exclusivity in the US and EU Markets

HPR106 Pricing of New Oncology Products in the US and Key European Markets

HPR106 Pricing of New Oncology Products in the US and Key European Markets

Flattening the Curve and the Flight of the Rich: Pandemic-Induced Shifts in US and European Housing Markets

Flattening the Curve and the Flight of the Rich: Pandemic-Induced Shifts in US and European Housing Markets

MT31 The Promising Future of Digital Health: A Road to Reimbursement in US & EU5 Markets?

MT31 The Promising Future of Digital Health: A Road to Reimbursement in US & EU5 Markets?

Looking into the Market Behaviors through the Lens of Correlations and Eigenvalues: An Investigation on the Chinese and US Markets Using RMT.

This research systematically analyzes the behaviors of correlations among stock prices and the eigenvalues for correlation matrices by utilizing random matrix theory (RMT) for Chinese and US stock markets. Results suggest that most eigenvalues of both markets fall within the predicted distribution intervals by RMT, whereas some larger eigenvalues fall beyond the noises and carry market information. The largest eigenvalue represents the market and is a good indicator for averaged correlations. Further, the average largest eigenvalue shows similar movement with the index for both markets. The analysis demonstrates the fraction of eigenvalues falling beyond the predicted interval, pinpointing major market switching points. It has identified that the average of eigenvector components corresponds to the largest eigenvalue switch with the market itself. The investigation on the second largest eigenvalue and its eigenvector suggests that the Chinese market is dominated by four industries whereas the US market contains three leading industries. The study later investigates how it changes before and after a market crash, revealing that the two markets behave differently, and a major market structure change is observed in the Chinese market but not in the US market. The results shed new light on mining hidden information from stock market data.

Exploring the Transmission of Market Volatility between the US and Mainland China Stock Markets

This study investigates the transmission of market volatility between the United States and Mainland China stock markets, particularly in the context of extreme events like the 2007 subprime mortgage crisis and the 2020 COVID-19 pandemic. It underscores the increasing interdependence between these markets and the role of government intervention and regulation in shaping their development. This research offers valuable insights for stakeholders, including regulators, policymakers, and investors, as they navigate the complex landscape of systemic financial risks arising from the interconnectedness of these two major financial markets.

From Shanghai to Wall Street: The Influence of Chinese News Sentiment on US Stocks

This study explores the influence of Chinese news sentiment on US stocks, focusing on the potential policy shift granting Chinese retail traders direct access to US markets. Analyzing the flow of information between Chinese news sentiment and global news sentiment using transfer entropy, the findings reveal a significant influence of Chinese news sentiment on global news sentiment. Moreover, the study identifies a predominant unidirectional flow of information from news sentiment to stock returns, with Chinese news sentiment having a more substantial impact on future returns of US stocks compared to global news sentiment. This suggests that if the proposed policy changes succeed, Chinese retail traders may rely on Chinese news sentiment, potentially leading to increased volatility in the US market. Policymakers and market participants should be aware of these implications to prepare for changes in the US stock market dynamics. Further research can provide deeper insights into the interplay between news sentiment, investor behavior, and market volatility.

US and European Stock Markets in Response to Exogenous Shocks: Cross-Regional Analysis of Dynamic Networks During the COVID-19 Pandemic

This study aims to analyse the impact of force majeure events or exogenous shocks, characterized by a high level of uncertainty, on the US and European stock market behaviour through cross-regional and inter-industrial comparisons. Based on the sample of 832 largest stock-listed companies publicly traded in both regions, the authors investigate whether specific regional and industrial differences in the stock market reaction to exogenous shocks—as exemplified by the ongoing COVID-19 pandemic—and their recovery paths to be determined. The novelty of the research conducted by the authors is underpinned by the application of a dynamic network analysis method—supported by the exponential random graph modelling—for a data sample of publicly traded companies, encompassing major players and industrial leaders in both regions. Furthermore, the methods are applied quarterly for an identical set of industries in cross-market comparison, within a time span of periods before, during and beyond the exogenous shock. The results reveal significant differences in the reaction of US and European stock markets to exogenous shocks, despite globally integrated financial markets. The connectivity of the largest listed companies on the US market is higher than the European ones. Thus, publicly traded companies in the United States are more likely to be closely connected to their industry peers. As demonstrated by a cross-market comparison of the European and US stock market network configuration, the US network reveals higher probabilities of intra-industrial connections of its market participants. In contrast, the European stock market exhibits fewer connections and a less dense network of market participants in times of uncertainty or exogenous shocks. Except for the European financial industry, which behaves similarly to its US counterpart, the overall interconnectedness of European companies is weaker within the uncertainty-related timespan. The latest could be partially explained by numerous national regulations being implemented at a country level, which are partly deviating from the EU single-market policies. In contrast to a relatively homogeneous setting of the US market, a low level of interconnectedness of publicly traded companies in Europe could be further argued by the application of non-harmonized industrial policies, with the latest being expanded during the ongoing crisis in selected European locations. This difference could also be explained by the absence of a mutual strategy for alleviating the effects of the COVID-19 pandemic in Europe. The obtained results could be valuable for academics, conducting similar thematic research; for portfolio investors, and policymakers in forecasting, reacting and assessing stock market behaviour overall—and at the level of industrial sectors in particular—in response to events characterized as force majeure, exogenous shocks or periods of uncertainty.

Behind the curtain of payday lending: revealing consumer insights and ethical challenges in Indonesia and the USA using web-scraping methods

PurposeThis paper aims to explore the consumer insights and ethical concerns surrounding the online payday loan services available in the Google Play Store. This research was conducted to compare whether the presence or absence of debt collection protection acts in a country creates differences in consumer experiences regarding the ethics of payday loan collection. Specifically, the study compares customers’ experiences in both the Indonesian and US markets.Design/methodology/approachIndonesia and the USA were chosen because they have very different regulatory structures for the payday loan industry. The data was scraped using Python from 27 payday loan apps on the Indonesian Play Store, resulting in a total of 244,697 reviews extracted from the Indonesian market. For the US market, 446,010 reviews were extracted from 14 payday loan apps. The data was further analyzed using NVIVO.FindingsThe results suggest that consumers of payday loans in Indonesia and the USA hold positive views about the benefits of payday loan apps, as revealed by the word frequency and word cloud analysis. Notably, customers in both countries did not express any negative sentiments regarding the unethical interest rate charged by the payday loan, contradicting what is commonly reported in academic literature. However, a distinct pattern of unethical conduct was observed in both countries concerning marketing communication and debt collection practices. In the Indonesian market, payday loan companies were found to engage in unethical debt collection activities. In the US market, payday lenders exhibited unethical behavior in their marketing communication, particularly through deceptive advertising that makes promises to consumers that are not delivered.Originality/valueThe study aims to provide evidence on the various experiences of customers in the presence and absence of debt collection regulations using a novel methodology and a large sample, which strengthens the results and conclusions of the study. The study also intends to inform policymakers, particularly the Indonesian government, about the need for specific laws to regulate the debt collection process and prevent unethical practices. Ultimately, the study is expected to protect the rights of consumers from a deceptive marketing communication or unethical debt collection practices in both the Indonesian and US markets.

P17 Scroll Your Way to Better Health: Assessing the Key Determinants of Coverage Decision-Making for Digital Therapeutics in US and EU Markets

P17 Scroll Your Way to Better Health: Assessing the Key Determinants of Coverage Decision-Making for Digital Therapeutics in US and EU Markets

Sustainability, Resilience, and Returns During COVID-19: Empirical Evidence from US and Indian Stock Markets

The growing number of consulting reports published globally show mixed evidence of higher returns for environmental, social, and governance (ESG) indices as compared to equity indices. The present study analyzes whether or not sustainability provided resilience, during turbulent times, to the US and India, who were worst hit by the COVID-19 pandemic. The study tests whether higher ESG scores led to higher stock returns during and after the COVID-19 pandemic. The findings revealed little and negative associations of sustainability with stock returns for sample firms during the COVID-19 crisis. There is no empirical evidence indicating that sustainability guarantees resilience during crisis times. Investors have their own preference channels and taste for sustainability that are beyond their financial motives. JEL Codes: Q01, G120

The informativeness of dividend ratios and their economic predictive value towards equity premium

Purpose This paper aims to examine and compare the dividend ratios’ statistical and economic ability to predict the equity premium in the UK and US markets and two US sub-indices (S&P 500 Growth and S&P 500 Value). Design/methodology/approach In this paper, the authors use the linear regression models to examine the dividend ratios’ statistical ability to predict the equity premium. The in-sample and out-of-sample approaches, including Diebold and Mariano (1995) statistics, and Goyal and Welch’s (2003) graphical approach, are used. Also, the mean-variance analysis is used to test the economic significance. Findings The paper findings indicate that the dividend ratios have in-sample and out-of-sample predictive abilities in both UK and US markets and both US sub-indices. However, the results show that the dividend ratios have a less impressive predictive ability in the US market compared to the UK market and less in the US value index than the US growth index. This could indicate that there is no relation between the number of companies that distribute dividends in each index and the informativeness of dividends ratios. Furthermore, the tests show the dividend ratios’ predictive ability departure during particular periods and in some indices. Research limitations/implications Results and implications of this research are exclusively applied to the US and UK markets. These results can also be applied with caution to other markets, taking into consideration the distinctive characteristics of these markets. Practical implications Results revealed in this paper imply that the investors in any of the indices may experience economic gain by adopting a dynamic trading strategy using the information content of the dividend ratios prediction models instead of the benchmark model, which is the prevailing simple moving average model. Originality/value This paper adds value through testing the prediction models’ economic significance in two well-developed markets, in addition to exploring the relationship between the number of companies distributing cash dividends and the dividends ratio prediction ability. Unlike most of the previous studies in which dividend ratios’ prediction ability is attributed to the number of companies that distribute dividends in the market, this paper denied this interpretation by studying two S&P 500 sub-indices. To the best of the authors’ knowledge, this is the first study to test the prediction models’ ability for these sub-indices.

Pre- and Post-COVID-19: The Impact of US, UK, and European Stock Markets on ASEAN-5 Stock Markets

This study investigates the relationship between closing–opening prices of stocks in the US, UK, and European markets and the prices of stocks in the five Association of Southeast Asian Nations (ASEAN-5) markets, a group consisting of five founding members, namely, Indonesia, Malaysia, the Philippines, Singapore, and Thailand. In particular, this study examines the impact of US, UK, and European stock market movements on ASEAN-5 stock markets before and during the COVID-19 pandemic. An autoregressive distributed lag (ARDL) bounds testing approach was employed on two independent data sets, representing prices of stocks before and during the COVID-19 pandemic. The results reveal that among the ASEAN-5 markets, only the Philippines had a cointegration relationship with the US, UK, and European markets before the crisis. However, almost all ASEAN-5 markets moved in tandem with the US, UK, and European markets during COVID-19, except for Thailand. These empirical findings also indicate that the stock markets in the two regions tended to co-move during the COVID-19 pandemic, implying a contagion effect. Further, the causality results also provide substantial evidence of contagion between markets during the pandemic. These results imply that the stock markets in ASEAN-5 are susceptible at the opening bell to the behaviour of US, UK, and European stocks. Therefore, investors or traders in ASEAN-5 should participate in foreign markets (other than the US, UK, and Europe) that do not exhibit cointegration relationships to better mitigate and manage risk at the opening bell, especially during a global crisis.

Exploring the Potential Challenges for Developing Generic Orphan Drugs for Rare Diseases: A Survey of US and European Markets

ObjectivesThe US Food and Drug Administration in 1983 and the European Union’s European Medicines Agency in 2000 implemented the orphan drug development program for rare diseases. The study aimed to find the potential challenges encountered by generic companies in developing generics for rare diseases. MethodsWe performed a thematic analysis, which consists of qualitative and quantitative research. For data analysis of approved orphan drugs, we used statistical methods, and for the industrial case study, we selected 14 generic companies and conducted semistructured interviews related to 10 critical areas of drug development. ResultsThe orphan drug approvals were classified into 4 categories: the number of orphan approvals, pediatric claims, formulation, and therapeutic areas. We analyzed the approvals from 2001 to 2021; the Food and Drug Administration approved 815 drugs and European Medicines Agency approved 258 drugs. The pediatric orphan approvals were analyzed from 2010 to 2021; the average percentage of orphan drugs claim pediatric exclusivity during this period was found to be 31.8%. In formulation, we found the highest percentage of drugs belong to small molecules at 71%. In the therapeutic class, oncology drugs have a majority of approvals at 25%. The industrial case study responses revealed that the major challenge for drug development is the complexity of the disease at 21%, followed by the limited market at 17%. ConclusionsThere is a high need for generic orphan drugs in the developing countries. The generic companies can use the opportunities provided by health authorities for the benefit of both the company and the patient perspective.

Risk spillovers from China's and the US stock markets during high-volatility periods: Evidence from East Asianstock markets

This paper studies cross-country risk spillovers through C-vine copula quantile regression. We find Both China's and the US markets can result in large risk spillovers to East Asian markets. Furthermore, their significant conditional spillovers indicate they can emit risk through an intermediary market. However, their distinctive dependency structures with East Asian markets reflect their differences in spillovers to the markets in magnitude. The risk spillovers from US are stronger than China in magnitude. Moreover, the risk spillover from China's stock market during its high-volatility period is weaker than the whole period, which is contrary to the US market. It may imply Chinese financial influences gradually increase with Chinese financial liberalization and regional integration. Our results have implications for macroprudential regulators adopt the effective supervision and regulation to deal with the cross-border risk spillovers, and for international investors in risk hedging, derivative valuation and investment.

Problems in the US, UK and Hong Kong Property Markets Under the Impact of COVID-19

Contemporarily, the COVID-19 has negative affected various field globally including property markets. On this basis, this paper discusses the existing real estate problems in some countries and some new problems caused by the COVID-19 epidemic, as well as the causes of these problems. Subsequently, implementations and policies that the governments of these countries proposed to address issues are discussed. To be specific, this paper focuses on the distance and analysis of three countries or regions, namely the United Kingdom, the United States and Hong Kong. According to the analysis, the United Kingdom mainly focused on immigration under the pandemic; the United States focused on analyzing different problems in real estate markets caused by the epidemic among cities with different functions; while Hong Kong, China focused on analyzing the problems and causes of low human settlement wages and low per capita land occupation area. These results shed light on guiding further exploration of policy implementation under risk conditions.

US and Russian Financial Markets: Comparative Analysis

US and Russian Financial Markets: Comparative Analysis

Volatility Spillover Effects of the US, European and Chinese Financial Markets in the Context of the Russia–Ukraine Conflict

The present study aims to investigate the volatility spillover effects in the international financial markets before and during the Russia–Ukraine conflict. The subject of this paper is the study of the influence of the recent war between Russia and Ukraine on the transmission of volatility between the American, European and Chinese stock markets using the DY methodology. The sample period for daily data is from 1 June 2019 to 1 June 2022, excluding holidays. The volatility spillover index increased during the war period, but this increase remains insignificant compared to that recorded during the COVID-19 pandemic crisis. According to the empirical results, we also found varying levels of dependence and spillover effects between the European, American and Chinese stock indices before and during the Russia–Ukraine conflict.