Market Uncertainty Research Articles

Capital Flows to Emerging Markets: The Role of Information Transparency

Using annual capital flow data from 1990 to 2010 for 21 emerging markets, this study empirically investigates the impact of macroeconomic information transparency on capital flows, taking into account financial market uncertainty. The level of in- formation transparency is measured using the country's compliance with the IMF's SDDS. The findings reveal that SDDS compliance mitigates the negative influence of the VIX index on both net and total gross inflows. However, the positive effect of SDDS compliance on capital inflows is observed only when the VIX index reaches a sufficiently high level. This relationship is primarily driven by other in- vestment inflows, as it is the only type of capital flow significantly affected by the SDDS compliance in conjunction with VIX. The results suggest that although enhanced information transparency in emerging markets may not attract more foreign capital during normal periods, it provides stability by reducing the decline in other investment inflows during times of financial turmoil, ultimately contributing to the overall stability of total capital inflows.

Demand Forecasting for Agro Tech Technical Textiles

Demand forecasting is vital in the agrotech industry, merging technology with agriculture to drive innovation and efficiency. Accurate forecasting helps companies predict market trends, optimize resource use, and enhance operations. By anticipating future demand for agricultural products and technological solutions, businesses can make informed decisions on production, inventory, and marketing. However, demand forecasting in agrotech faces challenges such as seasonal variations, limited data, technological complexity, and market uncertainties. Factors like weather patterns, regulatory changes, and shifting consumer preferences add to the difficulty. To address these challenges, methodologies such as statistical techniques, data analytics, and machine learning are employed. Common methods include time series analysis, regression analysis, and hybrid techniques, which use historical data to forecast future trends. Effective demand forecasting improves resource planning, supply chain management, and customer satisfaction. Aligning production with expected demand and optimizing inventory can cut costs, reduce waste, and boost competitiveness. Demand forecasting is essential for strategic planning in agrotech, enabling businesses to predict market trends, meet customer needs, and achieve sustainable growth in a dynamic environment.

Securing the Future: Strategies for Global Polio Vaccine Security Amid Eradication Efforts

Background/Objectives: As we commemorate 50 years of the Expanded Programme on Immunization (EPI), the global mission to eradicate polio stands at a critical juncture. While remarkable progress has been made over the past decades, ensuring a steady supply of polio vaccines remains a significant challenge that could undermine these achievements. This manuscript aims to address the complexities of polio vaccine security within the context of the Immunization Agenda 2030 (IA2030) and the Global Polio Eradication Strategy 2022–2029, proposing actionable strategies to strengthen the vaccine supply. Methods: This manuscript analyzes obstacles to vaccine security, including supply disruptions and market uncertainties. It presents the Polio Vaccine Security Framework as a key strategy for addressing these challenges. Data were gathered from Global Polio Eradication Initiative (GPEI) reports, consultations with key stakeholders, and analyses of past vaccine shortages. Results: The findings indicate that the primary risks to vaccine security include the lack of a coherent long-term policy framework on polio vaccination, the absence of a clear polio vaccine development roadmap, and insufficient long-term, predictable forecasting. Additionally, stronger coordination is needed between stakeholders involved in vaccine supply, polio containment, and research, as well as addressing challenges related to financing and access to resources. Conclusions: A robust, adaptable, and sustainable approach to vaccine security, proposed in the Polio Vaccine Security Framework, is critical to achieving and sustaining polio eradication. Collaboration among policymakers, manufacturers, and stakeholders to implement it is essential to ensure the uninterrupted supply of polio vaccines, protecting the progress made over the past half century, and preventing a resurgence of poliovirus in the future.

Analysing the Stock Performance of DLF in the Face of the Pandemic: A Study on Risk, Return, and Market Correlation

This study investigates the stock performance of DLF Ltd., a prominent player in the Indian real estate sector, in three distinct phases: pre-pandemic (March 2019 to March 2020), during the pandemic (March 2020 to March 2022), and post-pandemic (March 2022 to September 2024). Using monthly historical stock prices of DLF, the SENSEX, and the BSE Realty Index, collected from the BSE website, this research applies mean-variance analysis to assess the risk and return characteristics of DLF’s stock during these periods. Additionally, correlation and regression analyses are conducted to explore the relationship between DLF’s stock returns and the broader market indices, with a particular focus on the BSE Realty Index, given its relevance to the real estate sector. The study reveals the significant impact of the COVID-19 pandemic on the real estate market, especially on stocks like DLF, which experienced heightened volatility during the pandemic. The pre-pandemic phase reflected stable growth, while the pandemic period saw a sharp decline in stock returns due to market uncertainty and economic downturns. However, the post-pandemic phase witnessed a robust recovery, with DLF’s stock aligning closely with the recovery trends in the real estate sector, as indicated by its correlation with the BSE Realty Index. This paper aims to provide valuable insights into the stock performance of DLF in relation to macroeconomic factors and sector-specific trends, offering an understanding of how the company’s performance has evolved to enhance shareholder value across these three critical phases. The findings offer implications for investors and stakeholders in assessing the resilience and potential of real estate stocks in times of crisis and recovery.

Sectoral responses to economic policy uncertainty and geopolitical risk in the US stock market

We examine the impact of economic policy uncertainty and geopolitical risk on various industries, highlighting their asymmetric effects on sectoral volatility. Furthermore, we investigate the differential effects of economic policy uncertainty and geopolitical risk on sectoral volatility, distinguishing between good and bad volatility responses. We find an asymmetric relationship between economic policy uncertainty and geopolitical risk in these industries, with economic policy uncertainty generally exerting a stronger impact on sector-specific volatility compared to geopolitical risk. During normal circumstances since the 2010s, the influence of geopolitical risk on sector-specific volatility has been relatively insignificant. However, both economic policy uncertainty and geopolitical risk have played significant roles in affecting multiple sectors during certain crisis periods, with geopolitical risk demonstrating short-term effects. These findings have important implications for both investors and policymakers. Investors can time positions using insights on policy uncertainty and geopolitical risk, while policymakers can identify vulnerable sectors.

Pricing blue carbon to promote the protection and restoration of the marine environment: A real option model

Pricing blue carbon will allow the monetization of the implicit carbon sequestration value of socioeconomic activities in marine ecosystems. This will empower those engaged in marine environment protection and restoration to reap economic benefits while imposing costs on those who harm the marine environment or carbon-emitting enterprises. This can significantly increase the enthusiasm of local governments, enterprises, and others for protecting and restoring the marine environment. However, owing to the characteristics of public goods and the externalities of blue carbon, it is difficult to price them through the supply and demand relationship of the traditional market. This paper focuses on how to price blue carbon under government policies and market uncertainties to encourage investors to engage in blue carbon projects involving the ecological protection and restoration of coastal wetlands. First, a universal blue carbon pricing model is established via the real option approach. The mangrove blue carbon project in Zhanjiang, Guangdong, was used as a case study to evaluate the price of mangrove blue carbon. This research provides technical support for the formation of blue carbon prices, and this method can be used not only to promote the protection and restoration of the marine environment but also to optimize the supply of blue carbon, fully leveraging its role in addressing climate change.

An Analytical Study On The Correlation Between Soybean And Palm Oil Prices And The Interplay Of Market Forces

This paper studies the price relationship between two important agricultural commodities: soybean oil and palm oil. For the analysis the following statistical methods – Pearson correlation and multivariate regression – have been used on a simulated dataset over a fifteen-year period. The present study unwraps the economic, environmental, and policy factors that contribute to their interconnected nature. While the results show a strong positive correlation between the two future prices, the outcomes also provide a much broader perspective on the role of economic conditions, including the global supply chain and demand spillover. Moreover, environmental trends and policy shifts together shape future price trends equally. In addition, the paper forecasts the possible future price trend of each commodity using ARIMA and helps to determine the market direction. This research contributes to the broader discussion on agricultural economics and commodity markets, offering a data-driven perspective that supports strategic planning and informed action in the face of market uncertainties and environmental challenges

The Impact of Financial Crises on IPO Underpricing in the Chinese Stock Market: A Comparative Analysis of the 2008 Financial Crisis and the COVID-19 Pandemic

The capacity of enterprises to access finance is intrinsically linked to their long-term sustainability. The efficient allocation of financial resources across society increases the utilization of social assets. Initial public offerings (IPOs) represent a highly effective mechanism for generating capital to support the growth and development of firms. The paper thus examines the impact of financial crises, specifically the 2008 financial crisis and the Covid-19 pandemic, on IPO pricing in the Chinese stock market. In this paper, pre-crisis and post-crisis IPO data are analyzed to identify trends and changes in underpricing. Statistical methods are used to examine the relationship between market conditions, economic indicators and IPO characteristics. The results show that IPO underpricing decreased significantly after the 2008 financial crisis due to increased market caution and regulatory changes, while the COVID-19 pandemic led to an increase in market uncertainty and volatility, which led to an increase in underpricing. These insights are significant for investors, companies planning initial public offerings, and policymakers aiming to stabilize financial markets during economic downturns.

The dynamic relationship among economic and monetary policy, geopolitical risk, sentiment, and risk aversion: A TVP-VAR approach

We study how external economic and market uncertainty factors affect investors’ risk aversion. Utilizing TVP-VAR framework, we examine the impact of economic policy uncertainty (EPU), monetary policy uncertainty (MPU), geopolitical risk (GPR), and investor sentiment (Sent) on the risk aversion index (RAI). Our analysis reveals that (i) EPU and MPU are primary transmitters of shocks, significantly influencing RAI; (ii) GPR has a minimal and temporary effect, while Sent exhibits limited influence; and (iii) the impact on risk aversion has lessened, indicating growing market resilience to policy-related shocks. These findings underscore the psychological impact of economic instability on investors’ risk aversion.

Research on the Impact of Investor Sentiment on Stock Returns Based on Uncertainty

This paper examines the relationship between firm-level investor sentiment and stock returns, and attempts to illustrate the impact of financial market uncertainty on this relationship. The results show that investor sentiment significantly affects the short-term returns of stocks, and this influence weakens when uncertainty increases. And in companies with less uncertainty, the effect becomes even stronger.

Climate policy uncertainty, market volatility and sustainable investing: new insights from a TVP-VAR framework

ABSTRACT Under a TVP-VAR framework, this study investigates not only the role of climate-transition stocks (CS) and green bonds (GB) in combating climate policy uncertainty and market volatility but also the association between CS and GB in the context of climate and market uncertainties. Findings reveal that both CS and GB are resistant to climate and market risks from a medium- to long-term perspective. However, from a short-term perspective, extreme market turmoil caused by the COVID-19 pandemic has weakened the ability of CS and GB to withstand market risks. Furthermore, risk spillovers between CS and GB are consistently positive and tend to be medium-lived, providing new evidence for co-movements between sustainable equity and bond markets.

Pengaruh Pengetahuan Investasi, dan Herding Behaviour terhadap Keputusan Cryptocurrency (Studi Kasus pada Mahasiswa Perguruan Tinggi Negeri di Jambi)

This descriptive quantitative study aims to analyze and produce an empirical test of the influence of investment knowledge and herd behavior on cryptocurrency investment decisions among state university students in Jambi. The population and sample used are state university students in Jambi who have carried out cryptocurrency investment activities. The samples in this study were 54. Meanwhile, the total sample did not include Jambi Ministry of Health Polytechnic students. Data was collected by distributing questionnaires using Google Forms and Likert scale measurements. The data testing techniques used were validity and reliability tests, r-square tests, and hypothesis tests using Smartpls 4.0 software. The study results showed that (1) investment knowledge positively and significantly affects investment decisions. The better the students' investment knowledge about cryptocurrency is, the more it will affect investment decisions. The combination of awareness, knowledge, skills, attitudes, and behaviors is needed to make the right financial decisions and achieve individual financial well-being. and (2) Herding Behavior has a positive and significant effect on investment decisions; herd behavior is influenced by psychological factors that make investors take illogical actions, significantly when market uncertainty increases and market volatility is high. This is following the theory of financial behavior, which states that subjective norms, among others, are influenced by other investors' opinions, which can affect the decision of state university students in Jambi to invest in cryptocurrency. These findings have practical implications for understanding and managing cryptocurrency investments in the face of market uncertainty.

Personal devices: investing apps and the selectively self-directed digital-financial subject

ABSTRACT Across the world, a growing number of financial non-professionals are investing in stocks through mobile and web-based trading apps that are designed to be ‘convenient’ and ‘easy’ for non-expert investors to use. What new kinds of investor subjects are being formed through the use of these devices, which bring the opportunities and uncertainties of the financial market into the layperson’s smartphone and laptop computer? Drawing on interviews with twenty trading app users in Singapore, this article argues that app-using investors commonly conduct themselves as selectively self-directed digital-financial subjects. In contrast to the paradigmatic neoliberal subject, who strives to be as informed, calculative and controlled in investing their money as possible, the app-using investor aims to understand and control only some aspects of their investing practice, while in other aspects allowing their practice to be shaped and determined by digital designs and operations that are opaque and even threatening to them. App-using investors selectively choose to go along with arrangements in which their autonomy and agency are compromised, on the chance of profitable outcome. With the proliferation of consumer ‘fintech’ applications that invite lay users to enter such arrangements, the selectively self-directed subject will likely become a more commonly encountered figure.

Understand your decision rather than your model prescription: Towards explainable deep learning approaches for commodity procurement

Hedging against price increases is particularly important in times of significant market uncertainty and price volatility. For commodity procuring firms, futures contracts are a widespread means of financially hedging price risks. Recently, digital data-driven decision-support approaches have been developed, with deep learning-based methods achieving outstanding results in capturing non-linear relationships between external features and price trends. Digital procurement systems leverage targeted purchasing decisions of these optimization models, yet the decision-mechanisms are opaque. We employ a prescriptive deep-learning approach modeling hedging decisions as a multi-label time series classification problem. We backtest the performance in two evaluation periods, i.e., 2018–2020 and 2021–2023, for natural gas, crude oil, nickel, and copper. The approach performs well in the first evaluation period of the testing framework yet fails to capture market disruptions (pandemic, geopolitical developments) in the second evaluation period, yielding significant hedging losses or degenerating into a simple hand-to-mouth procurement policy. We employ explainable artificial intelligence to analyze the performance for both periods. The results show that the models cannot handle market regime switches and disruptive events within the considered feature set.

Evaluating the environmental and financial performance of additive manufacturing at scale in the consumer goods industry

As corporate sustainability commitments and environmental regulations intensify, additive manufacturing users must balance the technology's maturing economic value with its application- and process-dependent environmental impact. With limited methods to navigate this multi-dimensional variability at scale, additive manufacturing stakeholders face challenges when making growth and investment decisions. To bridge this gap, this study applies system modeling methodologies to a case study of an additive manufacturing service unit in the sporting goods industry aiming to improve its product portfolio's economic and environmental impacts and scale its capabilities. A tradespace model compares the value of additive manufacturing to injection molding across product characteristics and life cycle decisions, and a flexible design analysis evaluates additive manufacturing scaling strategies, considering market and technology uncertainties. The tradespace analysis reveals that additive manufacturing reduces product environmental footprint by 95 % and unit cost by 93 % for 1-to-20-part production volumes compared to injection molding, while injection molding lowers environmental footprint by 72 % and unit cost by 56 % for 100-to-50,000-part production volumes compared to additive manufacturing. This analysis also suggests that additive manufacturing's economic and environmental value increases when located in geographies with low-carbon footprint energy and when manufacturing very low production quantities or small parts that maximize build capacity. The flexible design analysis indicates that expanding internal production capacity to a larger facility with renewable power, once higher demand is confirmed, can reduce part environmental footprint by up to 49 % and increase Net Present Value by more than 600 % compared to maintaining current operations that leverage external service bureaus. The results demonstrate the potential of these system modeling methodologies in integrating financial and environmental impact assessments at the company level for strategic scaling decisions. Future model developments are recommended to incorporate additive manufacturing's unique design impacts on the product life cycle, more nuance in the impact analyses, and the social component of the technology's sustainability.

Strategy adaptation under external uncertainty: examining speed-based competitions

PurposeDespite the growing attention being paid to the role of uncertainty in the competitive business environment, few studies have considered uncertainty as an antecedent factor and explored its direct impact on accelerating a firm’s innovation speed. This study develops a conceptual framework that examines the impacts of technological uncertainty and market uncertainty on innovation speed, building on complex adaptive theory. Furthermore, it is important to note that the internal resources of a firm and its external environment are not separate entities. In this study, we investigate the moderating role of a firm's internal and external resource ability (financial constraints level and organizational slack level) in the relationship between environmental uncertainty and innovation speed.Design/methodology/approachOur data sample is the panel data of China's A-share listed companies. The data year span is from 2000 to 2018. We use a hierarchical regression analysis model.FindingsOur results reveal that both technology uncertainty and market uncertainty can promote innovation speed. Still, a firm’s organizational slack positively moderates the relationship between technology uncertainty and innovation speed, and financial constraints negatively moderate the relationship between demand uncertainty and innovation speed.Originality/valueOur research contributes to the existing literature on uncertainty and extends its research perspective by no longer taking uncertainty as an environmental factor but exploring its direct impact. Still, our research focuses on innovation speed and discusses the impact of environmental uncertainty (including technology uncertainty and demand uncertainty) on firms’ innovation speed, expanding the limitations of previous research, which usually holds a relatively general perspective on innovation problems.

Unveiling the antecedents of sustainable performance: Insights from hospitality industry managers

The hospitality industry faces significant challenges in achieving sustainable performance, particularly amidst a rapidly changing market and environmental uncertainties. Unfortunately, previous studies have paid limited attention to this specific aspect of performance. This study explores the antecedents – organizational resilience, dynamic capabilities, agile leadership, and organizational ambidexterity – that contribute to sustainable performance among managers in this sector. A self-administered electronic questionnaire was used to collect primary data from 210 hotel managers at various levels in Makassar, Indonesia, following a purposive sampling approach. The relationships were analyzed using partial least squares structural equation modeling (PLS-SEM) with SmartPLS 4.0. The results indicate that organizational resilience and agile leadership significantly influence sustainable performance, while dynamic capability and organizational ambidexterity do not show a significant impact. Furthermore, both organizational resilience and dynamic capability are significant to organizational ambidexterity, and they also significantly contribute to agile leadership. These findings illuminate the critical determinants affecting sustainable performance in the hospitality sector, providing valuable insights for practitioners and policymakers aiming to enhance sustainability practices in the industry.

Foreign business exposure, policy uncertainty, and investment allocation decisions of Chinese multinational corporations

Using unique subsidiary-level data of 3863 Chinese non-financial firms from 2000 to 2019, we document that the multinational firms have 5.3 % higher capital expenditures than domestic firms, relative to the average. After decomposing firms' investment into domestic and offshore investment, we find that the increased capital expenditure of multinational firms results from their offshore investment allocation in response to policy uncertainty in the domestic market. Our analysis suggests that, in the face of domestic uncertainty, multinational firms switch to their offshore markets as a means to reallocate investment, rather than in response to offshore investment opportunities, access to foreign capital, or domestic competition. Overall, this paper helps us better understand the real options theory in the context of international business.

Pengelolaan Kas dan Strategi Kelangsungan Usaha pada Pedagang Kecil Somai Bagas di Pringapus

This study aims to analyze financial management in Micro, Small, and Medium Enterprises (MSMEs) in Semarang Regency, focusing on various business sectors such as culinary, retail, and handicrafts. Using a qualitative approach, data was collected through in-depth interviews lasting 30–45 minutes with 10 MSME owners. Each interview followed a structured format to ensure the depth of data obtained. The findings indicate that 70% of business owners still use manual methods for financial recording, while the remaining 30% use digital financial applications, although they face technical challenges in their usage. The main challenges faced include inadequate financial literacy (60%) and the impact of income fluctuations (50%) due to market uncertainties. A total of 80% of respondents expressed interest in improving their financial management skills. This study recommends developing digital-based financial training programs and technology support for MSMEs as a sustainable step to improve financial management efficiency and ensure the long-term viability of their businesses.

Shadow Banking, Stock Market Volatility, and Stock-Money Market Correlation: Evidence from China

ABSTRACT The study on the relationship between shadow banking (SB) and stock market volatility is scarce. Based on sample data from January 2006 to May 2024, this paper dives deep to clarify whether and how China’s SB brings uncertainties to China’s stock market and the impact of SB on the stock-money market correlation. The novelty of this paper is that we connect low-frequency SB with high-frequency financial market information under the framework of mixed-frequency data analysis. Our findings indicate that the expansion of SB could directly enhance China’s stock market volatility. There exists a persistent correlation between China’s stock and money markets in the long run. Furthermore, the rapid development of SB also strengthens the stock-money market correlation in the long run. Since SB could reduce the controllability of China’s monetary policy and increase China’s money market uncertainties, we believe that China’s money market may serve as an important channel for SB to spread risks to the stock market volatility by pushing the two markets to move more closely. We shed new light on the literature regarding the relationship between SB and stock market. This paper makes the first attempt to identify the role of SB in driving the dynamics of stock-money market correlation.