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This study examines the value implications of oil price uncertainty for investors in diversified firms using a sample of 922 USA firms from 2001 to 2019.

Our study employs a panel dataset to examine the value implications of oil price uncertainty for diversified firm investors. We consider several alternative specifications to account for unobserved factors and measurement errors that could potentially bias our results. In particular, we use alternative measures of the excess value of diversified firms and oil price uncertainty, additional control variables, fixed-effects models, the Oster test, impact threshold for confounding variable (ITCV) analysis, two-stage least square instrumental variable (2SLS-IV) analysis and the system-GMM model.

We find that the excess value of diversified firms, relative to a benchmark portfolio of single-segment firms, increases with high oil price uncertainty. The impact of oil price uncertainty is asymmetric, as corporate diversification is value-increasing for diversified firm investors only when the volatility is due to positive oil price changes and amidst supply-driven oil price shocks. The excess value increases irrespective of diversified firms’ financial constraints and oil usage. Diversified firms become conservative in their internal capital allocations with high oil price uncertainty. Such conservatism is value-increasing for diversified firm investors, as it supports higher performance in response to oil price uncertainty.

Our study has three important implications: first, they are relevant to investors in understanding the portfolio value implications of oil price uncertainty. Second, they are helpful for firm managers while comprehending the value-relevant implications of internal capital allocations. Finally, our findings are policy relevant in the context of the future of diversified firms in developed markets.

This paper aims to investigate the relationship between uncertainty and corporate cash holdings with the moderating role of political connections.

We employ fixed effects estimation on a panel dataset of 669 Vietnamese listed firms over the 2010–2020 period, with one- and two-way standard error clustering. We conduct various robustness tests, including two-stage least squares/instrumental variable and generalized method of moments regressions, alternative cash holding measure, and additional controls for macroeconomic conditions and ownership types.

The effect of uncertainty on cash holdings is weakened for firms with political connections relative to those without the connections. Although general firms depend on cash flows to adjust their cash holding behavior when uncertainty increases, our findings suggest that politically connected firms do not rely on internal cash flows to accumulate cash when confronted high uncertainty.

Our findings on the role of political connections in moderating the relationship between cash holding and economic policy uncertainty have practical implications for policymaking. Since political connections serve as a buffer for a firm’s liquidity, firms may want to seek those connections, which can, in turn, lead to increasing informal costs and unfair business environment.

This is the first study investigating the role of political connections to the nexus of cash, cash flow and uncertainty, providing novel evidence regarding the less dependence on internal cash flows to save cash by politically connected firms. Second, the paper enriches the literature on the motives of cash holdings by proposing a modified agency view in the context of weak investor protection. Therefore, our findings strengthen the explanation for the positive effect of uncertainty on firms’ cash holdings in emerging markets.

The purpose of this study is to explore how the unprecedented rise in the economic policy uncertainty influence Indian banking sector stability. The unprecedented rise in the economic policy uncertainty during the recent pandemic has garnered the attention of policymakers to investigate its consequences on different sectors of the economy.

In this quest, the present study uses system generalized method of moments and other econometric tools to examine the influence of economic policy uncertainty on the Indian banking sector, covering the time frame from 2000 to 2022. In addition, the current study also investigates the mediating role of regulation and supervision in the nexus of economic policy uncertainty and the Indian banking sector stability.

The empirical outcome reveals that economic policy uncertainty negatively influences banking stability. However, when economic policy uncertainty interacts with stringent banking regulations, private monitoring and supervisions, it assists in diversifying the negative impact of economic policy uncertainty on the Indian banking sector stability.

To the best of the author’s knowledge, the study is an original work and provides robust estimates that will assist policymakers in understanding the influence of policy uncertainty on the banking stability. Moreover, the study also helps in understanding the role of supervision and regulation in mitigating the negative consequences of policy uncertainty on the banking stability.

This paper attempts to document the effect of economic uncertainty on financing constraints faced by private firms.

Ordered logistic regression is used to analyze the data of private firms from 101 developing countries. The data was provided by the World Bank's Enterprise Surveys and was gathered during the period between 2006 and 2019.

The findings show that firms headquartered in countries with high economic uncertainty face more financing constraints than firms headquartered in countries with low economic uncertainty. The authors argue that the increase in economic uncertainty allows capital providers to adjust their lending decisions by reducing the provision of capital to firms. The paper also shows that firms headquartered in countries with strong institutional infrastructure and well-functioning firms are less likely to be affected by economic uncertainty while accessing finance.

The findings would help managers, investors, regulators, and policymakers better understand the implication of economic policy uncertainty on the real economy. This study also sheds the light on the importance of minimizing volatility, ambiguity, and randomness in governmental decisions and policies. Regardless of the pertinence of these policies, arbitrariness surrounding their development and communication can limit their effectiveness and produce unwanted effects.

This paper is closely related to prior literature that documents the behavior of credit providers and investors (the supply side) during the periods of economic uncertainty. The authors differ from this strand of literature by taking the perspective of firms – the demand side.

We aim to clarify the effect of economic uncertainty on Chinese stock market fluctuations. We extend the understanding of the asymmetric connectedness between economic uncertainty and stock market risk and provide different characteristics of spillovers from economic uncertainty to both upside and downside risk. Furthermore, we aim to provide the different impact patterns of stock market volatility following several exogenous shocks.

We construct a Chinese economic uncertainty index using a Factor-Augmented Variable Auto-Regressive Stochastic Volatility (FAVAR-SV) model for high-dimensional data. We then examine the asymmetric impact of realized volatility and economic uncertainty on the long-term volatility components of the stock market through the asymmetric Generalized Autoregressive Conditional Heteroskedasticity-Mixed Data Sampling (GARCH-MIDAS) model.

Negative news, including negative return-related volatility and higher economic uncertainty, has a greater impact on the long-term volatility components than positive news. During the financial crisis of 2008, economic uncertainty and realized volatility had a significant impact on long-term volatility components but did not constitute long-term volatility components during the 2015 A-share stock market crash and the 2020 COVID-19 pandemic. The two-factor asymmetric GARCH-MIDAS model outperformed the other two models in terms of explanatory power, fitting ability and out-of-sample forecasting ability for the long-term volatility component.

Many GARCH series models can also combine the GARCH series model with the MIDAS method, including but not limited to Exponential GARCH (EGARCH) and Threshold GARCH (TGARCH). These diverse models may exhibit distinct reactions to economic uncertainty. Consequently, further research should be undertaken to juxtapose alternative models for assessing the stock market response.

Our conclusions have important implications for stakeholders, including policymakers, market regulators and investors, to promote market stability. Understanding the asymmetric shock arising from economic uncertainty on volatility enables market participants to assess the potential repercussions of negative news, engage in timely and effective volatility prediction, implement risk management strategies and offer a reference for financial regulators to preemptively address and mitigate systemic financial risks.

First, in the face of domestic and international uncertainties and challenges, policymakers must increase communication with the market and improve policy transparency to effectively guide market expectations. Second, stock market authorities should improve the basic regulatory system of the capital market and optimize investor structure. Third, investors should gradually shift to long-term value investment concepts and jointly promote market stability.

This study offers a novel perspective on incorporating a Chinese economic uncertainty index constructed by a high-dimensional FAVAR-SV model into the asymmetric GARCH-MIDAS model.

This study aims to investigate the effect of political turmoil on the firm financial performance, particularly in presence of politically affiliated board of directors.

The study applied panel regression analyses on a data set of Pakistan’s listed companies ranged over 14 years, spanning from 2007 to 2021. Political turmoil was first gauged through three determinants, i.e. political protest, government election and constitutional reform, and thereafter, economic uncertainty index was used as a proxy for political turmoil. For the purpose of political connection, the study used political affiliation of the board of directors.

The study finds that political turmoil has deleterious effect on the return on assets and Tobin’s Q. The study further unveils that politically affiliated firms are relatively insulated from the volatility posed by the political uncertainty and exhibit significantly better financial outcomes.

Findings of the study suggest that appropriate composition of the board is imperative in offsetting the risk posed by the political turmoil. Hence, the results are useful for investors, policymakers and regulators to ensure financial soundness of firms in the wake of political turmoil.

To the best of the authors’ knowledge, this is the first study that investigates the moderating impact of political connection on the performance of companies in presence of political turmoil.

Exchange rate volatility is an important factor affecting investors and policymakers. This study aims to examine the impact of uncertainties, in terms of changes in economic policy, monetary policy and global financial markets, on exchange rate volatility.

The study uses the GARCH (1,1) univariate model to calculate exchange rate volatility. Economic and monetary policy uncertainties are measured using news-based indices, while global financial market volatility is measured using the implied volatility index. Panel autoregressive distributed lag modeling is used to analyze the impact of uncertainty on exchange rate volatility in the short and long run. The sample consists of 26 developed and emerging markets from 2005 to 2020.

The study finds that economic policy uncertainty significantly increases exchange rate volatility. Similarly, global financial market uncertainty leads to increased exchange rate volatility. The effect of US monetary policy uncertainty reduces exchange rate volatility.

This research contributes to the existing literature on exchange rate fluctuations by examining the impact of uncertainties on exchange rate volatility. The study uses novel news-based indices for measuring economic and monetary policy uncertainties and includes a broader sample of emerging and advanced markets. The findings have important implications for investors and policymakers.

The supply chain (SC) of the fast-moving consumer goods (FMCG) sector in India witnessed a significant change soon after introducing the Goods and Services Tax (GST). With the initiation of this tax, companies started moving from individual state-wise warehouses to consolidation warehouses model to save costs. This paper proposes a model that frames a mathematical formulation to optimize the distribution network in the downstream SC by considering the complexities of multi-product lines, multi-transport modes and consolidated warehouses.

The model is designed as mixed-integer linear programming (MILP), and an algorithm is developed that works on the feedback loop mechanism. It optimizes the transportation and warehouses rental costs simultaneously with impact analysis.

Total cost is primarily influenced by the critical factor transportation price rather than the warehouse rent. The choice of warehouses at prime locations was a trade-off between a lower distribution cost and higher rent tariffs.

The study enables FMCG firms to plan their downstream SC efficiently and to be in line with the recent trend of consolidation of warehouses. The study will help SC managers solve complexities such as multi-product categories, truck selection and consolidation warehouse selection problems and find the optimum value for each.

The issues addressed in the proposed work are transporting products with different sizes and weights, selecting consolidated warehouses, selecting suitable vehicles for transportation and optimizing distance in the distribution network by considering consolidated warehouses.

This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?

A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.

The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.

The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.

The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?

This study seeks to build a financial uncertainty index for Saudi Arabia. This index serves as a leading indicator of Saudi economic activity and helps to describe economic fluctuations and forecast economic trends.

This study adopts an extension of the Jurado et al. (2015) procedure by combining financial uncertainty factors with their net spillover effects on GDP and inflation to construct an aggregate financial uncertainty index. The authors consider 13 monthly financial variables for Saudi Arabia from January 2010 to June 2021.

The empirical results show that the constructed financial uncertainty estimates are good leading indicators of economic activity. The robustness analysis suggests that the authors’ proposed financial uncertainty estimators outperform the alternative estimates used by other existing approaches to estimate the financial conditions index.

To the best of the authors’ knowledge, this is the first attempt at constructing a financial uncertainty index for Saudi Arabia. This study extends the empirical literature, from which the authors propose a novel conceptual framework for building a financial uncertainty index by combining the approach of Jurado et al. (2015) and the time-varying connectedness network approach proposed by Antonakakis et al. (2020)