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This study examines the extent to which gold and silver bubbles are correlated and which metal’s bubble spills over to the other. In addition, the overlap in bubble-like episodes for the two metals is demonstrated and the influence of crises (global financial crises, European debt crisis and the COVID-19 pandemic) on the development of these episodes is compared.

This study proposes a two-step approach. In the first step, price bubbles are identified based on the backward sup augmented Dickey–Fuller of Phillips et al. (2015a, 2015b) and modified by Phillips and Shi (2018). In the second step, the correlation in the contagion effect of the bubbles between the two precious metal prices is measured using a nonparametric regression with a time-varying coefficient approach developed by Greenaway-McGrevy and Phillips (2016).

The findings suggest that the safe-haven property of gold and silver during financial market turbulence induces excessive price increases beyond their fundamental values. Furthermore, the results indicate that bubbles are contagious among precious metal markets and flow mainly from gold to silver; these findings are associated with the period after 2005, particularly during the global financial crisis. A contagious bubble effect is not found between gold and silver during the coronavirus disease 2020 pandemic.

The results suggest that financial market participants should consider portfolio weights in precious markets in light of the bubble correlation between gold and silver, especially during crises.

To the best of the authors’ knowledge, this is the first study that explores the correlation of bubble-like episodes between gold and silver.

The purpose of this research is to examine the linkages between oil prices and stock market in Gulf Cooperation Council (GCC) countries. Prior work argues that oil prices and the GCC stock markets are not related. This conclusion could be due to the fact that only linear linkages have been examined.

This study employs newly developed techniques of rank tests of nonlinear cointegration analysis proposed by Breitung and Gourieroux and Breitung. The Breitung's method is selected in this study due its potential superiority at detecting cointegration when the error‐correction mechanism is nonlinear.

The empirical analysis of the paper supports that oil price impact the stock price indices in GCC countries in a nonlinear fashion. Thus, the statistical analysis in this paper obviously supports a nonlinear modeling of the relationship between oil and the economy.

The paper contains the normal limitations associated with the econometric method including statistical bias.

The implication of this paper findings is that policy makers at GCC countries should keep an eye on the effects of changes in oil price levels on their own economies and stock markets. For individual and institutional investors, the nonlinear relationship between oil and stock markets imply predictability in the GCC stock markets.

The paper presents new findings on the relationships between oil prices and the stock market in GCC countries. These findings should be of interest to researchers, regulators, and market participants.

The authors aim to assess whether herding in GCC stock markets is more responsive to global dynamics than its response to regional developments. To do so, they use the largest equity market in the region which is Saudi Arabia as the benchmark, and then they examine if herding crosses from this large regional market to the rest of equities in the neighboring markets during various time periods. To compare the importance of global influences on herding, the authors investigate and compare the impact of the information flow from the US equity market on the herding of equities in the GCC markets.

To investigate herding in GCC markets the authors use the relationship between the squared market return and the cross-section absolute deviation that does not covary with market styles and/or fundamentals. In order to do that we follow Galariotis et al. (2015) and account for four styles: market-oriented, small-cap, value and momentum. As these factors have been shown to be associated with the economic fundamentals, filtering the covariance of deviation with these factors is expected to remove the style and the fundamental herding influence from the value of the dispersion.

The results show significant herding behavior that persists across various independent periods. This evidence stands even when the authors control for the well- known factor structures in stock returns. Importantly, the authors find that the few herding crossovers that occurred during the sample period are more likely to originate from the Saudi market rather than from the US. Therefore, the authors conclude that behavioral inefficiencies in the GCC equity markets are likely to be regional and that the sentiment-based trading in the US has essentially a minimal role to play.

The empirical findings are useful for policymakers who aim at preventing market manipulation in order to preserve the integrity of financial markets. Policymakers in the GCC should disclose more information to aid investors so they do not rely on other investors' trades. The portfolio managers should be aware that the correlation of GCC equities can be higher in the short term due to common market herding in these countries. As the US market does not play an important role in triggering behavioral irrationalities in these markets, investing in GCC equities is a good hedge in a US portfolio. Finally, the results have also important implications for active funds that aim to exploit short-term trending in markets in order to enhance performance.

The authors’ contribution in this paper is to investigate herding in GCC markets by using the relationship between the squared market return and the cross-section absolute deviation that does not covary with market styles and/or fundamentals. Another contribution of our paper is to investigate any cross herding from the Saudi market to the rest of the markets in the area. The previous literature on GCC equity market herding is silent on this issue and it is typically restricted to the level of the single market.

This study aims to validate the link between production manipulation and a firm’s performance variability (fundamentals and stock returns). It explores whether executives' risk-taking incentives encourage production deviations around the normal level during uncertainty.

Utilizing panel data of manufacturing firms from Compustat over three decades, the study investigates production management practices during economic uncertainty. The Economic Policy Uncertainty Index (EPU) is employed as a key metric. The empirical strategy involves documenting the effect of economic uncertainty on overproduction and underproduction, examining the role of executive compensation and assessing the impact on risk.

The research finds that risk-taking incentives increase over/underproduction, particularly amplifying the extent of underproduction during uncertainty. Production deviation rises, indicating that firms take greater risk by engaging in abnormal business operations. The study’s results are robust against various econometric methods, emphasizing the influence of risk-taking incentives on corporate production decisions.

While providing valuable insights, the study acknowledges inherent limitations, including factors influencing production decisions beyond risk-taking incentives. Further research could explore additional determinants for a comprehensive understanding.

The findings highlight the potential dark side of executive compensation that motivates suboptimal risk-taking decisions, impacting risk, cost of capital and firm performance. Policymakers and compensation committees can use these insights to design efficient systems that mitigate moral hazard problems associated with productivity changes.

The study emphasizes the broader social implications of production manipulation under uncertainty. It prompts discussions on the ethical considerations of managerial opportunism, its potential consequences for stakeholders and market dynamics.

This study contributes to the literature by examining the role of economic uncertainty on production manipulation and the influence of risk-taking incentives. It extends the earnings management literature by considering real activity manipulation and emphasizing the importance of decomposing production deviation into positive and negative values.

The purpose of this study is to examine the effect of product market competition on the oil uncertainty–investment relation.

The authors use firm-level financial data from the COMPUSTAT database, competition proxies from Hoberg and Phillips (2016) and macroeconomic data on crude oil price uncertainty. Corporate investment is measured as capital expenditure scaled by total assets or as the annual change in (net) total fixed assets plus depreciation. Since our panel data covers a short period (22 years) and the regressions include a combination of a lagged dependent variable and firm fixed effects, the authors apply Blundell and Bond’s (1998) GMM system when regressing corporate investment on the interaction between oil uncertainty and competition.

Consistent with the theories in the irreversible investment literature, the authors first show that investments are negatively related to oil uncertainty. Second, they show that firms in competitive industries decrease their investments in response to heightened uncertainty by a higher degree than firms in concentrated industries, suggesting that competition can exacerbate negative investment outcomes when success is uncertain. The authors also examine how competition relates to investment asymmetric reactions to positive and negative oil price return volatilities and find a stronger negative relationships between competition and investment-positive oil price volatility, indicating that increasing the probability of a negative outcome due to uncertainty leads firms to reduce investment to a larger extent.

The findings provide useful insights to guide corporate investment decisions under oil price change uncertainty. In particular, if firms can wait for the resolution of uncertainty before deciding to pursue irreversible investment in a competitive market, they can avoid potentially large losses by foregoing investment when the outcomes are unfavorable. This is because competition brings a greater uncertainty to firm performance if the investment outcome is poor, as firms in competitive industries share a large proportion of industry-wide profits with rivals and, thus, competition could erode profit margins and increases the likelihood of being driven out of the market. Hence, firms in competitive markets should balance between strategic preemptive motives and waiting for the resolution of uncertainty before deciding to pursue investment.

This study is the first to examine the effect of competition on the relationship between investment and oil price uncertainty. Moreover, it is the first to examine the effect of competition on the asymmetric response of investment to oil price uncertainty emanating from positive and negative changes in oil price.

This paper aims to examine the impact of oil price uncertainty on the stock market returns of ten oil importing and exporting countries in the Middle East and North Africa (MENA) region. The sample contains both oil importing and oil exporting countries that depend heavily on oil production and exports.

This paper intuitively applies the generalized autoregressive conditional heteroskedasticity (GARCH)-in-mean vector autoregression (VAR) model using weekly data over the period January 2001-February 2014.

The findings indicate that oil uncertainty matters in the determination of real stock returns. There is a negative and significant relationship between oil price uncertainty and real stock returns in all countries in the sample. The influence of oil price risk is more serious in those economies that depend heavily on oil revenues to grow.

The findings have important implications. For instance, managers should be aware of the linkages between oil price uncertainty and equity returns when they use oil to hedge and diversify equities, particularly in economies where oil is important for economic growth. The policymakers in oil importing countries should encourage companies to improve efficiency in the usage of energy and to resort to alternative sources to avoid fluctuations in earnings and equity prices. In the countries that heavily depend on oil efforts should focus on diversifying the domestic economy away from oil to protect against oil price fluctuations.

To the best of our knowledge, this is the first attempt to study the influence of oil price uncertainty in the MENA region. The sample contains both oil importing and oil exporting countries that depend heavily on oil production and exports. The empirical findings of the paper have valuable policy implications for investors, market participants and policymakers.

The purpose of this paper is to empirically examine the market efficiency, asymmetric effect and time varying risk–return relationship for daily stock return of Amman Stock Exchange (ASE).

The Box–Jenkins selection model is used to determine the stochastic process of equity returns; the exponential generalized autogressive conditional heteroscedesticity (EGARCH) and threshhold autoregressive conditional heteroscedasticity in mean are utilized to measure the persistent of volatility, risk–return relationship and volatility magnitude to bad and good news.

The univariate statistics show negative skewness, excess kurtosis and deviation from normality for the ASE index. The results show that stock return follows an ARMA (1, 1) stochastic process with significant serial correlation, implying stock market inefficiency. The results also show significant positive relationship between equity return and risk in the ASE, which is consistent with the portfolio theory. The EGARCH model suggests the existence of the asymmetric effect.

The paper offers insights into market efficiency, time‐varying volatility and asymmetric effect in the ASE.

In this paper, the aim is to investigate the tail behavior of daily stock returns for three emerging stock in the Gulf region (Bahrain, Oman, and Saudi Arabia) over the period 1998‐2005. In addition, the aim is also to test whether the distributions are similar across these markets.

Following McNeil and Frey, Wanger and Marsh, and Bystrom, extreme value theory (EVT) methods are utilized to examine the asymptotic distribution of the tail for daily returns in the Gulf region. As a first step and to obtain independent and identically distributed residuals series, the returns are prefiltered with an ordinary time‐series model, taking into account the observed Gulf return dynamics. Then, the “Peaks‐Over‐Threshold” (POT) model is applied to estimate the tails of the innovational distribution.

Not only is the heavy tail found to be a facial appearance in these markets, but also POT method of modelling extreme tail quantiles is more accurate than conventional methodologies (historical simulation and normal distribution models) in estimating the tail behavior of the Gulf markets returns. Across all return series, it is found that left and right tails behave very different across countries.

The results show that risk models that are able to exploit tail behavior could lead to more accurate risk estimates. Thus, participants in the Gulf equity markets can rely on EVT‐based risk model when assessing their risks.

The paper extends previous studies in two aspects. First, it extends the classical unconditional extreme value approach by first filtering the data by using AR‐FIAPARCH model to capture some of the dependencies in the stock returns, and thereafter applying ordinary extreme value techniques. Second, it provides a broad analysis of return dynamics of the Gulf markets.

The purpose of this paper is to analyze the efficiency performance of the Gulf Cooperation Countries (GCC) banking sector. The primary focus is to assess whether market power, risk taking activities, and regulations have significant effects on GCC banks’ efficiency performance.

The estimation and inference has been implemented using a double bootstrap procedure that simultaneously corrects for bias and validates inference on the influence of covariates. In the first stage, efficiency scores are estimated with data envelopment analysis (DEA). In the second stage, variation in the resulting efficiency scores is explained using a truncated regression model with inference based on a semi-parametric bootstrap routine.

The authors found compelling evidence that efficiency is not independent of the market structure, the bank's risk taking activities, and the regulatory environment. In particular, the Lerner Index provides evidence that market power decreases efficiency. The capital adequacy, the supervisory power and the market discipline were all found to improve efficiency. Additionally, when the risk is measured by the Z-Score or even by the ratio of non-performing loans to total loans, it adversely affects efficiency.

The results of the current study have important implications for regulators and supervisors. Promoting banks’ competitive environment in the GCC countries through reducing the information barriers to entry, encouraging bank privatization, and lowering the activities restrictions can potentially improve operational efficiency of banks. Also enhancing banks’ diversification activities and risk management techniques may have the advantage of increasing operational efficiency. Furthermore, improvements in the regulatory conditions that enhance banking supervision and monitoring would also improve efficiency.

The main contributions of the paper are threefold: first, to the knowledge, this study is the first to employ by far the most comprehensive data set of GCC banks investigated to date. Second, the analysis focusses on the influence of a wide set of factors, most of them was not covered before in related economic literature on bank efficiency of the GCC countries. Third, the methodological innovation involves applying a double bootstrap procedure proposed by Simar and Wilson (2007).

The purpose of this study is to investigate the role of stock markets in economic growth and to shed some light on the macroeconomic determinants which must have an important influence on stock markets development.

The empirical study is conducted using an unbalanced panel data from 12 Middle Eastern and North African (MENA) region countries. Econometric issues are based on estimation of some fixed and random effects specifications.

It is found that saving rate, financial intermediary, stock market liquidity and the stabilization variable are the important determinants of stock market development. In addition, it is found that financial intermediaries and stock markets are complements rather than substitutes in the growth process.

This paper has some policy implications to MENA region countries. In order to promote stock market development in the region, it is important to encourage savings by appropriate incentives, to improve stock market liquidity, to develop financial intermediaries and to control inflation.

Since it is unclear whether emerging markets in the MENA region respond, similarly, to economic and political shocks like other emerging markets and/or developed markets. This paper fills this gap by making an in‐depth analysis of 12 MENA capital markets in order to assess how they can improve their capital markets, and hence, benefit the global investor.