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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.

This study aims to investigate the effect of product market competition on the exposure of firms’ returns to consumption fluctuations (C-CAPM beta).

The C-CAPM beta comes from a regression of a stock’s returns against consumption growth, with controls for the Fama–French three factors and momentum. The Herfindahl–Hirschman index of concentration measures competition, with other measures like deregulation and tariff reductions used for robustness tests. Industries are categorized using different SIC digits, with the NAICS measure used for robustness tests. The C-CAPM beta is regressed to competition, with appropriate control variables, to find its relationship.

Higher levels of competition reduces the C-CAPM beta. The results are consistently robust to different measures of product market competition and industry identification.

Product market competition influences the sensitivity of systematic risk, as measured by the C-CAPM beta, to consumption, such that higher levels of competition reduce systematic risk.

This research contributes to a literature that admittedly is still murky, as the relationship between competition and systematic risk is still unsettled. No study (to the authors’ knowledge) examines the effect of competition on firms’ exposure to consumption. This research adds to the literature on the role of competition in risk, specifically with respect to consumption.

The purpose of this paper is to examine the effects of product market competition on capital spending (investments) financed by cash flow (CF), and the role of financial constraints (FC) on these effects.

The Herfindahl-Hirschman index of concentration measures competition. Earnings retention, working capital, the Kaplan and Zingales (1997) index and CF shortfalls measure FC. Regressions relating capital spending to competition are performed for the full sample, as well as financially constrained and unconstrained, and growth and value firms’ sub-samples. For robustness, large reductions in import tariffs are examined to exogenously measure competition, with the impact of these on capital spending tested via the difference-in-difference method.

The results show that competition fosters valuable investments when firms are financially unconstrained, especially for growth firms, and reduces these investments when they are financially constrained, especially for value firms.

The role of policy makers in alleviating FC should be focused toward growth firms that operate in competitive industries. As well, increasing financial pressure on value firms in competitive industries can have desirable effects, as it forces these firms to reduce investment inefficiency.

Many firm-specific and environmental factors drive the relation between competition and investment. Khanna and Tice (2000) find profitable firms increasing and highly levered firms decreasing investments in response to Wal-Mart’s entry into their markets. Jiang et al. (2015) suggest that environments with predictable growth drive a positive relation between competition and investments. This study claims that another factor that affects this relation is the firm’s level of FC.

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 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.

This paper examines and forecasts correlations between cryptocurrencies and major fiat currencies using Generalized Autoregressive Score (GAS) time-varying copulas. The authors examine to which extent the multivariate GAS method captures the volatility persistence and the nonlinear interaction effects between cryptocurrencies and major fiat currencies.

The authors model tail dependence between conventional currencies and Bitcoin utilizing a Glosten-Jagannathan-Runkle Generalized Autoregressive Conditional Heteroscedastic model (GJR-GARCH)-GAS copula specification, which allows detecting the leptokurtic feature and clustering effects of currency returns distribution.

The authors' results show evidence of multiple tail dependence regimes, implying the unsuitability of applying static models to entirely describe the extreme dependence between Bitcoin and fiat currencies. Compared to the most common constant copulas, the authors find that the multivariate GAS copulas better forecast the volatility and dependency between cryptocurrencies and foreign exchange markets. Furthermore, based on the value-at-risk (VaR) and expected shortfall (ES) analyses, the authors show that the multivariate GAS models produce accurate risk measures by adding cryptocurrencies to a portfolio of fiat currencies.

This paper has two main contributions to the existing literature on cryptocurrencies. First, the authors empirically examine the tail dependence structure between common conventional currencies and bitcoin using GJR-GARCH GAS copulas which consider the leptokurtic feature and clustering effects of currency returns distribution. Second, by modeling VaR and ES, the authors test the implication of using time-varying models on the performance of currency portfolios, including cryptocurrencies.