Explore the vast range of titles available.

This study examines the reaction of four major emerging equity markets of the Pacific Rim to the US oil market fear index (i.e., the Chicago Board of Trade Volatility Index, OVX). The OVX is designed to perform as a leading indicator of the volatility in crude oil markets. Our study examines the daily data for the period of 2014 through 2019. We excluded data for the extraordinary and transitory COVID-19 time period. We found that, during this period, there were four significant breaks in the data. Impulse responses from the structural vector autoregressive (SVAR) estimation show that in the second and third subperiods, from December 2016 through December 2018, the volatility of the equity markets of Hong Kong, Shanghai, Seoul, and Taiwan responded to structural shocks to the OVX. Nonlinear Granger causality tests confirmed these findings. This period is characterized by geopolitical crises, like nuclear proliferation on the Korean Peninsula and lingering complications surrounding the Brexit referendum.

We investigate how the volatility of the iShares Latin America 40 ETF (ILF) responds to key economic and market sentiment indicators associated with economic uncertainty. Specifically, we explore the regimedependent nature of ILF volatility in relation to Economic Policy Uncertainty (EPU), U.S. Economic Uncertainty (ECU), Global Economic Policy Uncertainty (GEPU), and implied risk, as captured by the Chicago Board Options Exchange's VIX (CBOE VIX), from 2001 to 2023. Our findings highlight that the connection between market volatility and economic/market sentiment is influenced by distinct volatility regimes. Utilizing a two-covariate GARCH-MIDAS (GM) model, a regime-switching Markov Chain (MSR) model, and quantile regressions (QR), we reveal that the impact of sentiment on realized volatility varies depending on the prevailing volatility regime, reflecting investors' differing responses to market uncertainty. Additionally, our results show a significant linkage between ILF's short and long-term volatility and economic uncertainty/sentiment indicators, suggesting that these factors shape ILF volatility across different market conditions and quantiles of the volatility distribution. Overall, our findings indicate that investor sentiment and economic uncertainty extend beyond their domestic origins, influencing volatility patterns in U.S., global, and Latin American markets.

The enterprise value (EV) is a crucial metric in company valuation as it encompasses not only equity but also assets and liabilities, offering a comprehensive measure of total value, especially for companies with diverse capital structures. The relationship between economic uncertainty and firm value is rooted in economic theory, with early studies dating back to Sandmo's work in 1971 and further elaborated upon by John Kenneth Galbraith in 1977. Subsequent significant events have underscored the pivotal role of uncertainty in the financial and economic realm. Using a VAR-MIDAS methodology, analysis of accumulated impulse responses reveals that the EV of air carrier firms responds heterogeneously to financial and economic uncertainties, suggesting unique coping strategies. Most firms exhibit negative reactions to recessionary risks and economic policy uncertainties. Financial shocks also elicit varied responses, with positive impacts observed on EV in response to increases in the current ratio and operating income after depreciation. However, high debt levels are unfavorably received by the market, leading to negative EV responses to debt-to-asset ratio shocks. Other financial shocks show mixed or indeterminate impacts on EV.

This study examines the reaction of the Standard and Poor's Regional Bank Index (SPRB) to the U.S. equity market fear index (i.e., the Chicago Board of Trade Volatility Index [VIX]). The VIX is designed to perform as a leading indicator of the volatility in equity markets. However, practitioners observe many periods of divergence between the VIX and S&P 500. Our paper examines the daily data for the period of 2009 through 2019. We show that once the effects of consumer confidence and capacity utilization are accounted for, there is a negative association between the VIX and regional bank performance.

This study examines the reaction of four major equity markets of the world to the US equity market fear index, i.e., the Chicago Board of Trade Volatility Index (VIX). The VIX is designed to perform as a leading indicator of the volatility in equity markets. Our paper examines the daily data for the period of 2013 through 2018. We find that during this period there were three significant breaks in the data. Impulse responses from the structural vector autoregressive model estimation show that, in the first and second subperiods that cover from 6/2013 through 5/2016, equity market volatility in the US, UK, France, and Germany responded to structural shocks to the VIX. Nonlinear Granger causality tests confirm these findings. However, in the post Brexit-vote era, equity indices neither react to VIX structural shocks nor are caused by these shocks.

We present strong evidence against the excess-comovement hypothesis-that the prices of commodities move together beyond what can be explained by fundamentals. Prior studies employ broad macroeconomic indicators to explain common price movements, and potentially correlated fundamentals are not controlled for. We use inventory and harvest data to fit a partial equilibrium model that more effectively captures the variation in individual prices. The model explains the majority of the comovements among commodities with high price correlation, and all of the comovements among those with marginal price correlation. Common movements in supply factors appear to play an important role in the observed comovements in commodity prices.

Employing the daily broad dollar index we conduct a battery of tests for the presence olfow-dimension chaos. The dollar index return series is subjected tu Correlation Dimension tests, EDS tests, and tests fi1r entropy. While wefind strong evidence ofnonlinear dependence in the data, the evidence is not consistent with chaos. Our test results indicate that a GARCH process explains the nonlinearities in the data. We also show that employing seasonally adjusted index series enhances the robustness ofresults via the existing tests for chaotic structure.

This paper investigates the daily volatility spillovers between Standard and Poor's 500, and equity indices of Brazil, Argentina, and Mexico for the period of August 2007 through August 2012. We find that equity indices under study exhibit nonlinear dependencies, inconsistent with chaotic structure. Bivariate GARCH estimations indicate bi-directional spillovers. Findings show evidence of asymmetric market responses to shocks in all markets. Therefore, we estimate asymmetric bivariate EGARCH models. We find evidence of leverage effect as positive and negative shocks to each market impart unequal impact on the volatility of the other market. Furthermore, effects of negative shocks are much more pronounced than positive shocks. Finally, the non-linear Granger causality test results confirm that markets of Americas cause one another, i.e., there is shock feedback.

This paper investigates the daily volatility spillovers between crude oil prices and equity indexes in several developed markets. We find that the price and index series exhibit nonlinear dependencies that are inconsistent with chaotic structure. Bivariate vector autoregressive general autoregressive conditional heteroscedasticity (VARGARCH) estimations indicate bidirectional volatility spillovers. Finding evidence of asymmetric market responses to negative and positive shocks, we also estimate asymmetric bivariate VAR-exponential GARCH (VAR-EGARCH) models. We find shock transmissions to be asymmetric, whereby positive and negative shocks of the same size on oil prices have unequal impacts on the volatility of equities. Specifically, volatility responses and spillovers are more severe following negative news and shocks in each market. We further establish that there are causalities and feedback between crude oil prices and equity indexes in major developed economies. Considering the deleterious income and wealth effects of negative shocks to oil prices on the economies under study, our findings are in contrast to the notion that some economies are better able to weather negative shocks to the crude oil markets because of their increased efficiency or flexibility. Furthermore, maintaining adequate strategic crude oil reserves in the United States and other major economies is paramount in coping with shocks to crude oil supplies and price volatility.

This study investigates the relationship between the market volatility of the iShares Asia 50 ETF (AIA) and economic and market sentiment indicators from the United States, China, and globally during periods of economic uncertainty. Specifically, it examines the association between AIA volatility and key indicators such as the US Economic Uncertainty Index (ECU), the US Economic Policy Uncertainty Index (EPU), China's Economic Policy Uncertainty Index (EPUCH), the Global Economic Policy Uncertainty Index (GEPU), and the Chicago Board Options Exchange's Volatility Index (VIX), spanning the years 2007 to 2023. Employing methodologies such as the two-covariate GARCH-MIDAS model, regime-switching Markov Chain (MSR), and quantile regressions (QR), the study explores the regime-dependent dynamics between AIA volatility and economic/market sentiment, taking into account investors' sensitivity to market uncertainties across different regimes. The findings reveal that the relationship between realized volatility and sentiment varies significantly between high- and low-volatility regimes, reflecting differences in investors' responses to market uncertainties under these conditions. Additionally, a weak association is observed between short-term volatility and economic/market sentiment indicators, suggesting that these indicators may have limited predictive power, especially during high-volatility regimes. The QR results further demonstrate the robustness of MSR estimates across most quantiles. Overall, the study provides valuable insights into the complex interplay between market volatility and economic/market sentiment, offering practical implications for investors and policymakers.