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The purpose of this paper is to investigate how bank-specific factors affect the riskiness of conventional and Islamic banks in response to shocks in major financial indices as market conditions change.

The authors use a multivariate quantile model using daily equity returns data to analyze financial risk spillovers in the values at risk that may occur between major financial indices and the equity prices of conventional and Islamic banks worldwide. Then, using both quantile and quantile-on-quantile models, the authors examine the effects of bank-specific variables such as leverage ratio, bank size, return on equity and capital adequacy ratio on the initial impact of shocks in major global financial indices on bank equity price returns at different quantiles of shocks and bank-specific variables.

The findings reveal that major financial indices can predict bank stock returns. Moreover, the authors find that the effect of bank-specific factors on the riskiness of banks is heterogeneous in that it depends on the bank type (Islamic vs conventional), the level of banking variable (high vs low) and, more importantly, market conditions.

To the best of the authors’ knowledge, this is the first study that compares the dual banking system with stock market performance while considering bank-specific variables as market conditions change. The results of this study reveal that the effect of bank-specific variables on bank performance varies according to different quantiles of shocks and bank-specific variables. Islamic banks may echo or differ from conventional banks depending on the specific factor under investigation.

This study aims to compare the safe-haven properties of different asset markets such as gold, dollar, oil and disaggregated real estate sector (house, plot and residential) against equity returns in Pakistan over the monthly period of January 2011–December 2020.

The authors use wavelet coherence to encapsulate the overall dependence and correlation of asset classes. Further, the authors also study the potential of diversification at the tail of returns distribution by applying the wavelet value-at-risk (VaR) framework.

The results of wavelet coherence show that the dependence is weaker (stronger) in the short (long)-term investment horizon. Moreover, the findings of wavelet VaR reveal that the degree of co-movement between gold and equity returns greatly affects the portfolio risk followed by residential property and oil.

The findings are beneficial for the individual investor, fund managers and financial advisors looking for the optimal portfolio combination that hedges the excessive negative movements in equity returns subject to the heterogeneity in the investment horizon.

This is a primary effort to estimate safe-haven investments opportunities at a large spectrum, including disaggregated real estate sector against stock returns in Pakistan. Moreover, this study uses wavelet coherence and wavelet VaR which have an advantage over traditional analysis for diversification.

This chapter studies the dynamic responses of the conditional quantiles and their applications in macroeconomics and finance. The authors build a multi-equation autoregressive conditional quantile model and propose a new construction of quantile impulse response functions (QIRFs). The tool set of QIRFs provides detailed distributional evolution of an outcome variable to economic shocks. The authors show the left tail of economic activity is the most responsive to monetary policy and financial shocks. The impacts of the shocks on Growth-at-Risk (the 5% quantile of economic activity) during the Global Financial Crisis are assessed. The authors also examine how the economy responds to a hypothetical financial distress scenario.

This study analyses the impact of economic and trade policy uncertainty on US and Chinese stock markets. Also, this study examines the hedge and safe-haven properties of US and China stocks against both US and Chinese economic and trade policy uncertainty.

To achieve the desired goals, the authors employ Dynamic Conditional Correlation through Glosten et al. (1993) model based on the Generalized Autoregressive Conditional Heteroscedasticity (DCC-GJR-GARCH (1, 1)) and Quantile cross-spectral (QS) models. The study uses monthly observations spanning from March 2010 to June 2022.

This study evidence that the economic and trade policy uncertainty between USA and China is extremely sensitive and has high volatility clustering effects on DJChina88 and DJUS, respectively. Conversely, against the Chinese economic and trade policy uncertainty, the US stock market indexes show both hedging properties across the period and safe-haven during COVID-19 and Russia–Ukraine crises. In contrast, among the Chinese stock markets, only DJShenzhen and DJShanghai stock indices might provide strong hedging and safe-haven properties against the US economic and trade policy uncertainties; however, DJShenzhen (DJChina88) stock shows weak hedge and safe-haven properties (hedging benefits) against Chinese trade policy uncertainty (CTPU) (Chinese economic policy uncertainty [CEPU]).

The findings have significant implications for investors, portfolio managers and regulators in hedging and making proper decisions under uncertain circumstances.

The study extends the literature on stock market performance to cover the economic and trade policy uncertainty by providing novel evidence during the recent COVID-19 and Russia–Ukraine invasion.

The purpose of this paper is to analyze the tourist landscape as represented in Turisme de Barcelona’s YouTube tourism promotional videos, looking at the landscape’s tangible locations, symbolic and tourist assets and the protagonists in an effort to interpret its storytelling in an overtourism context.

The mixed methodology is based on a visual content analysis of promotional videos posted on the official Barcelona tourism YouTube channel. Quantitative data analysis about the assets and their localization was completed with a qualitative assessment of the way these assets are displayed to unveil the narrative they convey.

The results highlight that Barcelona’s projected image is mainly based on tangible heritage (especially monuments), its recognizable cityscape and its eno-gastronomic assets. This rather conventional image is geographically concentrated on the neighborhoods perceived as tourist neighborhoods.

This analysis provides a critical reflection of the actual strategy of destination management organizations and the storytelling they transmit. The findings can help to orientate their future actions and provide a method of analysis that can be repeated for other destinations.

This paper sheds new light on the use of urban landscapes in nonstatic images both as a narrative subject and as a tangible tourist space in promotional discourse.

Systemic risk is of concern for economic welfare as it can lower the credit supply to all the sectors within an economy. This study examines for the first time the complete hierarchy of variables that drive systemic risk during normal and crisis periods in Pakistan, a developing economy.

Secondary data of the bank, sector and country variables are used for the purpose of the analysis spanning from 2000 to 2020. Systemic risk is computed using marginal expected shortfall (MES). One-step and two-step system GMM is performed to estimate the impact of firm, sector and country-level variables on systemic risk.

The findings of the study highlight that sector-level variables are also highly significant in explaining the systemic risk dynamics along with bank and country-level variables. In addition, economic sensitivity influences the significance level of variables across crisis and post-crisis periods and modifies the direction of relationships in some instances.

The study examines the systemic risk of a developing economy, and findings may not be generalizable to developed economies.

The outcome of the study provides a comprehensive framework for the central bank and other regulatory authorities that can be translated into timely policies to avoid systemic financial crisis.

The negative externalities generated by systemic risk also affect the general public. The study results can be used to avoid the systemic financial crisis and resultantly save the loss of the general public's hard-earned holdings.

The firm, sector and country-level variables are modeled for the first time to estimate systemic risk across different economic conditions in a developing economy, Pakistan. The study can also act as a reference for researchers in developed economies as well regarding the role of sector-level variables in explaining systemic risk.

The purpose of this paper is to investigate the relationship between loan default and loss given default (LGD) in an agricultural loan portfolio. The analysis employs a simulation model approach to evaluate the role that systematic and non‐systematic risks play in determining the economic capital requirements under different agricultural economic conditions.

The authors employ the theoretical approach suggested by Miu and Ozdemir to assess the role of LGD in the banking industry. A Monte Carlo simulation model is developed using Excel and calibrated to an agricultural credit association using historical data. The simulation model is used to evaluate the mark‐up to economic capital that is implied by increasing credit risks due to cyclical changes in farm real estate values.

The paper demonstrates that historical systematic risks due to the correlation between probability of default (PD) and LGD through the business cycle can result in a significant mark‐up in the economic capital required by an agricultural lender. Using historical land price changes as the driver of systematic risk, the authors show that the correlations between changing PD and land values and between the PD and LGD provide evidence of how sensitive credit risk exposure is to these parameters.

This paper is the first application of the Miu and Ozdemir model of systematic risk to an agricultural lending institution. The model approach can be adapted by farm lenders to evaluate their changing economic capital requirements through an economic cycle in agriculture.

Understanding parental psychopathology interaction is important in preventing negative family outcomes. This study investigated the effect of paternal psychiatric history on maternal depressive symptom trajectory from birth to 12 months postpartum. Maternal Edinburgh Postpartum Depression screens were collected at 1, 6 and 12 months and fathers' psychiatric diagnoses were assessed with the Structured Clinical Interview for DSM-IV from 64 families. There was not a significant difference in the trajectory of maternal depressive symptoms between mothers with partners with history of or a current psychiatric condition or those without a condition. However, mothers with partners with substance abuse history had higher levels of depressive symptoms relative to those affected by mood/anxiety disorders or those without a disorder. Our results call for a closer look at paternal history of substance abuse when treating postpartum maternal depression.

This study aims to investigate the busy season contagion effects on other clients of the Big 4 auditor’s local office associated with the non-timely (NT) filing(s) by large accelerated filer (LAF) client(s) of the office. Specifically, the authors examine the influence such events have on the audit quality and timeliness of other clients of that office.

Using panel data of annual NT filings of LAF clients between 2006 and 2019, the authors apply the ordinary least squares regression technique to model audit reporting lag (ARL) and the logistic regression technique to model the probability of restatements.

Controlling for audit firm, industry and year-fixed effects, the authors find that a LAF NT filing reduces audit quality and audit timeliness of other clients of the office, as measured by restatement risk and ARL. The impact on ARL is most pronounced on the medium and small clients within the office. The deteriorated audit quality is observed for medium clients.

The results of this study have practical implications for auditors and regulators. They reveal the contagion effect in the auditor’s local office with the NT LAF client. The main limitation of the study is the lack of staffing utilization data to allow for drawing conclusions on causality.

To the best of the authors’ knowledge, this is the first study to document the contagion effect of NT filings of LAF clients conducted at the auditor’s local office level.