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This chapter proposes a vector autoregressive VAR model with structural shocks (SVAR) that are identified using sign restrictions, and whose distribution is subject to time varying skewness. The authors also present an efficient Bayesian algorithm to estimate the model. The model allows tracking joint asymmetric risks to macroeconomic variables included in the SVAR, and provides a structural narrative to the evolution of those risks. When faced with euro area data, our estimation suggests that there has been a significant variation in the skewness of demand, supply and monetary policy shocks. Such variation can explain a significant proportion of the joint dynamics of real GDP growth and inflation, and also generates important asymmetric tail risks in those macroeconomic variables. Finally, compared to the literature on growth- and inflation-at-risk, the authors find that financial stress indicators are not enough to explain all the macroeconomic tail risks.

The purpose of this study is to investigate the impact of idiosyncratic and macroeconomic risks on capital structure on SADC countries.

Employing data from the African Financials database, the analysis is conducted over a ten year period spanning from 2009 to 2018 for 309 companies. Unit Root Fisher Chi-Square test and Granger Causality test were employed to test for unidirectional and bidirectional relationships cross-sectionally. To resolve endogeneity issues, System GMM was used as main topology for panel regression analysis.

The study confirmed that companies become risk averse when there is an increase in idiosyncratic and macroeconomic risk and therefore take less leverage. According to the perking order theory, a higher variability in earnings shows that the bankruptcy probability amplifies. Hence, institutions with high income employ more internal finance during periods of high idiosyncratic and macroeconomic uncertainty thereby lowering leverage. A positive significant and statistically relationship is also confirmed between idiosyncratic risk and leverage in Botswana, South Africa and Tanzania. Companies with higher leverage make riskier investment in line with the trade-off theory. In short, executives from the SADC region consider more importance to fluctuations in risk while accelerating or diminishing leverage in their capital structure.

The study is among one of the pioneering work underpinning the idiosyncratic risk and macroeconomic risk on capital structure and relying on a large number of companies across the SADC region. In this respect, it adds contribution to the existing literature on risks and capital structure to the socio-economic goals of the SADC region.

This chapter uses an application to explore the utility of Bayesian quantile regression (BQR) methods in producing density nowcasts. Our quantile regression modeling strategy is designed to reflect important nowcasting features, namely the use of mixed-frequency data, the ragged-edge, and large numbers of indicators (big data). An unrestricted mixed data sampling strategy within a BQR is used to accommodate a large mixed-frequency data set when nowcasting; the authors consider various shrinkage priors to avoid parameter proliferation. In an application to euro area GDP growth, using over 100 mixed-frequency indicators, the authors find that the quantile regression approach produces accurate density nowcasts including over recessionary periods when global-local shrinkage priors are used.

The purpose of this paper is to provide an analysis of the relationship between expected risk premia on property stocks and some major macroeconomic risk factors as reflected in the general business and financial conditions

Employs a three‐step estimation strategy (principal component analysis, GARCH (1,1) and GMM) to model the macroeconomic risk variables (GDP growth, INDP growth, unexpected inflation, money supply, interest rate and exchange rate) and relate them to the first and second moments on property stock excess returns of four major markets, namely, Singapore, Hong Kong, Japan and the UK. Macroeconomic risk is measured by the conditional volatility of macroeconomic variables.

The expected risk premia and the conditional volatilities of the risk premia on property stocks are time‐varying and dynamically linked to the conditional volatilities of the macroeconomic risk factors. However there are some disparities in the significance, as well as direction of impact in the macroeconomic risk factors across the property stock markets. Consequently there are opportunities for risk diversification in international property stock markets.

Results help international investors and portfolio managers deepen their understanding of the risk‐return relationship, pricing of macroeconomic risk as well as diversification implications in major Asia‐Pacific and UK property stock markets. Additionally, policy makers may play a role in influencing the expected risk premia and volatility on property stock markets through the use of macroeconomic policy.

This paper aims to identify and analyze the similarities and differences of the liquidity risk determinants within conventional and Islamic banks.

This study uses a dynamic panel data approach to examine the relationship between liquidity risk and a set of bank-specific and macroeconomic factors during 2005–2015, by selecting 27 Islamic banks and 49 conventional ones operating in the MENA region. More specifically, the dynamic two-step generalized method of moment estimator technique introduced by Arellano and Bond (1991) is applied.

The results suggest that the set of bank-specific variables influences the liquidity risk of both banking systems, while macroeconomic factors determine the liquidity risk of conventional banks. Islamic banks are not affected by macroeconomic determinants.

The research facilitates to the academicians, practitioners and bankers to have an alluded picture about liquidity risk determinants and their management. The findings can be used by bankers’ policy decision-makers to improve and enhance their consideration for liquidity risk management in both banking systems. Indeed, the study makes them aware to manage liquidity risk differently between conventional and Islamic banks, as the results reveal different liquidity risk determinants.

Compared to the abundant studies on the determinants of credit risk, researchers have not sufficiently addressed the factors influencing liquidity risk. Moreover, none of these few research studies has discussed and compared liquidity risk determinants within both banking systems operating in the Middle East and North Africa (MENA) region. This leads us to identify the similarities and differences between conventional and Islamic banks in the MENA region in respect of systematic and unsystematic determinants of the liquidity risk. The value is attributed to the increasing differentiation between Islamic and conventional banks. Islamic banks are characterized with a different liquidity structure distinguishing them from their conventional counterparts.

This study attempts to conduct a comparative analysis between dynamic and static asset allocation to achieve the long-term target return on asset liability management (ALM). This study conducts asset allocation using the ex ante expected rate of return through the outlook of future economic indicators because past economic indicators or realized rate of returns which are used as input data for expected rate of returns in the “building block” method, most adopted by domestic pension funds, does not fully reflect the future economic situation. Vector autoregression is used to estimate and forecast long-term interest rates. Furthermore, it is applied to gross domestic product and consumer price index estimation because it is widely used in financial time series data. Based on asset allocation simulations, this study derived the following insights: first, economic indicator filtering and upper-lower bound computation is needed to reduce the expected return volatility. Second, to reach the ALM goal, more stocks should be allocated than low-yielding assets. Finally, dynamic asset allocation which has been mirroring economic changes actively has a higher annual yield and risk-adjusted return than static asset allocation.

The purpose of this paper is to provide insights on how a firm's size is related to risk taking of Malaysia's insurance companies, from 2000‐2010.

The sample used for empirical testing in this study comprised direct insurance firms licensed under Malaysia's Insurance Act 1996, for the time frame between 2000 and 2010. Pearson's correlation, fixed and random effects models, and the system Generalized Method of Moments (GMM) method were used in this study.

Both the fixed effects and the system GMM panel data regression models suggested a positive link between the insurance firm size and underwriting risk. For the robustness test, the results of the analysis using changes in data broadly resemble the outputs of the levels estimation.

The sample of this study is limited to Malaysia's insurance sector only.

Advocates of the too‐big‐to‐fail (TBTF) theory believe that government support and the guarantee of a financial bailout are warranted for large financial institutions facing crises, for the main purpose of avoiding disruptions within a country's economy. The drawback, however, may be that the TBTF doctrine is the culprit behind excessive risk taking by insurance firms of large proportions. A number of regulatory concerns have been raised and addressed from this study.

This study investigates the risk-taking behavior of financial institutions in the USA. Specifically, differences between taking risks that affect primarily the shareholders of the institution and risks contributing to the overall systemic risk of the financial sector are examined. Additionally, differences between risk-taking before, during and after the financial crisis of 2007/2008 are examined.

To analyze the determinants of stand-alone and systemic risk, a generalized linear model including size, governance, charter value, business cycle, competition and control variables is estimated. Furthermore, Granger causality tests are conducted.

The results show that systemic risk has a positive effect on valuation and that corporate governance has no significant effect on risk-taking. The influence of competition is conditional on the state of the economy and the risk measure used. Systemic risk Granger-causes idiosyncratic risk but not vice versa.

The major limitations of this study are related to the analyzed subset of large financial institutions and important risk-culture variables being omitted.

The broad policy implication of this paper is that systemic risk cannot be lowered by market discipline due to the moral hazard problem. Therefore, regulatory measures are necessary to ensure that individual financial institutions are not endangering the financial system.

This study contributes to the empirical literature on bank risk-taking in several ways. First, the characteristics of systemic risk and idiosyncratic risk are jointly analyzed. Second, the direction of causality of these two risk measures is examined. Moreover, this paper contributes to the discussion of the effect of competition on risk-taking.