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The paper aims to analyse the drivers of changes in European equity tail risk.

For this purpose, the paper uses a panel data model with fixed effects based on five explanatory variables including the VIX, the variance risk premium (VRP), the one-year lagged slope of the riskless term-structure, the default spread and market-specific illiquidity via the measure of Bao et al. (2011). The study analyses a comprehensive database of representative European equity indices from February 2003 to December 2013. The database just contains markets of euro member states to avoid biases due to different currencies. To measure equity tail risk, the ex post realized value-at-risk was used.

There is empirical evidence that the VIX, the VRP and the default spread are key determinants of equity tail risk changes across all markets. Moreover, the results reveal that market-specific illiquidity is an important determinant in PIIGS markets and the one-year lagged term-structure slope in core markets. The analysis also documents that market-specific risk premia are a relevant determinant of equity tail risk changes. Another finding is that risk premia in PIIGS markets are basically higher as in core markets, which reflect the higher risk involved in investing in PIIGS markets.

The paper offers a unique perspective on equity tail risk in aggregate equity markets and helps both investors and risk managers to get a comprehensive understanding of relevant drivers.

This paper aims to provide new perspectives on the integration of East Asian stock markets and the dynamic volatility transmission to the Bitcoin market utilising daily data from 2014 to 2020.

The authors undertake comprehensive analyses of the dependency dynamics, systemic risk and volatility spillover between major East Asian stock and Bitcoin markets. The authors employ a vine-copula-CoVaR framework and a VAR-BEKK-GARCH method with a Wald test.

(a) With exception of KS11 and N225; HSI and SSE; HSI and KS11, which have moderate dependence, dependencies among other markets are low. In terms of tail risk, the upper tail risk is more significant in capturing strong common variation. (b) Two-way and asymmetric risk spillover effects exist in all markets. The Hong Kong and Japanese stock markets have significant risk spillovers to other markets, and quite notably, the Chinese stock market is the largest recipient of systemic risk. However, the authors observe a more significant risk spillover from the Chinese stock market to the Bitcoin market. (c) The VAR-BEKK-GARCH results confirm that the Korean market is a significant emitter of volatility spillovers. The Bitcoin market does provide diversification benefits. Interestingly, the Chinese stock market has an intriguing relationship with Bitcoin. (d) An increase in spillovers in East Asia boosts spillovers to Bitcoin, but there is no intuitive effect of Bitcoin spillovers on East Asian spillovers.

For the first time, the authors examine the dynamic linkage between Bitcoin and the major East Asian stock markets.

The recent 2008–2009 financial crisis has led international financial authorities to review the existing regulation; the Basel Committee on Banking Supervision has been thus induced to review the pillars of the Basel Accord (Basel II) in order to strengthen the risk coverage of capital framework (Basel 2.5 and III). These reforms will help to raise capital requirements for the trading book, which represents a major source of losses for internationally financial institutions, especially during crisis periods. In particular, the Committee has introduced a Stressed Value-at-Risk (SVaR) capital requirement, as a new methodology to evaluate market risk.

This chapter aims to shed some lights on the issues major banks have to face when calculating SVaR in the context of emerging markets, pointing out the differences in adopting an estimation model with respect to another one. Our results show a considerable increase in capital requirements especially when new rules are applied to financial markets with high-risk parameters, such as emerging markets are. The increased cost due to higher capital requirements could be a disincentive to investment in markets with higher risk profiles than the developed markets, taking also into account that diversification benefits deriving from investing in emerging economies have shown a decrease over time. The reduction of institutional investors can thus represent a brake on the process of innovation and evolution of emerging markets.

The use of risk proxies in internal models remains a popular modelling solution. However, there is some risk that a proxy may not constitute an adequate representation of the underlying asset in terms of capturing tail risk. Therefore, using empirical examples for the financial collateral haircut model, this paper aims to critically review available statistical tools for measuring the adequacy of capturing tail risk by proxies used in the internal risk models of banks. In doing so, this paper advises on the most appropriate solutions for validating risk proxies.

This paper reviews statistical tools used to validate if the equity index/fund benchmark are proxies that adequately represent tail risk in the returns on an individual asset (equity/fund). The following statistical tools for comparing return distributions of the proxies and the portfolio items are discussed: the two-sample Kolmogorov–Smirnov test, the spillover test and the Harrell’s C test.

Upon the empirical review of the available statistical tools, this paper suggests using the two-sample Kolmogorov–Smirnov test to validate the adequacy of capturing tail risk by the assigned proxy and the Harrell’s C test to capture the discriminatory power of the proxy-based collateral haircuts models. This paper also suggests a tool that compares the reactions of risk proxies to tail events to verify possible underestimation of risk in times of significant stress.

The current regulations require banks to prove that the modelled proxies are representative of the real price observations without underestimation of tail risk and asset price volatility. This paper shows how to validate proxy-based financial collateral haircuts models.

This study aims to investigate the risk-return trade-off in the Indian equity market at both the aggregate equity market level and in the cross-sections of stock return using alternative risk measures.

The study uses weekly and monthly data of 3,085 Bombay Stock Exchange-listed stocks spanning over 20 years from January 2000 to December 2019. The study evaluates the risk-return trade-off at the aggregate equity market level using the value-weighted and the equal-weighted broader portfolios. Eight different risk proxies belonging to the conventional, downside and extreme risk categories are considered to analyse the cross-sectional risk-return relationship.

The results show a positive equity premium on the value-weighted portfolio; however, the equal-weighted portfolio of these stocks shows an average return lower than the return on the 91-day Treasury Bills. The inverted size premium mainly causes this anomaly in the Indian equity market as the small stocks have lower returns than big stocks. The study presents a strong negative risk-return relationship across different risk proxies. However, under the subsample of more liquid stocks, the low-risk anomaly regarding other risk proxies becomes moderate except the beta-anomaly. This anomalous relationship seems to be caused by small and less liquid stocks having low institutional ownership and higher short-selling constraints.

The findings have important implications for investors, managers and practitioners. Investors can incorporate the effects of different highlighted anomalies in their investment strategies to fetch higher returns. Managers can also use these findings in their capital budgeting decisions, resource allocations and other diverse range of direct and indirect decisions, particularly in emerging markets such as India. The findings provide insights to practitioners while valuing the firms.

The study is among the earlier attempts to examine the risk-return trade-off in an emerging equity market at both the aggregate equity market level and in the cross-sections of stock returns using alternative measures of risk and expected returns.

This study examines the value relevance of recognised and disclosed revaluations of land and buildings for a large sample of Australian firms from 1993 through 1997. In contrast to prior research, we control for risk and cyclical effects and find no difference between recognised and disclosed revaluations, using yearly‐cross‐sectional and pooled regressions and using both market and non‐market dependent variables. We also find only weak evidence that revaluations of recognised and disclosed land and buildings are value relevant.

Using a convenient tail-risk measure of performance, this paper aims to explore the extent to which incorporating higher statistical moments such as an assets skewness and kurtosis, provides further insight into the potential benefits of asset-class diversification within the realm of Islamic finance.

The authors use Engle’s (2002) DCC-GARCH model to study the dynamic conditional correlations between asset classes. Furthermore, the authors use the modified value-at-risk (Favre and Galeano, 2002), which incorporates higher statistical moments, to measure the performance of portfolios during both crisis and bullish regimes.

The most important finding relates to the estimation of portfolio tail-risk. In particular, the authors find that using a standard two-moment value-at-risk (VaR) measure, which assumes normally distributed returns, rather than a four-moment VaR, which incorporates an asset skewness and kurtosis, can lead to a substantial underestimation of portfolio risk during the most extreme market conditions.

This paper contributes to the extremely limited research considering higher-moments within the realm of Islamic portfolio-management. The results suggest that Islamic portfolio managers should remain cognisant of the skewness and kurtosis parameters of their assets. Ignoring higher-moments could induce misleading inferences and would, therefore, constitute imprudent risk-management.

The purpose of this paper is to present theoretical and empirical support that the fear component associated with rare events has an impact on risk premium and market returns.

Extension of jump-diffusion model to extract the fear component from representative agent risk aversion, Standard VAR and impulse response function analysis, Event study analysis.

The model implicates that investor fear of tail jumps in the financial market impacts equity risk premium. The empirical findings show both positive stock and monetary policy shocks decrease investor’s fear. It can be attributed to that a bullish stock market and an increase in interest rate reflects expanding economy, and it leads to a decrease in fear. Moreover, a surprise decline in the expected short-term rate has a mixed impact on tail risk aversion. A plausible explanation is that investors believe a surprise drop in an expected short-term rate reflects a fast deteriorating economic outlook during unconventional monetary policy period.

This paper provides theoretical framework to decompose risk aversion into two separate components: one component associated with daily volatility, and the fear component associated with rare events. The study uses risk premiums decomposed from Chicago Board Options Exchange volatility index as proxies for the two components of risk aversion, and then utilizes standard value at risk and event study analysis to show the fear component plays a role in risk premium and market return.

This paper investigates the probable differential impact of the confirmed cases of COVID-19 on the equities markets of G7 and Nordic countries to ascertain possible interdependencies, diversification and safe haven prospects in the era of the COVID-19 pandemic over the short-, intermediate- and long-term horizons.

The authors apply a unique methodology in a denoised frequency-domain entropy paradigm to the selected equities markets (Li et al. 2020).

The authors’ findings reinforce the operability of the entrenched market dynamics in the COVID-19 pandemic era. The authors divulge that different approaches to fighting the pandemic do not necessarily drive a change in the deep-rooted fundamentals of the equities market, specifically for the studied markets. Except for an extreme case nearing the end (start) of the short-term (intermediate-term) between Iceland and either Denmark or the US equities, there exists no potential for diversification across the studied markets, which could be ascribed to the degree of integration between these markets.

The authors’ findings suggest that politicians should pay closer attention to stock market fluctuations as well as the count of confirmed COVID-19 cases in their respective countries since these could cause changes to market dynamics in the short-term through investor sentiments.

The authors measure the flow of information from COVID-19 to G7 and Nordic equities using the entropy methodology induced by the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN), which is a data-driven technique. The authors employ a larger sample period as a result of this, which is required to better comprehend the subtleties of investor behaviour within and among economies – G7 and Nordic geographical blocs – which largely employed different approaches to fighting the COVID-19 pandemic. The authors’ focus is on diverging time horizons, and the ICEEMDAN-based entropy would enable us to measure the amount of information conveyed to account for large tails in these nations' equity returns. Furthermore, the authors use a unique type of entropy known as Rényi entropy, which uses suitable weights to discern tailed distributions. The Shannon entropy does not account for the fact that financial assets have fat tails. In a pandemic like COVID-19, these fat tails are very strong, and they must be accounted for.

The purpose of this paper is to apply safety‐first portfolio principles in an environment where financial risk exists because of the probability of terrorist attacks, where the catastrophic events of September 11, 2001 (911) are the focal point of the analysis.

Safety‐first portfolios of US equities bilaterally combined with 12 developed and emerging region global equity indices are obtained for 911. Extreme value theory and safety‐first principles are used to optimize these portfolios for US risk‐averse investors. The actual performances of all portfolios in the post‐911 period are compared to the optimal results. The robustness of the results is examined by replicating the analysis for the period following July 7, 2006, when no actual terrorist attacks occurred on US soil.

Optimal ex ante (ex post) safety‐first portfolios on 911 have high (low) US weights, and on July 7, 2006 low US weights. The differences are attributed to changes in market projections and/or conditions. In all cases, wealth is preserved even without the ex post optimal portfolios.

Safety‐first portfolio optimization can protect wealth given financial risks of extreme events like terrorist attacks.

The paper shows that quantitative assessments of financial risk are feasible, even though uncertainty with experts' risk assessments of extreme events such as 911 exists because of limited historical data and low probability of occurrence. The results are useful to investors developing international diversification strategies to protect wealth given the risks of terrorist attacks.