Hachmi Ben Ameur

Since the aftermath of the recent global financial crisis, socially responsible (SR) investments have become an alternative form of conventional finance, giving rise to further systemic risk between conventional and SR stock markets. In this paper, we assess this risk transmission using Value at Risk (VaR) modeling for the US, Europe and the Asia-Pacific region, over the period covering January 2004–December 2016. We find that socially responsible stock markets exhibit less risk than do conventional markets in terms of the risk hedging properties induced by the SR screening. Second, contributions to systemic risk vary across market phases and return distribution levels, with a larger contribution and spillover effect during the recent global financial crisis. For example, at the downside of the distribution (CoVaR at 5%), the conventional European index shows the highest contribution to the world market’s systemic risk, while the US stock market shows the highest contribution at the upside of the distribution (CoVaR at 95%). This finding is justified by the difference in the risk aversion of investors that varies with the market state as well as the disparities in the development of SR markets.

The goal of this paper is to explore volatility transmission from various markets to the fine wine market. Knowledge of these channels for transmitting volatility to the wine market allows practitioners to anticipate the future volatility and the consequences of a shock on the wine market, to develop their investment strategy and diversify their risk. We especially analyse the impact of U.S. markets (i.e. art, commodities, credit, financial and real estate) during the 2007–2017 period. We shed additional light on how the volatility of the fine wine market varies during an extended period including a financial crisis. Our results indicate that, in the short-term, volatility is transmitted with a negative effect through the financial and commodity markets and with a positive effect through the art, residential real estate, and credit default markets. In the long-term, the wine market is impacted by all other markets. We show that correlations are time-varying.

Keywords
ADCC-GARCHAlternative assetCollectiblesFinancial marketsVolatilityWine

We investigate intraday hedging and the safe haven role of Bitcoin for stocks, currencies, and oil. The hedge concept depends on non-correlation or negative interaction, on average, while the safe haven concept depends on non-correlation or negative correlation in times of market turmoil. We look at Bitcoin’s ability to be a hedge or safe haven asset with standard financial assets by considering a short investment horizon using high frequency data. Accordingly, we propose a new measure, the q-detrending moving average cross-correlation coefficient, to characterise intraday market interdependence between Bitcoin and these assets during medium and extreme movements. During medium fluctuations, Bitcoin is a weak hedge against currencies, oil, and stocks. During high fluctuations, we find a negative relationship between Bitcoin and oil, meaning Bitcoin can serve as a safe haven against extreme down movements in this market. However, Bitcoin is a weak safe haven asset for the other two markets

The aim of this paper is to investigate the impact of Brexit on the dependence between European financial markets. We use the Diebold and Yilmaz (2009, 2012) approach to better map the relationship between the three main European markets and we propose an Optimal portfolio weighting to gain insights into the portfolio design dynamics in the period between 2013 and 2019, in particular any changes due to uncertainty surrounding Brexit. First, the findings show that between September 2015 and September 2016, the high level of volatility and spillover confirms the strong degree of market integration, with uncertainty surrounding the referendum outcome having a clear impact on the three main European markets. Second, the direction of spillover in the pre-Brexit period was from the UK market to the French and German markets in anticipation of uncertainty regarding the outcome of the referendum and the period immediately following it. Third, only the conditional correlation between the pair (CAC40–FTSE100) is characterized by an asymmetric effect.

This study aims to measure the risk dependence between the two most important energy markets, oil and gas, to analyze their risk spillovers. To this end, we apply different extreme risk measures (the value at risk, conditional value at risk, delta conditional value at risk, and copula) to high-frequency energy data to capture the intraday dynamic dependence between oil and gas prices (using, in particular, a 5-min intraday sample data from November 2014 to October 2017). Our analysis shows two interesting findings. First, while we highlight an extreme risk dependence between oil and gas markets, the risk spillover from the oil to the gas market is higher than that from the gas to the oil market. Second, the upward and downward risk spillovers exhibit asymmetry, as extreme negative shocks produce a stronger spillover effect than do extreme positive shocks. The exploration of these systemic risk forms provides significant insights for policymakers and investors in terms of risk management and portfolio diversification.

The COVID-19 outbreak generates various types of news that affect economic and financial systems. No studies have assessed the effects of such news on financial markets. This study sheds light on the impact of non-fundamental news related to the COVID-19 pandemic on the liquidity and returns volatility. Because we examined extreme events, we performed quantile regression on daily data from December 31, 2019 to the end of lockdown restrictions in China on April 7, 2020. Results showed that the non-fundamental news, as the number of deaths and cases related to the COVID-19, raised the stock market returns volatility and reduced the level of stock market liquidity, increasing overall risk, whereas fundamental macroeconomic news remained largely immaterial for the stock market. These findings are explained by a knock-on effect because the health system’s inability to manage and treat a high number of COVID-19 patients in intensive care led the country to implement a lockdown and the global economy to largely shut down.

Since the aftermath of the recent global financial crisis, socially responsible (SR) investments have become an alternative form of conventional finance, giving rise to further systemic risk between conventional and SR stock markets. In this paper, we assess this risk transmission using Value at Risk (VaR) modeling for the US, Europe and the Asia-Pacific region, over the period covering January 2004–December 2016. We find that socially responsible stock markets exhibit less risk than do conventional markets in terms of the risk hedging properties induced by the SR screening. Second, contributions to systemic risk vary across market phases and return distribution levels, with a larger contribution and spillover effect during the recent global financial crisis. For example, at the downside of the distribution (CoVaR at 5%), the conventional European index shows the highest contribution to the world market’s systemic risk, while the US stock market shows the highest contribution at the upside of the distribution (CoVaR at 95%). This finding is justified by the difference in the risk aversion of investors that varies with the market state as well as the disparities in the development of SR markets.

This paper aims at modeling and forecasting volatility in both oil and USD exchange rate markets using high frequency data. We test whether extreme co-movements (co-jumps) between these markets, as well as intraday unexpected news, help to improve volatility forecasting or not. Accordingly, we propose different extensions of Corsi (2009) model by including co-jumps and news. Our analysis provides two interesting findings. First, we find that both markets exhibit significant co-jumps driven by unexpected macroeconomic news. Second, we show that our model outperforms Corsi (2009) model and provides more accurate forecasts. In particular, while co-jumps constitute a key variable in forecasting oil price volatility, the unexpected news is relevant to forecasts of USD exchange rate volatility.

This study revisits an important issue in financial theory: the instability of market beta. To this end, we demonstrate that the linear constant risk model is misleading and does not reproduce changes in beta correctly. We develop a new nonlinear market model to capture beta instability over time for three main states: bear, normal, and bull markets. Our model endogenously identifies these states and their thresholds. We then apply this econometric specification to four major sustainable stock indexes in the US, Europe, Asia, and the World for 2004–2015. The results provide three main findings. First, the market beta is time-varying and changes asymmetrically and nonlinearly, suggesting that the systematic risk statistically differs between market regimes for the US, Europe, and the World. Second, the positive sign of beta in the bull market for these three regions suggests that systematic risk increases as economic conditions improve. Third, the lowest level of beta in the bear market indicates the usefulness of the sustainable stock index to hedge and cover investors’ portfolios against risk, particularly in a bear market.

Keywords
Time-varying market beta Bull and bear markets Instability Sustainable index nonlinearity

This paper determines the optimal financial portfolio in the multidimensional setting when the investor exhibits ambiguity aversion. We consider the Maccheroni et al. (Econometrica 74(6):1447–1498, 2006) framework which includes both the Gilboa and Schmeidler’s (J Math Econ 18(2):141–153, 1989) multiple priors preferences and the (American Econ Rev 91:60–66, 2001) multiplier preferences. We determine the optimal portfolio profile under ambiguity when the investors can invest on various risky assets. We investigate in particular the CRRA case while introducing an ambiguity index based on the relative entropy criterion. Such result extends Ben Ameur and Prigent (Econ Model 34:89–97, 2013) when there is only one risky asset. Indeed, we show for example how the ambiguity on the correlations between the risky assets crucially modify the optimal payoff. Such results have important practical applications in structured portfolio management when investing on multiple financial indices and basket options.

This paper points to further measurement errors in stock markets. In particular, we show that the application of usual performance ratios to evaluate financial assets can lead to inappropriate findings and consequently wrong conclusions. To this end, we analyze standard performance ratios as well as extreme loss-based financial ratios and compare the conclusions with those provided by systemic risk measures. The application of these different measures to both conventional and Islamic stock indexes for developed and emerging countries in the context of the financial crisis yields two interesting results. First, the analysis of financial performance exhibits further measurement errors. Second, the consideration of extreme loss and systemic risk in computing performance measures increases the reliability of performance analysis.

This paper studies stock price comovements in two key regions [the United States and Europe, which is represented by three major European developed countries (France, Germany, and the United Kingdom)]. Our paper uses recent high-frequency data (HFD) and investigates price comovements in the context of “normal times” and crisis periods. To this end, we applied a non-Gaussian Asymmetrical Dynamic Conditional Correlation (ADCC)-GARCH (Generalized Autoregressive Conditional Heteroscedasticity) model and the Marginal Expected Shortfall (MES) approach. This choice has three advantages: (i) With the development of high-frequency trading (HFT), it is more appropriate to use HFD to test price linkages for overlapping and nonoverlapping data. (ii) The ADCC-GARCH model captures further asymmetry in price comovements. (iii) The use of the MES enables to measure systemic risk contributions around the distribution tails. Accordingly, we offer two interesting findings. First, while the hypothesis of asymmetrical and time-varying stock return linkages is not rejected, the MES approach indicates that both European and US indices make a considerable contribution to each other's systemic risk, with significant input from Frankfurt to the French and US markets, especially following the collapse of Lehman Brothers. Second, we show that the propagation of systemic risk is higher during the crisis period and overlapping trading hours than during nonoverlapping hours. Thus, the MES test is recommended as an indicator to help monitor market exposure to systemic risk and to gauge expected losses for other markets

We propose several important extensions of the standard Constant Proportion Portfolio Insurance (CPPI), which are based on the introduction of various conditional floors. In this framework, we examine in particular both the margin and the ratchet based strategies. The first method prevents the portfolio from being monetized, known as the cash-lock risk; the second one allows to keep part of the past gains whatever the future significant drawdowns of the financial market, which corresponds to ratchet effects. However, as for the standard CPPI method, the investor can benefit from potential market rises. To control the risk of such strategies, we introduce risk measures based both on quantile conditions and on the Expected Shortfall (ES). For each of these criteria, we prove that the conditional floor must be higher than a lower bound. We illustrate the advantages provided by such strategies, using a quite general ARCH type model. Our empirical analysis is mainly conducted on S&P 500 and Euro Stoxx 50. Using parameter estimation, we provide portfolio simulations and measure their respective performances using both the Sharpe and the Omega ratios. We also backtest the strategies, using a sliding window method to dynamically estimate the parameters of the models based on the last two years of weekly returns. Our results emphazise the advantages of introducing time varying floors from both the theoretical and operational points of view.

While studies have focused on Islamic banking, research on the effect of the geographical environment on Islamic banks is scarce. We investigate this issue by using daily data on 12 Islamic banks in four regions (Africa, Asia, Europe, and the United States) from July 2007 to April 2016. We apply different methodological approaches (principal component analysis, panel data tests, and quantile regression). First, the principal component analysis shows that the performance of Islamic banks varies among regions. Second, the linear panel regression highlights that the geographical environment positively and significantly affects Islamic banking, suggesting the importance of externality effects. Finally, the environmental effect seems to vary with quantiles (positive effect for the lowest quantile versus negative effect for the highest quantile). This quantile specification points to nonlinearity in the environment–Islamic bank performance relationship, reflecting a time-varying discipline imposed by the Sharia board (Islamic Law). This finding helps better explain the main difference between Islamic banks in the East (Africa and Asia) and those in the West (Europe and the United States) and also enables investors to adjust their portfolio choices when considering the products of Islamic banks according to regional specificities.

The aim of this paper is to compute and describe the conditions of an optimal employee ownership contract between an employer and an ambiguity‐averse employee. We then introduce ambiguity aversion in the baseline model of Aubert et al. (2014) using the multiple prior preferences of Gilboa and Schmeidler (1989) and its extension proposed by Maccheroni et al. (2006). This model offers solutions that reconcile labor and financial economics and behavioral economics research findings on employee ownership. The paper focuses on the most common situation where employee ownership has a positive impact on corporate performance, but can also be used as an entrenchment mechanism. We determine the optimal company stock contribution, which corresponds to a perfect subgame Nash equilibrium in the ambiguity framework. Using the framework of Gilboa and Schmeidler (1989), we show that the optimal ownership contract is increasing with respect to the lower bound of the return expectation in the case of a high level of effort, and decreasing with respect to the upper bound of the return expectation in the case of a low level of effort. In the framework of Maccheroni et al. (2006), we prove that if aversion to ambiguity is sufficiently high, then we find the same behavior as in the case of no ambiguity

Abstract

This paper examines the effects of the financial crisis that began in 2008 on the equity premium of 6 French sector indices. Since the systematic risk coefficient beta remains the most common explanatory element of risk premium in most asset pricing models, we investigate the impact of the crisis on the time-varying beta of the six sector indices cited. We selected daily data from January 2003 to December 2012 and we applied the bivariate MA-GARCH model (BEKK) to estimate time-varying betas for the sector indices. The crisis was marked by increased volatility of the sector indices and the market. This rise in volatility led to an increase in the systematic risk coefficient during the crisis and first post-crisis period for all the major indices. The results are intuitive and corroborate findings in the empirical literature. The increase of the time-varying beta is considered by investors as an additional risk. Therefore, as expected, investors tend to increase their equity premiums to b ear the impact of financial crisis.

Abstract

The aim of this paper is to investigate the dynamics of oil price volatility by examining interactions between the oil market and the US dollar/euro exchange rate. Unlike previous related studies that focus on low frequency data and GARCH volatility measures, we use recent intraday data to measure realised volatility and to investigate the instantaneous intraday linkages between different types and proxies of oil price and US$/euro volatilities. We specify the drivers of oil price volatility through a focus on extreme US$ exchange rate movements (intraday jumps). Accordingly, we find a negative relationship between the US dollar/euro and oil returns, indicating that a US$ appreciation decreases oil price. Second, we note the presence of a volatility spillover from the US exchange market to the oil market. Interestingly, this spillover effect seems to occur through intraday jumps that take place simultaneously in both markets.

Abstract

Using an asymmetric dynamic conditional correlations (ADCC) generalised auto-regressive conditional heteroskedacity (GARCH) framework, the present study explores the possible contagion effects between financial and the fine wines markets during the period of 2003 to 2014. Our results are manifold. Firstly, we demonstrate that the different wine indices are not affected in the same way by financial market volatility. Secondly, it seems that the choice of the financial index selected strongly influences the identification of the contagion effects. Thirdly, we emphasise a proximity or regional effect mediating the contagion transmission of financial market volatility to fine wines indices. Finally, our study reinforces the possible alternative asset nature of fine wines.

Abstract

This paper focuses on oil market dynamics through the investigation of oil systematic risk and oil risk premium dynamics over the period 1997-2012, which includes several different economic episodes, enabling us to capture a considerable number of statistical properties for oil prices. Interestingly, unlike previous studies, the authors retained data for several developed and emerging oil markets and used different oil prices in order to provide a comprehensive and wide-ranging vision of oil price dynamics. To this end and in order to take eventual time variation and asymmetry in oil price dynamics into account, the authors applied recent econometrics tests associated with the ADCC-GARCH class of model. This modelling enabled us to appropriately specify the dynamics of oil conditional variance and time-varying oil risk premium. Accordingly, this study offers three interesting findings. First, the hypotheses of asymmetry and time variation in oil risk premia are not rejected. Second, the recent global financial crisis has increased systematic oil risk and oil risk premia in different regions. Finally, oil risk premia in emerging countries are significantly higher than those in developed countries, suggesting the inclusion of additional premium induced by political instability and geopolitical changes in emerging economies.

The aim of this study is to investigate the relationship between the financial and the real business cycles in the US over the period February 1987 – March 2016. Using different monthly time-series as proxies for financial and macroeconomic cycles, we, first, specify driving factors and propose two indicators to measure financial and real business cycles, using the methodology of Principal Component Analysis (PCA). Interestingly, we identify not only the main different cycles for each indicators, but also, we measure the duration of phases for each indicator. Second, we investigate the connectedness between the two economic and financial indicators per cycle and per phase. Our findings show that further evidence of significant connectedness between the financial and economic cycles that is actively stronger during the phase “Expansion-Growth”.

Abstract

Originality/value of paper – We show in this chapter that it is possible to choose variable multiples for the CPPI method if quantile hedging is used and in the case of dependent log returns. Upper bounds can be calculated for each level of probability and according to state variables. This new multiple can be determined according to the distributions of the risky asset log return and volatility.