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International audience; The contribution of this paper is threefold: first, it introduces a new geopolitical risk index that incorporates recent geopolitical events ignored in Caldara and Iacoviello (2018)’s index. In addition to war threats and acts, terrorist threats and acts and nuclear threats, the new indicator accounts for global trade tensions, the changing fundamentals of U.S.-China relations, the escalated U.S.-Iran conflict, Saudi Arabia’s uncertainty, Venezuela’s crisis, and OPEC news that rise in response to important OPEC meetings and events connected with OPEC production levels. Second, it addresses how the volatility of six oil prices (the Nigerian Bonny Light, Brent, Dubai, OPEC, Tapis, and WTI) behave when the developed geopolitical risk index unexpectedly changes. Third, it examines whether OPEC maintains a buffer of spare capacity that it uses to respond to potential crises that reduce oil supplies. We show that an increase in the geopolitical risk index is significantly associated with unanticipated oil price changes, though with varying sensitivities. Our findings also reveal that OPEC’s use of spare capacity reduces the reaction of oil price to geopolitical risks but moderately, thus suggesting a limited stabilizing influence on the oil market. The limited amount of spare production capacity leaves the oil market on a knife’s edge as it deals with a host of potential supply disruptions stemming from geopolitical issues.

International audience; While most of the debates about cryptocurrencies are centered on the global Bitcoin market, in thisarticle, we focus on local Bitcoin trading volume in 21 emerging countries. In particular, we attempt todetermine the drivers of Bitcoin trading volume in these countries over the period August 1st, 2015 – June2nd, 2018. Based on VECM and ARDL models, we find evidence of significant relationship between thelocal Bitcoin trading volume in each country and the associated banking system access, especially in theshort-run. Moreover, altcoins (Ethereum, Ripple) prices are shown to affect positively and significantlythe local Bitcoin trading volume for most countries in the long-run (VECM results) and the short-run (ARDL results).

International audience; Gold is considered as a hedge against inflation, it offers an opportunity for portfolio diversification. This paper examines the recent evolution of seasonal anomalies in the Chinese Gold market. It studies the day of the week effect and the monthly effect through gold prices at the Shanghai Gold Exchange (SGE) over the 2002 to 2016 period. We investigate seasonal patterns in economically favorable times and unfavorable times by using a UCM model and an ARCH model. The reforms in regulations have rendered the Chinese financial market more efficient, in such cases; we expect an alteration in seasonal anomalies in the Chinese Gold market. However, it would seem that seasonality does exist in the Chinese Gold Market. The Monday returns have been positive and the Tuesday returns have been negative for the whole period. We also highlight that January and February generate the best returns. The return in the middle of the year is negative. This paper contributes to the existing finance literature by investigating the anomalies during the recent period. Although in the Chinese stock market, the seasonal anomalies persist, the index may be efficient despite the regularity in price formation, in this case, a study over a more recent period is necessary.

The Fama-French (FF) five-factor model is cast into a dynamic setting to capture the impact of illiquidity over the phases of the business cycle on the returns of the passive FF twelve sector portfolios. We use two dynamic approaches, Kalman filtering and a recursive/rolling robust instrumental variables (IV) algorithm cast into a GMM framework, to determine time-varying alpha and beta estimates. Our principal result is that the Kalman filter approach supports the hypothesis that illiquidity is an important risk factor in a dynamic context. However, the only factor found to matter in the dynamic GMM approach is the market risk premium. Nevertheless, illiquidity may be prescient with respect to financial crises. Keywords: Illiquidity, Fama-French five-factor model, Kalman filter, Robust IV algorithm, JEL Classification: C58, G12

International audience; We examine if women on corporate boards (WOCB) influence a firm's corporate social performance (CSP). To do this, we utilize stakeholder theory. From an empirical standpoint, we use the control function (CF) approach suggested by Wooldridge (2015), which takes into account the issue of endogeneity raised in the literature (namely, omitted variables, reverse causality, and dynamic endogeneity). Using a sample of firms from the S&P 500 between 2004 and 2015, we find that WOCB have a positive and significant effect (at the 5% level) on CSP. We compare our results to more traditional approaches (pooled OLS, the fixed-effects model, and system GMM). We shed light on an issue that is still considered controversial (Byron and Post, 2016).

International audience; The aim of this paper is to analyze the dynamic evolution of six liquidity proxies ontime, and to find their causality with the French CAC 40 stock market index returns, overthe period from January 2007 to December 2018. For that, we use a vector autoregressiveapproach and the impulse response function, to do causality test between the CAC 40 index returns and six differents liquidity proxies. Empirical results suggest a significantshort-term relationship between the returns and the liquidity. As for Granger’s causalitytest, the results reveal that there is unidirectional causality running from equity returnsto liquidity.

This paper extends the work of Pindyck, R. S. 2012. “Uncertain Outcomes and Climate Change Policy.” Journal of Environmental Economics and Management 63 (3): 289–303. by taking into consideration a large class of different utility functions of economic agents. As in Pindyck, R. S. 2012. “Uncertain Outcomes and Climate Change Policy.” Journal of Environmental Economics and Management 63 (3): 289–303, instead of considering a social utility function that is characterized by constant relative risk aversion (C.R.R.A), we use the expo-power utility function of Saha, A. 1993. “Expo-power Utility: A ‘Flexible’ Form for Absolute and Relative Risk Aversion.” American Journal of Agricultural Economics 75 (4): 905–13. In fact, depending on the choice of the expo-power utility function parameters, we cover a diverse range of utility functions. Apart from covering the other utility functions that a C.R.R.A omits, the Expo-power utility function permits us to discern if under the other utility-regimes of economic agents, the willingness to pay remains more affected by uncertain outcomes than certain outcomes when we vary the expectation and standard deviation of the temperature’s probability distribution. Our paper has maintained the small-tailed gamma distributions of temperature and economic impact of Pindyck, R. S. 2012. “Uncertain Outcomes and Climate Change Policy.” Journal of Environmental Economics and Management 63 (3): 289–303. not only because they hinder infinite future welfare losses (for an exponential utility function), but because it is easy to change some moments of the distribution (jointly or holding the others fixed) while studying how uncertainty influences the willingness to pay as explained in Pindyck, R. S. 2012. “Uncertain Outcomes and Climate Change Policy.” Journal of Environmental Economics and Management 63 (3): 289–303.

International audience; Using an affine model to compute the price of equities based on a dataset of macroeconomic factors, we propose a measure of equity bubbles. We use a dynamic affine term structure framework to price equity and bonds jointly, and investigate how prices are related to a set of macrofactors extracted from a large dataset of economic time series. We analyze the discrepancies between market and model implied equity prices and use them as a measure for bubbles. A bubble is diagnosed over a given period whenever the discrepancies are not stationary and impact the underlying economy consistently with the literature’s findings, increasing over the shorter term economic activity before leading to a net loss in it. We perform the analysis over 3 major US and 3 major European equity indices over the 1990–2017 period and find bubbles only for two of the US equity indices, the S&P500 and the Dow Jones. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

International audience; This paper assesses the impact of low-carbon policy on stock returns by means of an environmental extension of Fama and French's (2015) five factor model. This paper makes four major contributions. Firstly, for the first time a factor, GMC (green minus carbon), meant to provide the premium which results from not paying a carbon price is constructed. The GMC factor is obtained by means of a sample of 182 firms from 19 European countries operating in 35 sectors: from January 2008 to December 2018 the value-weight returns of 91 firms regulated by the 2003/87/CE directive are subtracted from the value-weight returns of 91 firms exempted by the 2003/87/CE directive upon which the EU-ETS is based. Secondly, we provide evidence that the addition of the GMC factor improves the performance of the 5 factor model in Europe in the 2008-2018 time span. Thirdly, results show that there is a high green premium rather than a carbon premium as it was asserted by parts of the literature, and that this green premium is highly statistically significant. Fourthly, after performing a carbon stress test, we show the effects of EU-ETS average price shocks on both carbon and green firms for each market cap tranche.

International audience; In a first step, we model the multivariate tail dependence structure and spillover effects across energy commodities such as crude oil, natural gas, ethanol, heating oil, coal and gasoline using canonical vine (C-vine) copula and c-vine conditional Value-at-Risk (CoVaR). In the second step, we formulate portfolio strategies based on different performance measures to analyze the risk reduction and diversification potential of carbon assets for energy commodities. We identify greater exposure to losses arising from investments in heating oil and ethanol markets. We also find evidence of carbon asset providing diversification benefits to energy commodity investments. These findings motivate for regulatory adjustments in the trading and emission permits for the energy markets most strongly diversified by carbon assets.

International audience; This study characterizes the oil market as a nonlinear-switching phenomenon and examines its dynamics in response to changes in geopolitical risks over low- and high-risk scenarios. We separate the shocks due to geopolitical acts from those due to geopolitical threats to address whether the serious effects of geopolitical risks are mostly due to increased threats of adverse events or to their realization as acts. While we find the acts to generate a positive and strong impact on oil price dynamics, the effect of threats appears to be moderate or non-significant. Imperfect information in the oil price determination, the history of oil supply disruptions emanating from geopolitical events, the continued rise in populism in the world, oil market volatility, multifractility and the time-varying degree of weak-form efficiency have been advanced to explain the unforeseen responses of oil prices to geopolitical threats. To accommodate recent oil-related events, we construct a composite geopolitical risk indicator by accounting for contemporaneous sources of geopolitical risks, namely global trade tensions, US-China relation risks, US-Iran tensions, Saudi Arabia’s uncertainty and Venezuela’s crisis. The combined effects have an outsized impact on oil prices.

CNRS 4, FNEGE 3, HCERES B, ABS 3; International audience; This paper focuses on the linkage between equity prices and fundamentals for 27 individual shares belonging to the French stock price index (CAC40). To assess fundamental value, the traditional Dividend Discount Model (DDM) is coupled with the Arbitrage Pricing Theory (APT), which assumes that investors hold efficient portfolios. This yields a simple equity valuation relationship for which the APT determines the long-term risk premium included in the DDM. Accordingly, equity risk premia are determined by common factors reflecting the non diversifiable risk. These factors are not a priori identified by the theory, and therefore must be exhibited through an empirical analysis. Four domestic and three international common factors are found, all being among those identified by empirical analyses of the APT in the literature. While studies related to stock price indices showed that DDM fundamental values are very smooth compared to stock indices, our DDM-APT model reproduces both trends and major fluctuations of share prices. Further, as for studies based on stock indices, a mean-reverting process of equity prices towards fundamentals is highlighted, but the linear Error Correction Model (ECM) that was considered contains shortcomings suggesting a more complex adjustment process.

International audience; This article empirically investigates the impact of renewable production on congestion using a unique database on the Italian Power Market, where zonal pricing is implemented. We estimate two econometric models: a multinomial logit model, to assess whether renewables increase the occurrence of congestion, and a two stage least squares (2SLS) model to evaluate the impact of wind and photovoltaics on congestion costs. Our analysis suggests that larger renewable supply in importing regions decreases the probability of congestion compared to the no congestion case, while the reverse occurs when renewable production is located in an exporting region. The 2SLS estimations reveal that the same mechanisms explain the level of congestion costs. Our results also highlight that the magnitude of the congestion effects, both in terms of probability and costs, is very sensitive to the location of the historical efficient production, mainly hydro power, and to the geographical configuration of the transmission network.

International audience; This study assesses the roles of Bitcoin as a hedge, a safe haven and/or a diversifier against extreme oil price movements, in comparison to the corresponding roles of gold. We use a quantile-on-quantile regression approach to capture the dependence structure between the considered market returns under different Bitcoin market conditions, while considering nuances of oil price movements, compared to gold. Our findings show that both Bitcoin and gold would serve the roles of a hedge, a safe haven and a diversifier for oil price movements. However, this property seems to be sensitive to the Bitcoin's and gold's different (bear, normal or bull) market conditions and to whether the oil price is in a downside, normal or upside regime. By controlling for new and relevant U.S. and global uncertainty indicators, we confirm that both Bitcoin and gold, but not oil, are assets where investors may park their cash during times of political and economic turmoil. The conditional Value-at-Risk (CoVaR) approach to risk management is then conducted, providing robust evidence of the usefulness of each of the Bitcoin and gold in expanded oil portfolios, in terms of diversification opportunities and downside risk reductions.

International audience; Dans cet article, nous nous proposons de tester une extension du modèle d’évaluation des actifs financiers (MEDAF), dans lequel nous ajoutons un facteur de risque systémique, mesuré par une agrégation des principales mesures de risques systémiques, comme proposée récemment par différents auteurs, dans le cadre d’une analyse en composantes principales parcimonieuse (ACPP). Il ressort de nos analyses empiriques menées sur le marché américain que le risque systémique est effectivement une composante importante de la rémunération sur certains titres. Nous proposons finalement une application originale servant à l’identification et au classement des institutions financières d’importance systémique (IFIS).

International audience; The paper applies an event study methodologyaims to investigate the macroeconomic announcements effects on Standard&Poor’s500 and oil prices. Our results provide evidence for a significant impact of the US macroeconomic news on oil prices. This impact is split into two components, namely the direct effect (common response) and indirect effect (volatility transmission). Altogether our results show that the volatility transmission is bidirectional. Not only a significant volatility transmission from the oil market to the US stock market is revealed, but also a high volatility transmission is recorded from the oil market to the stock market especially after the release of consumption indicators.

International audience; We develop and implement a method for maximum likelihood estimation of a regime-switching stochastic volatility model. Our model uses a continuous time stochastic process for the stock dynamics with the instantaneous variance driven by a Cox-Ingersoll-Ross (CIR) process and each parameter modulated by a hidden Markov chain. We propose an extension of the EM algorithm through the Baum-Welch implementation to estimate our model and filter the hidden state of the Markov chain while using the VIX index to invert the latent volatility state. Using Monte Carlo simulations, we test the convergence of our algorithm and compare it with an approximate likelihood procedure where the volatility state is replaced by the VIX index. We found that our method is more accurate than the approximate procedure. Then, we apply Fourier methods to derive a semi-analytical expression of S&P 500 and VIX option prices, which we calibrate to market data. We show that the model is sufficiently rich to encapsulate important features of the joint dynamics of the stock and the volatility and to consistently fit option market prices.

International audience; This article aims to study the role of gold quoted on the Shanghai Gold Exchange in the diversification of Chinese portfolios using a mean-risk and stochastic dominance analysis. With the 2004–2014 period, our results show that in general, risk-averse investors prefer not to include gold while risk-seeking investors prefer to include it in their stock–bond portfolios, especially in crisis periods. This result is found to be time-varying but not time-frequency dependent and the inclusion of the risk-free asset does not induce relevant impacts. Furthermore, risk-seekers prefer including gold in an equal-weighted portfolio while risk-averters prefer including gold in efficient portfolios.

International audience; To assess how financial markets and commodities are inter-related, this paper introduces a ‘volatility surprise’ component into the asymmetric DCC with one exogenous variable (ADCCX) framework. We develop an econometric model in which returns and volatility allow to influence pairs of assets, and derive several case studies linking commodities to stocks, bonds and currencies from 1983 to 2013. The innovative feature of our model is that these volatility spillovers are modeled consistently within the correlation dynamics of the ADCCX model. We find evidence that return and volatility spillovers do exist between commodity and financial markets and that in turn, their relative impact on each other is very substantial.

International audience; This article addresses the issue of measuring the level of aggregate financial stress on stock markets, which is a central issue for investors and policy-makers. To this end, Realized EquiCorrelation (REC) is obtained by plugging realized volatility as an input into the Dynamic EquiCorrelation (DECO) model where both the continuous and jump components of realized volatility are considered. An application is provided for the 20 major stock markets over January 2000–May 2014 using intra-day data. The results remarkably pick up financial stress periods.

In this paper, we propose an alternative approach to estimate long-term risk. Instead of using the static square root method, we use a dynamic approach based on volatility forecasting by non-linear models. We explore the possibility of improving the estimations by different models and distributions. By comparing the estimations of two risk measures, value at risk and expected shortfall, with different models and innovations at short, median and long-term horizon, we find out that the best model varies with the forecasting horizon and the generalized Pareto distribution gives the most conservative estimations with all the models at all the horizons. The empirical results show that the square root method underestimates risk at long horizon and our approach is more competitive for risk estimation at long term., Dans cet article, nous proposons une approche alternative pour estimer le risque à long terme. Au lieu d'utiliser la méthode de la racine carrée, nous proposons une approche dynamique. Nous comparons deux mesures de risques pour différents modèles de séries chronologiques. Nous trouvons que le meilleur modèle varie en fonction de l'horizon de prévision et de la distribution de Pareto généralisée utilisée. Les résultats empiriques montrent que la méthode de la racine carrée sous estime les risques.

International audience; This article proposes a new empirical methodology for computing a cross-market volatility index - coined CMIX - based on the Factor-Dynamic Conditional Correlation (DCC) model, implemented on volatility surprises. This approach solves problems in treating high-dimensional data and estimating time-varying conditional correlations. We provide an application to multi-asset market data composed of equities, bonds, foreign exchange rates and commodities during 1983-2013. This new methodology may be attractive to asset managers, because it provides a simple way to hedge multi-asset portfolios with derivatives contracts written on the CMIX.