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Donald Trump's use of Twitter was unprecedented. Despite his erratic communication style, some of Trump's strong statements were made in reference to the U.S. oil & gas industry, in line with his domestic policy agenda aimed at supporting re-industrialization and local investment. Did his Twitter messages actually reach domestic oil producers, refiners and transport operators or rather speculators willing to financially gamble on new information sources? To address this question, we model the WTI-Brent spread, which commonly reflects supply bottlenecks in the U.S. crude oil sector, using a nonlinear approach that reveals the perverse influence of some of Trump's tweets particularly on market speculative dynamics. Finally, we outline policy recommendations to counteract the market consequences of speculative behaviour driven by political noise.

International audience; Bitcoin is a cryptocurrency that stores transaction records in a public distributed ledger called the blockchain. All transactions that occurred since the beginning of Bitcoin in 2009 can therefore be consulted by anyone. This unique dataset allows us to study financial transaction networks among pseudonymous participants. Several works analyzed static transaction networks but did not consider the flow of money over the time. In this work, we focus on the analysis of flows, a challenging task given the scale of the data (hundreds of millions of transactions).We propose a method based on taint analysis to track Bitcoin money flow from initial starting points to the dissolution of the taint. The algorithm derives the dynamics subgraphs passing through known entities in the transaction network. We study the pattern of money flowing from different starting points: we taint coins minted by different mining pools in one day period between 2013 and 2016, and use graph embeddings from three representations of the data: (1) static network, (2) dynamic network, and (3) money flow pattern tree. Both qualitative and quantitative analysis show that mining pools have different diffusion patterns and that those patterns evolve over time. Based on this initial result, we are developing a method to select critical entities and expand our unsupervised approach to characterize other money flow patterns, in particular, related to illegal and cybercrime activities.

International audience; Bitcoin is the first and highest valued cryptocurrency that stores transactions in a publicly distributed ledger called the blockchain. Understanding the activity and behavior of Bitcoin actors is a crucial research topic as they are pseudonymous in the transaction network. In this article, we propose a method based on taint analysis to extract taint flows-dynamic networks representing the sequence of Bitcoins transferred from an initial source to other actors until dissolution. Then, we apply graph embedding methods to characterize taint flows. We evaluate our embedding method with taint flows from top mining pools and show that it can classify mining pools with high accuracy. We also found that taint flows from the same period show high similarity. Our work proves that tracing the money flows can be a promising approach to classifying source actors and characterizing different money flow patterns.

International audience; To cope with the weakened financial system, the innovative ecosystem of cryptocurrencies and the blockchain seem to emerge as alternative solutions. While they offer a decentralized governance, cryptocurrencies also provide exposure to social dimensions. We thus pose the following research question: is there a virtuous circle between extra-financial and financial performance for cryptocurrencies? To answer this question, we analyze the social performance, an extra-financial dimension, through miners’ compensation. Using a sample of cryptocurrencies between 2015 and 2021, we follow two econometric modeling approaches, namely portfolios constituted based on miner compensation and a panel regression model. This dual approach allows an analysis of the relationship at the macro and microeconomic level as well as enhancing the robustness of our inferences. Our results show that the social and financial performance relationship is positive. Thus, enhanced value sharing in the cryptocurrency landscape appears synonymous of greater financial performance.; Pour faire face au système financier fragilisé, l’écosystème innovant des cryptomonnaies et de la blockchain semble être une alternative. En plusd’une gouvernance décentralisée, les cryptomonnaies offrent une exposition aux dimensions sociales. Nous posons ainsi la question suivante :existe-t-il un cercle vertueux entre performance extra-financière et financière pour les cryptomonnaies ? Nous analysons ainsi la performancesociale, une dimension extra-financière, à travers la rémunération des mineurs. En utilisant un échantillon de cryptomonnaies entre 2015et 2021, nous réalisons une analyse de portefeuille constitué en fonction de la rémunération des mineurs et utilisons un modèle en données de panel.Cette double approche permet d’étudier la relation à l’échelle macro et microéconomique, renforçant la robustesse des inférences. Nos résultats montrent que la relation performance sociale et boursière est positive. Ainsi, un partage de la valeur ajoutée accrue pour une cryptomonnaiesemble être synonyme de performance financière plus élevée.

We introduce a framework to infer lead-lag networks between the states of elements of complex systems, determined at different timescales. As such networks encode the causal structure of a system, infering lead-lag networks for many pairs of timescales provides a global picture of the mutual influence between timescales. We apply our method to two trader-resolved FX data sets and document strong and complex asymmetric influence of timescales on the structure of lead-lag networks. Expectedly, this asymmetry extends to trader activity: for institutional clients in our dataset, past activity on timescales longer than 3 hours is more correlated with future activity at shorter timescales than the opposite (Zumbach effect), while a reverse Zumbach effect is found for past timescales shorter than 3 hours; retail clients have a totally different, and much more intricate, structure of asymmetric timescale influence. The causality structures are clearly caused by markedly different behaviors of the two types of traders. Hence, market nanostructure, i.e., market dynamics at the individual trader level, provides an unprecedented insight into the causality structure of financial markets, which is much more complex than previously thought., Comment: 19 pages, 10 figures, 1 table

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.

International audience

International audience; This study investigates whether investor attention to the fossil fuel divestment (FFD) movement is related to the stock returns of firms involved in extracting fossil fuels. We consider three complementary indicators of investor attention to the FFD movement: (1) the US weekly Google Search Volume Index on the topic "fossil fuel divestment," (2) the US weekly media coverage of fossil fuel divestment, and (3) the number of weekly visits to the "fossil fuel divestment" page on Wikipedia. Based on a sample of weekly returns on 1,850 US firms over the period 2012-2020, our econometric estimations report a positive relationship between investor attention to FFD and excess stock returns for US fossil fuel-related firms. Therefore, contrary to what the FFD campaigners might expect, the stigmatization of the fossil fuel industry does not drive down the stock returns on fossil fuel-related firms.

To speak of leximetry in the context of an impact analysis in contract law would consist in applying econometric principles to legal problems in order to empirically test different provisions and to interpret their understanding by the actors of the economic system. In this context, a general research problem could be formulated: is the reform of contract law a source of clarification or, on the contrary, of incomprehension for legal practitioners with regard to the judicial reading? The aim would be to examine the underlying issues, in particular the understanding of the reform by drafters of contracts, by introducing a quantitative analysis of the number of appeals at first instance on the issues arising from the reform, and its proper application by judges, by reference, for example, to the number of appeals lodged by the parties after referral to the court, as well as to the number of appeals to the Court of Cassation and the number of judgments in favour of, or against, resolution of the dispute. To this end, the present research methodology project aims to introduce to the jurist and the economist, different perspectives of mathematical analysis in Python 3.8, in order to lay the foundations of a new discipline in France, with great potential for the consolidation of legal security and the interpretation in terms of efficiency, of the production of law by the legislator. Table of contents : 1- Fractality of the legal phenomenon and mathematization of practice: an infinitely fragmented and statistically appropriable science ; 1.1- Ambiguity, legal security and statistical modeling: a common paradigm for law and computer science ; 1. 2- From the standardization of a large set of categorical variables to the realization of unbiased indicators of legal effectiveness ; 2- Towards a leximetry methodology for impact analysis of reforms: the example of ordinary least squares regression ; 2.1- Simple linear regression and OLS estimator, analysis of both strengths and limitations ; 2.2- Introduction to multiple regression by gradient descent algorithm .; Parler de leximétrie dans le cadre d'une analyse d'impact en droit des contrats consisterait à appliquer des principes économétriques à des problèmes juridiques afin de tester empiriquement différentes dispositions et d'interpréter leur compréhension par les acteurs du système économique. Dans ce contexte, une problématique générale de recherche pourrait être formulée : la réforme du droit des contrats est-elle une source de clarification ou, au contraire, d'incompréhension pour les praticiens du droit au regard de la lecture judiciaire ? Il s'agirait d'examiner les enjeux sous-jacents, notamment la compréhension de la réforme par les rédacteurs de contrats, en mettant en place une analyse quantitative du nombre de recours en première instance sur les questions issues de la réforme, et de sa bonne application par les juges, en se référant par exemple au nombre de recours formés par les parties après saisine de la juridiction, ainsi qu'au nombre de recours en cassation et au nombre d'arrêts favorables ou défavorables à la résolution du litige. A cette fin, le présent projet de méthodologie de recherche vise à présenter au juriste et à l'économiste, différentes perspectives de l'analyse mathématique en Python 3.8 afin de poser les fondamentaux d’une discipline nouvelle en France et porteuse d’un grand potentiel pour la consolidation de la sécurité juridique et l’interpretation en terme d’efficacité, de la production du droit par le législateur. Table des matières : 1- Fractalité du phénomène juridique et mathématisation de la pratique : une science infiniment fragmentée et statistiquement appropriable ; 1.1- Ambiguïté, sécurité juridique et modélisation statistique : un paradigme commun au droit et à l'informatique ; 1. 2- De la standardisation d'un large ensemble de variables catégorielles à la réalisation d'indicateurs non biaisés d'efficacité juridique ; 2- Vers une méthodologie leximétrique pour l'analyse d'impact des réformes : l'exemple de la régression par moindres carrés ordinaires ; 2.1- Régression linéaire simple et estimateur MCO, analyse des forces et des limites ; 2.2- Introduction à la régression multiple par algorithme de descente de gradient.

International audience; We implement a new framework to mitigate the errors-in-variables (EIV) problem in the estimation of asset pricing models. Considering an international data of portfolio stock returns from 1990 to 2021 widely used in empirical studies, we highlight the importance of the estimation method in time-series regressions. We compare the traditional Ordinary-Least Squares (OLS) method to an alternative estimator based on a Compact Genetic Algorithm (CGA) in the case of the CAPM, three-, and five-factor models. Based on intercepts, betas, adjusted R2 , and the Gibbons, Ross and Shanken (1989) test, we find that the CGA-based method outperforms overall the OLS for the three asset pricing models. In particular, we obtain less statistically significant intercepts, smoother R2 across different portfolios and lower GRS test statistics. Specifically, in line with Roll's critique (1977) on the unobservability of the market portfolio, we reduce the attenuation bias in market risk premium estimates. Moreover, our results are robust to alternative methods such as Instrumental Variables estimated with Generalized-Method of Moments (GMM). Our findings have several empirical and managerial implications related to the estimation of asset pricing models as well as their interpretation as a popular tool in terms of corporate financial decision-making.

This paper proposes a simple economic model describing retirees' use of bequests. The model assumes that retirees need long term care and have preferences regarding the source of this support. Support can either be bought from the market (at a fixed rate) or sourced from within their family and compensated through bequests. When calibrated, the model shows that for individuals to get at least 1h of daily care, they must, independently of their education level, save about 20% of their pension in the early years of their retirement. However, differences in the source of support appear between non educated and educated households. It is indeed much easier to get support from family members in non-educated households compared to educated ones. Those results suggest that non educated households are also less likely to contract financial insurance products for long term care as they can easily leverage informal arrangements (i.e. their family).

This paper proposes a simple economic model describing retirees' use of bequests. The model assumes that retirees need long term care and have preferences regarding the source of this support. Support can either be bought from the market (at a fixed rate) or sourced from within their family and compensated through bequests. When calibrated, the model shows that for individuals to get at least 1h of daily care, they must, independently of their education level, save about 20% of their pension in the early years of their retirement. However, differences in the source of support appear between non educated and educated households. It is indeed much easier to get support from family members in non-educated households compared to educated ones. Those results suggest that non educated households are also less likely to contract financial insurance products for long term care as they can easily leverage informal arrangements (i.e. their family).

This paper models the economic structure of the services provided by wealth management professionals. It offers a view on the transformation of the associated market when new productivity tools (i.e. digital robots) are introduced. Core insights are generated by calibrating the model to data from the French market. Key results are three fold. First, in the case of France, wealth management services are currently limited to individuals with more than 1.5M€ of assets. For those services to be democratized and extended to the entire population, the model suggests that 60%+ of today's activities in the profession must be automated. Second, wealth management services have currently an average cost of 500€ per client. The model then predicts that for every percent of activity automated via the introduction of productivity tools, services prices are reduced by about 4 to 5€. Finally, the model highlights that the introduction of new tools is likely to trigger an increase in demand for wealth management professional over the short run. This holds true until their services gets extended to the general population, point at which, the number of professionals needed will drastically reduce.

International audience; Данъчният анализ и прогнозирането на приходите са от първостепенно значение за гарантиране на жизнеспособността и устойчивостта на фискалната политика. Въпреки това мерките, предприети за ограничаване на разпространението на неотдавнашната пандемия, представляват безпрецедентно предизвикателство за установените модели и подходи. В настоящата статия се предлага модел за прогнозиране на данъчните приходи в България за фискалните години 2020-2022 г., изграден в съответствие с препоръките на Международния валутен фонд върху набор от данни, обхващащ периода между 1995 и 2019 г. По-нататък в изследването се обсъжда действителната надеждност на официалните български прогнози, като тези данни се съпоставят с предварително оценения модел. Количествените резултати от това проучване едновременно потвърждават предполагаемото отрицателно въздействие на пандемията върху данъчните приходи и доказват, че иконометрията може да бъде коригирана, за да се получат последователни прогнози за приходите дори в сравнително неизследвания случай на България, предлагайки нови идеи на създателите на политики и застъпниците.; Tax analysis and forecasting of revenues are of paramount importance to ensure fiscal policy's viability and sustainability. However, the measures taken to contain the spread of the recent pandemic pose an unprecedented challenge to established models and approaches. This paper proposes a model to forecast tax revenues in Bulgaria for the fiscal years 2020-2022 built in accordance with the International Monetary Fund's recommendations on a dataset covering the period between 1995 and 2019. The study further discusses the actual trustworthiness of official Bulgarian forecasts, contrasting those figures with the model previously estimated. This study's quantitative results both confirm the pandemic's assumed negative impact on tax revenues and prove that econometrics can be tweaked to produce consistent revenue forecasts even in the relatively-unexplored case of Bulgaria offering new insights to policymakers and advocates.

The role of financial intermediation has been illustrated in the finance literature. In addition to performing specialized tasks, several theoretical models postulate that they mitigate the costs associated with acquiring information and conducting financial transactions (Benston & Smith, 1976). Moreover, several studies have found that financial intermediation does more than reduce costs. It provides insurance and risk sharing (Allen & Gale, 1997, 2004), stimulates the financing of liquidity needs through credit lines (Holmström & Tirole, 1998), and helps create specialized products (Benston & Smith, 1976). The aim of this article is to describe and understand the economic and social role of intermediation in solidarity finance and present its contribution to economic growth. We first present the conventional theory of financial intermediation. Then, in second place, we discuss the different research works as well as the main empirical results when studying the relationship between financial intermediation and economic growth. Then, we highlight the form and the important place of intermediation in solidarity finance. Finally, we conclude with the study of relational financing in solidarity finance. We adopt the interpretive paradigm, whose aim is to bring out the deep meaning of intermediation in solidarity finance, which is still embryonic in Morocco. However, our work is purely theoretical due to the absence of empirical statistics at the national level., Le rôle de l’intermédiation financière a été illustré dans de nombreuses publications sur la finance. Outre l’exécution de tâches spécialisées, plusieurs modèles théoriques postulent qu’ils atténuent les coûts associés à l’acquisition d’informations et à la conduite de transactions financières (Benston & Smith, 1976). En outre, plusieurs études ont révélé que l’intermédiation financière fait plus que réduire les coûts. Elle prévoit des assurances et le partage des risques (Allen & Gale, 1997, 2004), stimule le financement des besoins de liquidité par des lignes de crédit (Holmström & Tirole, 1998), et aide à la création de produits spécialisés (Benston & Smith, 1976). L’objectif de cet article est de décrire et comprendre le rôle économique et social de l’intermédiation en finance solidaire et présenter sa contribution à la croissance économique. Nous présentons dans un premier lieu la théorie conventionnelle de l’intermédiation financière. Ensuite, dans un deuxième lieu, nous abordons les différents travaux de recherche ainsi que les principaux résultats empiriques lors de l’étude de la relation entre l’intermédiation financière et la croissance économique. Puis, nous mettons en lumière la forme et la place importante de l’intermédiation en finance solidaire. En dernier lieu, nous terminons par l’étude de financement relationnel en cas de finance solidaire. Nous adoptons le paradigme interprétatif, dont le but est de ressortir le sens profond de l’intermédiation en finance solidaire qui reste encore embryonnaire au Maroc. Or, notre travail est purement théorique du fait de l’absence des statistiques empiriques au niveau national.

International audience; Since cryptocurrencies were first created, the related markets have been known for their fluctuations, whether in terms of high volatility or illiquidity. Partially for those reasons, public authorities and regulators around the world have frequently attempted to regulate those markets. We aim in our study to examine whether cryptocurrency traders perceive market regulation in a beneficial way. Using an event study methodology for daily data covering the 2015-2019 period, we assess how regulatory news and events have affected returns in cryptocurrency markets. We further assess whether financial cryptocurrency characteristics and in particular their liquidity can explain cross-sectional variations in cryptocurrency return reactions. The results suggest that events that increase the probability of regulation adoption are associated with negative abnormal returns for the cryptocurrencies concerned. We also find that the magnitude of the return reactions is not the same across all the cryptocurrencies in our sample. We show that investors reacted less negatively for the most illiquid cryptocurrencies and for those that incurred more information asymmetry risk. Finally, we analyze a longer-term effect of regulatory events by studying the performance of cryptocurrencies. The risk-adjusted return in the preevent period is positive and significant, but it appears not to be significantly different from zero in the post-event period.

International audience; In this paper, we propose a new algorithm to estimate all the parameters of a Self Exited Threshold AutoRegressive (SETAR) model from an observed time series. The aim of this algorithm is to relax all the hypotheses concerning the SETAR model for instance, the knowledge (or assumption) of the number of regimes, the switching variables, as well as of the switching function. For this, we reverse the usual framework of SETAR model identification of the previous papers, by first identifying the AR models using array clustering (instead of the switching variables and function) and second the switching conditions (instead of the AR models). The proposed algorithm is a pipeline of well-known algorithms in image/data processing allowing us to deal with the statistical non-stationarity of the observed time series. We pay a special attention on the results of each step over the possible discrepancies over the following step. Since we do not assume any SETAR model property, asymptotical properties of the identification results are difficult to derive. Thus, we validate our approach on several experiment sets. In order to assess the performance of our algorithm, we introduce global metrics and ancillary metrics to validate each step of the proposed algorithm.

We present a dual process diffusion model to examine whether Bitcoin prices behave with jumps attributed to informative signals derived from Twitter and Google Trends. The empirical results indicate that Bitcoin prices are partially driven by a momentum on media attention in social networks, justifying a sentimental appetite for information demand.

L’intensite du monitoring peut varier en fonction du degre de controle et de l’anciennete des actionnaires de controle. Un modele a effets de seuil est utilise dans le cadre de la determination des remunerations des P-DG dans un panel d’entreprises cotees en France. Les resultats montrent que les entreprises peuvent etre considerees comme non controlees en-dessous d’un seuil de 10 % du capital. Au-dessus, trois regimes de controle sont identifies : un controle influent (10 % a 33 %), dominant (33 % a 45 %) et majoritaire (au-dela de 45 %). Pour l’anciennete du controle, le modele identifie un seuil d’environ huit annees apres la prise de controle, distinguant un controle recent d’un controle de long-terme. Les entreprises non controlees ou avec un controle recent ont recours a des contrats dits optimaux pour gerer les conflits d’agence et la retention des talents, tandis que les controles influent et majoritaire monitorent directement et apportent une meilleure gouvernance. Situe a un degre intermediaire, le controle dominant montre des signes d’enracinement.

Ce document de travail analyse l'asymétrie dans la vitesse d'ajustement entre le prix du brut et celui de l'essence en République Démocratique du Congo de 2008 à 2018. Etant donné qu'en économie, le coût marginal du produit augmente à cause du prix de l'input, le producteur devra répercuter cette hausse dans ces prix. Aucune attention particulière n'est portée sur la vitesse de cet ajustement supposé " instantané ". Cependant, nos résultats démontrent qu'il y a une rigidité du prix de l'essence à la baisse de celui prix du brut contrairement à l'effet inverse. Ce qui prouve à suffisance l'inefficacité dans l'administration du prix du carburant terrestre.

We highlight the considerable recent research that investigates how cryptocurrencies have been impacted by COVID-19. We highlight common threads of investigation and consider common findings and conclusions. We also provide suggestions for future research. Additionally, we provide an overview of a recent paper in which we report on a study that applies wavelet methods to daily data of COVID-19 world deaths and daily Bitcoin prices

This study considers the findings of previous research concerning the volatility and correlation transmission between equity and commodity markets and at- tempts to document evidence of contagion between these markets during four crises using the International Capital Asset Pricing Model (ICAPM). We study existence of contagion transmission mechanism between regional equity markets (USA, Western Europe and the BRICS) and sixteen categories of commodities (Crude Oil, Natural Gas, Electricity, Metals, Precious Metals, Agricultural Oils, Chemicals, Feeds, Fibers, Forestry Products, Grains, Live Stocks, Oil Seeds, Seeds, Semi-Conductors, and Softs). We find that while most of the commodities decoupled from the Global financial crisis, the Irish Banking crisis and the European debt crisis, evidence of contagion were detected during the BREXIT.

We investigate the impact of governments’ social distancing measures against the novel coronavirus disease 2019 (COVID-19) as this was reflected on 45 major stock market indices. We find evidence of negative direct and indirect (spillover) effects for the initial period of containment measures (lockdown)., Highlights • We examine direct and indirect effects of the COVID-19 social distancing measures. • We employ spatial econometrics. • Stock market returns and the intensity of lockdown are negatively related. • We find negative direct and indirect (spillover) effects.

In this paper, we investigate the relationship between output volatility and growth using the standard GARCH-M framework and the US monthly industrial production index (IPI) for the period January 1919–December 2017, by taking into account the presence of shocks and variance changes. The results show that the IPI growth is strongly affected by large shocks which are associated with strikes in some industries, recessions, World War II and natural disasters. We also identify several subperiods with different level of volatility where the volatility declines along the subperiods, with the pre-WWII period (1919–1946) the highest volatile period and the aftermath period of the GFC (2010–2017) the lowest volatile period. We find no evidence of relationship between output volatility and its growth during the full sample 1919–2017 and also for all the subperiods. From a macroeconomic point of view, this implies that economic performances, as measured by IPI growth, do not depend on the uncertainty as measured by IPI volatility.

Displacing labor off/near-shore has historically been the subject of many debates in the context of manufacturing firms. But it is not until recently that it has also started to be used as an instrument to improve competitivity in the realm of services. The management consulting industry is one of the many places where such transformation is underway. It is, however, common knowledge that off/near-shoring activities is difficult. Available benchmarks indeed state that only one out of two firms get some benefits out of the associated changes and it is known that one of the major derailleurs for this kind of evolution revolves around the willingness of their workers to embrace the change. For management consulting practices, the topic if very much on the table as they potentially can standardize and displace labor massively to reduce production costs (up to 50% of production activities can be done remotely). This therefore raises questions on the ability of such firms to provide incentives for their workers (i.e. what does it mean for one’s career? For one’s earnings? etc.). This paper therefore offers a career model that can be used by such firms to assess what off/near-shoring entails for local consultants. Once calibrated to US data, it notably shows that displacing labor simply delays consultants’ earnings until the final stage of their career (i.e. when they make it to partner) and also reduces the risk they bear when entering the industry (i.e. they become more likely to be promoted and therefore can yield higher revenue over time). The tradeoff is of course that if partners compensation increases up to 20%, consultants’ wages decrease by 200 to 500 US$ per year for every percent of work displaced. If the model shows how consultants can benefit from off/near-shoring, it also stresses that their compensation and career are primarily linked to the partnership structure of the firm they join. Consultants’ careers are indeed mainly about becoming the successor for an existing partner. Such that, for every percent of increase in succession chances, consultants’ wages decrease by 2–3 k$ per year. As a result, consultants’ career & compensation are much more impacted by the shape of the partnership one may join than by the partnership choices when it comes to off/near-shoring work. To the point, that under certain circumstances (i.e. firms where succession is very likely), the partnership structure even rules out competitive costs’ advantages presented by other geographies.

International audience; We aim to advance our understanding of the adverse effects of extreme temperatures by examining the extent to which high temperatures affect stock market activity. We address this question by analyzing the trading volumes on the French stock market on days when the weather in Paris is excessively hot over the period 1995-2019. Our empirical analyses show that, on average, trading volumes fall significantly (between 4 percent and 10 percent) when maximum daily temperatures exceed 30°C (86°F). The observed negative association is remarkably robust to a battery of alternative analyses such as bin tests, event studies, and time-series regressions controlling for any seasonal effects and financial market conditions. From a theoretical perspective, this study contributes to the literature on behavioral finance by demonstrating the existence of a "hot weather" effect on financial markets. It also offers important managerial and public policy implications.

International audience; This study examines the relationship between corporate greenwashing and product market competition (PMC). Using an unbalanced panel of 324 US firms over the 2005-2015 period, we find that the negative impact of PMC on greenwashing is conditional on the level of environmental costs. Our results suggest that PMC is an effective disciplinary mechanism for achieving economic efficiency --in the case of firms featuring a high level of environmental costs-- through an increase in the disclosure of reliable and material information.

It has been widely documented in the literature that financial development drives up the impact of CO2 emissions through increases in real economic activities and the consumption of polluting fossil fuel energy. However, when dealing with stock market development, such upward effects on economic growth, energy efficiency, and carbon emissions seems to give away to a positive impact especially in emerging markets. This paper contributes to this debate by exploring both the symmetric and asymmetric responses of CO2 emission to changes in stock market development indicators. In particular, using both the panel linear and nonlinear ARDL, our results demonstrate the asymmetric effects of stock market development indicators on carbon emissions in the context of emerging markets. In particular, the long-run elasticities results suggest that positive and negative shocks on stock market indicator decreases environ- mental quality by increasing carbon emissions. Based on these empirical findings, this study offers some crucial policy implications

This article seeks to highlight in more depth the public levers of action in the implementation of anti- corruption policies within the countries among the Central Africa region. Using non-supervised statistical method, we first study the profile of the countries concerned (institutional, social, entrepreneurial, etc.), then secondly, we analyze the impact of public measures on the extent of corruption at the national level. We manage to demonstrate that there is a common and standard sub-regional political program intended for public decision-makers, regardless of the degree of heterogeneity of national structures.

In this paper a hybrid model is investigated to capture both financial behaviors of an asset: (i) the leverage effect and (ii) the stochastic volatility component. For this we consider a hybrid model that takes the strengths of the Heston and the CEV models. The pricing of European options is investigated both theoretically and empirically. A decomposition formula that allows to estimate the option price is obtained. Moreover, numerical simulations of the asset price are done to give a better and concrete vision of the adding of this approach. In addition, the price of a European call option under the hybrid model is computed using the Monte Carlo method and our formula. Illustrations and tables show the efficiency of the numerical method based on our approximate formula.

This paper reviews eight software packages when estimating asymmetric GARCH models (from their default option). We consider the numerical consistency of GJR-GARCH, TGARCH, EGARCH and APARCH estimations with Normal and Student distributions as well as out-of-sample forecasting accuracy, using the model confidence set procedure. We show that results are clearly software-dependent for both asymmetric volatility models, especially for the t-ratios. The out-of-sample forecast results show that the differences in estimating symmetric and asymmetric GARCH models imply slight differences in terms of forecast accuracy, not statistically significant, except in few cases from the QLIKE loss function. Further, the results indicate that the different specifications of the asymmetric GARCH-type models used by the different packages appear to have no significant effect on their forecast accuracy.

Purpose This study aims to empirically investigate the effects of labor displacement on US management consulting (MC) firms. Design/methodology/approach This paper leverages standard linear regressions to identify and discuss correlations between progresses made in terms of labor displacement and the evolution of MC firms performance indicators. Findings In the context of US MC practices, the study shows that for every percent of work displaced, production costs are reduced by $3.7/h on average. It also highlights that as prices also go down by $3.3/h on average per percent of work displaced, off/near-shoring increases MC practices profitability. Displacing labor is yet a transformation that occurs mainly in very large firms (i.e. more than 1,000+ employees) and its full potential takes more than 4–5 years to realize. Originality/value This study provides new empirical benchmarks of the effect of labor displacement on MC firms. This study shows how long off/near-shoring takes to reach its full maturity.

In this paper, we define stochastic volatility operators in Hilbert space which are analogs to the widely-used SABR model [14] in finite dimensional case. We show the existence of the mild solution and some related regularity properties. Our proof is based on Leray-Schauder fixed point theorem and some priori inequalities on the stochastic operator processes we construct.

In this paper, we introduce a new time series model having a stochastic exponential tail. This model is constructed based on the Normal Tempered Stable distribution with a time-varying parameter. The model captures the stochastic exponential tail, which generates the volatility smile effect and volatility term structure in option pricing. Moreover, the model describes the time-varying volatility of volatility. We empirically show the stochastic skewness and stochastic kurtosis by applying the model to analyze S&P 500 index return data. We present the Monte-Carlo simulation technique for the parameter calibration of the model for the S&P 500 option prices. We can see that the stochastic exponential tail makes the model better to analyze the market option prices by the calibration., Kum-Hwan Roh gratefully acknowledges the support of Basic Science Research Program through the National Research Foundation of Korea (NRF) grant funded by the Korea government [Grant No. NRF-2017R1D1A3B03036548]

Financial crises are an important research topic because of their impact on the economy, businesses, and populations. However, prior research tends to generate reactive systemic risk measures, in the sense that the measure surges after the crisis starts. Few of them succeed in warning of financial crises in advance. In this paper, we first sketch a toy model that produces normal mixture distributions based on a dynamic regime switching model. We derive that the relative concavity among various indices tends to increase before a crisis. Using Polymodel theory, we introduce a measure of concavity as a crisis risk indicator, and test it against known crises observed in the past. We validate this indicator by a trading strategy holding long or short positions on the S & P 500 Index, depending on the indicator value.

International audience; The last five decades have witnessed dramatic changes in crude oil price dynamics. We identify the influence of extreme oil shocks and changing oil price uncertainty dynamics associated with economic and political events. Neglecting these features of the data can lead to model misspecification that gives rise to: firstly, an explosive volatility process for oil price uncertainty; and secondly, erroneous output growth dynamic responses to oil shocks. Unlike past studies, our results show that the sharp increase in oil price uncertainty after mid-1985 has a pernicious ed'ect on output growth. There is evidence that output growth responds symmetrically (asymmetrically) to positive and negative shocks in the period when oil price uncertainty is lower (higher) and more (less) persistent before (after) mid-1985. These results highlight the importance of accounting for outliers and volatility breaks in oil price and output growth, and the need to better understand the response of economic activity to oil shocks in the presence of oil price uncertainty. Our results remain qualitatively unchanged with the use of real oil price.

International audience; Au cours des dernières années, l'estimation de la durée de séjour hospitalier (DDS) au moment de l'admission du patient fait l'objet de plusieurs études. La DDS est un indicateur d'évaluation du rendement des établissements de soins et d'efficacité de la performance des services hospitaliers. La prédiction des DDS contribue à l'optimisation des ressources des hôpitaux, à l'amélioration de l'organisation des soins et à une meilleure planification des activités. Dans cette communication, nous exposons la démarche suivie pour implémenter un modèle de prédiction de durées de séjour hospitalier en exploitant des algorithmes d'apprentissage automatique. Pour chaque étape du processus de prédiction, les difficultés rencontrées sont soulevées et discutées. L'implication de l'expertise et son importance dans dans le projet sont également mises en évidence. Finalement, un exemple illustratif utilisant l'ensemble de données « Microsoft for length of stay prediction » est présenté. Mots clés : Durée de séjour hospitalier, exploration de données, apprentissage automatique, modèle de prédiction.

National audience; Dans de nombreux domaines, dans un monde évoluant rapidement, la formation et l'appropriation des futures conditions de travail sont essentielles. Dans ce but, cet article propose un simulateur sur table interactive munie de la technologie RFID, associé à des objets tangibles. Ce simulateur permet à des employés de se projeter dans des situations à venir, dans un cadre pouvant être collectif, autour de la table interactive, relativement à différents scénarios pouvant ensuite être rejoués. Un tel simulateur offre de nombreuses perspectives dans le domaine hospitalier.

International audience; Cet article présente les premières briques du travail réalisé dans le cadre du projet intitulé « Passeport Vasculaire », ainsi que les premiers résultats préliminaires. Ce travail est réalisé conjointement par le service de chirurgie vasculaire du Centre Hospitalier de Valenciennes (CHV) et l'entreprise Alicante. L'objectif est de détecter parmi l'ensemble des patients admis ou pré-admis au CHV le risque de pathologies vasculaires. Pour mener à terme ce projet, l'expertise des chirurgiens du pôle vasculaire du CHV est mise à disposition, ainsi qu'une combinaison de plusieurs techniques d'algorithmique et d'intelligence artificielle (IA). Ces techniques d'IA ont été exploitées pour tirer profit de l'importante masse de données hétérogènes et complémentaires disponibles au CHV.

International audience; Après des années d'hésitation, la Belgique s'engage dans une réforme structurelle de la nomenclature des procédures médicales sur base d'un plan proposé par le Département d'Economie de la santé de l'ULB (DESULB). L'Institut National Maladie Invalidité (INAMI) coordonne la 1 ère phase de la réforme visant à la modernisation du volet descriptif de la nomenclature afin de disposer d'une classification de libellés standardisés et précis. La mise en oeuvre des différentes étapes de la méthodologie pourrait intéresser d'autres pays confrontés à des défis similaires. Elle fait l'objet de différentes communications dont celle consacrée au travail de validation médicale.

International audience; La fragilité cognitive est un syndrome qui touche de plus en plus de personnes âgées. Elle se caractérise notamment par un changement de comportement et une qualité du sommeil altérée. L'analyse de cette dernière est généralement obtenue à l'aide d'un dispositif intrusif et ne peut donc pas être utilisé dans le cadre du suivi de l'évolution au quotidien. Nous proposons dans ce travail une nouvelle méthode d'analyse du sommeil à partir des données collectées de manière non intrusive par l'intermédiaire d'un lit connecté, permettant ainsi d'évaluer l'évolution du niveau de fragilité cognitive. Mots clés : Fragilité cognitive, Analyse de la qualité du sommeil, capteurs.

International audience; Cet article présente une étude qualitative exploratoire des différentes dimensions de la performance telles que perçues par les acteurs internes de l'hôpital public marocain. C'est le résultat d'une enquête menée auprès des cadres des hôpitaux marocaines sur les dimensions et le concept de la performance. Nous avons emprunté le modèle de [Sicotte et al.,1998], qui repose sur la théorie de l'action sociale de [Parsons,1951]. Les données collectées via un questionnaire ont été traitées via une analyse en composantes principales, ensuite une analyse de régression pour tester les relations entre les dimensions de la performance. Les résultats obtenus confirment que la performance est un concept multidimensionnel. La comparaison entre les opinions des acteurs nous montre qu'il y a des points d'ententes, mais aussi des divergences en ce qui concerne ce qu'est un hôpital performant.

International audience; Dans un contexte de vieillissement de la population, l'évaluation et le suivi des patients âgés participent aux objectifs de prévention gériatrique, à savoir l'allongement de la durée de vie sans incapacité et la préservation de l'autonomie. L'évaluation gériatrique standardisée (EGS) est un instrument de diagnostic multidimensionnel et pluridisciplinaire qui permet de proposer des soins personnalisés aux personnes âgées, sur la base de l'évaluation de leur état de santé. Cette évaluation repose sur une vaste collecte de données portant sur les incapacités médicales, psychosociales et fonctionnelles de la personne âgée fragile, afin d'élaborer un plan coordonné favorisant un vieillissement en bonne santé. Cependant, faute de moyens suffisants, une part importante de population âgée fragile n'est aujourd'hui pas prise en charge, ou insuffisamment. L'hypothèse de recherche est qu'une solution robotique permettrait un gain d'efficacité dans le suivi gériatrique, permettant ainsi le repérage et le suivi d'un plus grand nombre de personnes âgées. Résultat de 3 années de recherche, Clara est aujourd'hui un robot assistant gériatrique opérationnel de niveau TRL 8. Cet article présente l'évaluation pilote qui a été menée en situation réelle d'usage entre mai et juillet 2019, dans le cadre d'une convention cadre de partenariat entre les établissements dont sont issus les auteurs.

International audience; Au cours des dernières années, les besoins en soins d'urgences ont considérablement augmenté dans les services des urgences (SU). La gestion du flux de patients est l'un des principaux défis auxquels sont confrontés de nombreux SU. À cet égard, il est essentiel de prédire les demandes de soins afin de mieux adapter les ressources aux demandes de soins et d'atténuer les problèmes de surpopulation dans ces établissements. Les modèles de régression et de série chronologique existants, sont principalement des modèles linéaires et ne peuvent pas décrire la nature stochastique et non linéaire des données. Les approches basées sur l'apprentissage par réseaux de neurones sont considérées comme une nouvelle alternative pour la prévision dans divers domaines. Cet article présente une approche d'apprentissage par réseaux de neurones profonds basée sur le modèle GRU (Gated Recurrent Unit) pour prédire les demandes de soins dans un SU. Les données issues du service des urgences pédiatriques (SUP) du centre hospitalier régional de Lille (CHRU), sont utilisées pour tester et valider l'approche proposée. Les résultats montrent une bonne performance de prévision des admissions au SUP.

International audience; Dans cet article, nous abordons le problème de livraison des produits médicaux nécessaires pour une hémodialyse (HD) à domicile. Les patients de cette modalité de dialyse sont généralement contraints par leur capacité de stockage très limitée. L'objectif de ce travail est d'optimiser, à la fois, la fréquence de livraison de ces produits et le coût des livraisons. Nous proposons une modélisation linéaire de notre problématique qui présente des similarités avec une classe de problème très connue dans la littérature sous l'abréviation PVRPTW (problème de tournée de véhicule périodique avec fenêtres de temps). Pour valider le modèle, un exemple illustratif a été présenté et plusieurs scénarios ont été simulés.

International audience; Les structures de soins infirmiers à domicile sont réglementé par un nombre de places accordés chaque année qui est proportionnel au budget de fonctionnement alloué à la structure. Cette étude évalue différentes stratégies d'admission avec une prise en compte des charges de travail et des coûts associés à chaque usager en fonction de son plan de soin. Il en ressort que les coûts d'exploitation peuvent être fortement optimisés au détriment de l'équité de l'accès aux soins, notamment pour les usagers nécessitant le plus de soins en durée globale mais pas en lourdeur des actes techniques.

National audience; The public transport attempts to provide a service to every citizen on the same level of approachability. Even when the budget allows investments to upgrade the transport facilities accessibility, it would be necessary to deal with the time and transport organization. The research problem that has been treated here is the variant of the possible models applicable to the transport of persons with disabilities on the existing transport network by providing independence in their displacement. The literature recognizes several optimization models that could assist in delivering better transport services to persons with disabilities, such as transport on demand (also knows as dial-a-ride model), and another category is the model that proposes the shortest path on the network. In this paper, the conditions of the public transport network in Valenciennes (France) are analyzed within the transport flows and explained the best fitting with the optimization and location models.

International audience; Avec l'avènement du digital et des technologies associées visant la transformation des pratiques et des usages en liaison avec le domaine de la santé en général et le parcours des soins en particulier, le patient est désormais au centre de tout système de soins moderne et souvent suivi par plusieurs professionnels de santé et dans des lieux multiples. Dans le cadre de ce papier, nous traitons de l'aspect important relatif à l'eXpérience Patient (XP), en prenant comme contexte l'utilisateur en situation de handicap. Nous proposons un cadre méthodologique considérant l'eXpérience Patient suivant l'approche de design thinking visant le développement et la livraison de services numériques accessibles au sens de WCAG2 et AccessiWeb.

International audience; Les travaux sur la résilience en milieu professionnel se sont principalement concentrés sur la résilience au niveau individuel. Or, dans les organisations de santé les individus ne travaillent pas en vase clos ce niveau d’analyse est donc insuffisant pour capter, d’une part, toute la complexité des interactions et des interdépendances, et d’autre part, comprendre les processus au sein de l’équipe qui conduisent à la gestion des événements incertains et à risque. Cet article s’attache à explorer et à produire des connaissances fines et plus approfondies sur la manière dont la résilience de l'équipe se développe et se déploie. Ensuite, nous identifions les ressources qui rendent une équipe résiliente, nous explorons également les activités au travers desquelles ces ressources sont investies.