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International audience; Exloring the role of different types of investors on stock market is crticial since different types of investors react and behave differently when making investment decision. The role of investor behavior is a very important issue in an immature stock market like Vietnam stock market because the market is characterized by a large number of individual investors and low reporting standard. Institutional and foreign investors however play an influential role due to their large exposure and strong investment expertise. Clearly, examining the role of investor behavior and its impact on the stock market in Vietnam is an important topic in finance. A significant body of empirical research has shown that investor behavior is an essential factor to explain stock price that the classical financial theory cannot explain. This research examines the role of investor behavior in stock market by examining the relationship between investor behavior and stock return using the Vietnamese stock exchange data. We create a sentiment index using the principal components analysis (PCA). Consistent with the sentiment and stock return literature, the research shows a negative contemporaneous relationship between investor sentiment and market return.

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; In this paper, we examine the influence of the daily institutional investor attention to particular stocks on stock volatility and liquidity. The institutional investor attention is measured from the number of times that users of Bloomberg terminal, who are mostly institutional investors, search for or read articles on a specific stock. Relying on a large international dataset of approximately a million daily observations over the period 2011–2020 from nine countries (Canada, France, Germany, Japan, Russia, South Korea, Switzerland, the UK, and the US), we find that this recent measure of institutional investor attention has a strong positive effect on stock volatility and liquidity. Confirmed by a battery of robustness tests, our findings suggest that this continuous barometer of attention by institutional investors can be used by financial practitioners to predict future stock volatility and liquidity.

De nombreuses recherches se sont focalisées sur la relation entre le développement financier et la croissance, d’une part, et sur la relation entre l’intégration financière et le développement économique, d’autre part. Cependant, l’étude du lien entre libéralisation du compte capital et développement financier reste encore limitée, et en particulier pour les pays du Moyen-Orient et d’Afrique du Nord. L’objet de cet article est de proposer une analyse empirique de cette relation dans le cas de la Tunisie, pays qui a fait le choix depuis plusieurs décennies de s’ouvrir progressivement aux capitaux étrangers. L’étude économétrique menée sur la période 1986-2014 en utilisant conjointement un modèle de causalité de long terme Toda-Yamamoto et un modèle ARDL a permis de montrer que l’ouverture du compte capital avait bien un effet positif sur le développement financier en longue période. Ce résultat est robuste à plusieurs spécifications du modèle autorégressif et à des mesures alternatives du développement financier. Néanmoins, l’impact de court terme de l’ouverture du compte capital est plus limité, en particulier lorsqu’on considère les effets sur le marché boursier., Much research has focused on the relationship between financial development and growth, on the one hand, and the relationship between financial integration and economic development, on the other. However, the link between capital account liberalization and financial development remains limited, particularly for the Middle East and North African countries. The purpose of this article is to propose an empirical analysis of this relationship in the case of Tunisia, a country that has chosen for several decades to gradually open up to foreign capital. The econometric study carried out over the period 1986-2014 using a Toda-Yamamoto long-term causality model in conjunction with an ARDL model showed that the capital account openness did indeed have a positive effect on long-term financial development. This result is robust to several specifications of the autoregressive model and to alternative measures of financial development. Nevertheless, the short-term impact of the capital account openness is more limited, especially when considering the effects on the stock market.

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.

International audience; This research assesses the influence of hosting major international sporting competitions on the host countries' stock market performance before and after the announcement of such events. Specifically, this study explores whether stock markets of hosting countries experience cumulative average abnormal return (CAAR) during the aforementioned period. For the purposes of investigation, the study considers announcements of the 18th Asian Games and 30th SEA Games hosted by Indonesia and the Philippines, respectively. The LQ45 index of the Indonesia Stock Exchange (IDX) and PSEi index of the Philippines Stock Exchange (PSE) were chosen to test the significance of these events. It is found that only PSE has experienced a significantly positive CAAR for the event. Findings of this study can make a significant contribution to helping national governments and investors understand the significance of sports to the economies of developing countries and how major sports events can improve stock market efficiency.

State awards to civilians are a widespread social phenomenon across space and time. This paper quantifies the impact of State awards given to Directors on the stock value of their firms. We link a comprehensive dataset of recipients of the Légion d'honneurthe most prestigious official award in France-over the 1995-2019 period to Board positions in French listed firms. We document large abnormal returns in the stocks of recipients' firms at the date of the award, suggesting that awards signal valuable access to policy-makers. This interpretation is corroborated by the absence of any market reaction for recipients who were already identified before award receipt as being close to the Government.

Using a large database of US institutional investors’ trades in the equity market, this paper explores the effect of simultaneous executions on trading cost. We design a Bayesian network modelling the inter-dependencies between investors’ transaction costs, stock characteristics (bid-ask spread, turnover and volatility), meta-order attributes (side and size of the trade) and market pressure during execution, measured by the net order flow imbalance of investors meta-orders. Unlike standard machine learning algorithms, Bayesian networks are able to account for explicit inter-dependencies between variables. They also prove to be robust to missing values, as they are able to restore their most probable value given the state of the world. Order flow imbalance being only partially observable (on a subset of trades or with a delay), we show how to design a Bayesian network to infer its distribution and how to use this information to estimate transaction costs. Our model provides better predictions than standard (OLS) models. The forecasting error is smaller and decreases with the investors' order size, as large orders are more informative on the aggregate order flow imbalance (R2 increases out-of-sample from -0.17% to 2.39% for the smallest to the largest decile of order size). Finally, we show that the accuracy of transaction costs forecasts depends heavily on stock volatility, with a coefficient of 0.78.

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; In this paper, we look at the connection between the stock market and the unemployment rate in the United States. Using a recent time-varying Granger causality framework covering the period from January 1960 to October 2020, tests reveal that lagged realizations of the stock market have predictive power regarding unemployment, and vice et versa, but that the predictive ability only occurs sporadically over time, particularly during ‘crash’ periods. These results are in line with the literature on the information spillover between finance markets and the real-life economy, with changes of causality across time.

This paper investigates whether political connections affect individuals’ propensity to engage in white-collar crime. We identify connections by campaign donations or direct friendships and use the 2007 French Presidential election as a marker of change in the value of political connections to the winning candidate. We compare the behavior of Directors of publicly listed companies who were connected to the future President to the behavior of other non-connected Directors, before and after the election. Consistent with the belief that connections to a powerful politician can protect someone from prosecution or punishment, we uncover indirect evidence that connected Directors are more likely to engage in suspicious insider trading after the election: Purchases by connected Directors trigger larger abnormal returns, connected Directors are less likely to comply with trading disclosure requirements in a timely fashion, and connected Directors trade closer in time to their firms’ announcements of results. (JEL: D72, G14, G18, G38, K22, K42)

International audience; This paper studies the energy futures risk premia that can be extracted through long-short portfolios that exploit heterogeneities across contracts as regards various characteristics or signals and integrations thereof. Investors can earn a sizeable premium of about 8% and 12% per annum by exploiting the energy futures contract risk associated with the hedgers' net positions and roll-yield characteristics, respectively, in line with predictions from the hedging pressure hypothesis and theory of storage. Simultaneously exploiting various signals towards style-integration with alternative weighting schemes further enhances the premium. In particular, the style-integrated portfolio that equally weights all signals stands out as the most effective. The findings are robust to transaction costs, data mining and sub-period analyses.

We measure the extent to which consolidated liquidity in modern fragmented equity markets overstates true liquidity due to a phenomenon that we call Ghost Liquidity (GL). GL exists when traders place duplicate limit orders on competing venues, intending for only one of the orders to execute, and when one does execute, duplicates are cancelled. Employing data from 2013 for 91 stocks trading on their primary exchanges and three alternative platforms where order submitters are identified consistently across venues, we find that simply measured consolidated liquidity exceeds true consolidated liquidity due to the existence of GL. On average, for every 100 shares passively traded by a multi-market liquidity supplier on a given venue, around 19 shares are immediately cancelled by the same liquidity supplier on a different venue. Yet the average weight of GL in total consolidated depth, at around 4%, does not outweigh the liquidity benefits of fragmentation. GL is most pronounced for traders with a speed advantage such as high-frequency traders, in stocks exhibiting greater market fragmentation, in stocks where the tick is more likely to be binding, and on non-primary exchanges. Furthermore, GL decreases when the fraction of traders using smart order routing is large. Finally, we show that an increase in GL leads to the execution costs of slow and algo traders increasing, while those of HFTs are unaffected.

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; A vast quantity of high-dimensional, unstructured textual news data is produced every day, more than two decades after the launch of the global Internet. These big data have a significant influence on the way that decisions are made in business and finance, due to the cost, scalability, and transparency benefits that they bring. However, limited studies have fully exploited big data to analyze changes in news diversity or to predict financial market movements, specifically stock market crashes. Based on modern methods of textual analysis, this paper investigates the relationship between news diversity and financial market crashes by applying the change-point detection approach. The empirical analysis shows that (1) big data is a relatively new and useful tool for assessing financial market movements, (2) there is a relationship between news diversity and financial market movements. News diversity tends to decline when the market falls and volatility soars, and increases when the market is on an upward trend and in recovery, and (3) the multiple structural breaks detected improve the ability to forecast stock price movements. Therefore, changes to news diversity, embedded in big data, can be a useful indicator of financial market crashes and recoveries.

This paper questions the relevance of using only the 5-year maturity CDS spreads to examine the CDS market response to the disclosure of a regulatory stress test results. Since the stress testing exercises are performed on short-term forward-looking stressed scenarios (1 to 3 years), we assume that short-term CDS maturities (from 6-month to 3-year) should better reflect the CDS market response compared to the 5-year maturity. Based on ten regulatory stress tests carried out in Europe and in the US in the time period from 2009 to 2017, we analyze the CDS market response by investigating its reaction through all the different CDS maturities. Our results show that after the results’ disclosure, the CDS market reacts by correcting the CDS spreads of tested banks (upward or downward correction), at the level of all maturities. More precisely, we evidence that for a given stress test, the nature of the correction (upward or downward) is the same for all CDS maturities while the extent of the correction differs between short-term maturities (from 6-month to 3-year) and the 5-year maturity or more. Indeed, we find that the extent is higher on short-term maturities and in most cases, the lower the maturity of the CDS, the higher the extent of the correction (i.e. the stronger the market reaction). We therefore argue that the only use of the 5-year maturity is not suitable. Short-term CDS maturities matter since they better reflect the CDS market response. Also, the use of these short-term maturities show that the information content of the different stress tests is more diverse than what is highlighted in the existing literature.

Domestic outsourcing has grown substantially in developed countries over the past two decades. This paper addresses the question of the technological drivers of this phenomenon by studying the impact of the staggered diffusion of broadband internet in France during the 2000s. Our results confirm that broadband technology increases firm productivity and the relative demand for high-skill workers. Further, we show that broadband internet led firms to outsource some non-core occupations to service contractors, both in the low and high-skill segments. In both cases, we find that employment related to these occupations became increasingly concentrated in firms specializing in these activities, and was less likely to be performed in-house within firms specialized in other activities. As a result, after the arrival of broadband internet, establishments become increasingly homogeneous in their occupational composition. Finally, we provide suggestive evidence that high-skill workers experience salary gains from being outsourced, while low-skill workers lose out.

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

Using data from a peer-to-business crowdlending platform that exploits an auction-driven system to fund corporate loans, we show that non-professional investors are subject to a geographical-proximity bias. They are more likely to win the auctions of borrowers located close to their place of residence notwithstanding that they are not better informed about their creditworthiness. Unexpectedly, this behavioral bias distorts the loan rate discovery processby increasing the cost of funding for borrowers. This adverse effect results from the greaterability of local investors to submit winning bids at an early stage. This ability is gained from their experience in previous auctions of geographically close borrowers. This suggests that the familiarity feeling stemming from geographical closeness strengthens investor attention,and thereby improves lenders’ knowledge about the dynamics of the order flow in local borrowers’ auctions.

International audience; We use a dataset of approximately one million messages sent on StockTwits to explore the relationship between investor sentiment on social media and intraday Bitcoin returns. We find a statistically significant relationship between investor sentiment and Bitcoin returns for frequencies of up to 15 minutes. For lower frequencies, the relation disappears. We also find that the impact of sentiment on returns is concentrated on the period around the Bitcoin bubble. However, the magnitude of the effect is rather small making it impossible for a trader to make economic profits by trading on the information published on social media.

International audience; We examine how corporate real estate market participants adjust to the take-off of teleworking. We develop an indicator of the exposure of counties to teleworking in France by combining teleworking capacity with incentives and frictions to its deployment. We study how this indicator relates to prices and quantities in the corporate real estate market. We find that for offices in counties more exposed, the Covid-19 crisis has led to (1) higher vacancy rates, (2) less construction, (3) lower prices. Our findings reveal that teleworking has already an impact on the office market. Furthermore, forward-looking indicators suggest that market participants are anticipating the shift to teleworking to be durable.

To identify how blockchain technology affects current and future research, we carried out a bibliometric overview of the journal articles written on the blockchain. We aimed to answer some of the questions to visualize the trend of the publications regarding the advancement of blockchain utilization in fields relating to finance, economics, and social science. We used the Scopus database for the literature research, which resulted in 506 papers by 1278 authors from 79 countries. Our study showed that from 2008 till 2021, publishing about blockchain was more significant in conference papers than articles by a factor of 2. Our study also showed the importance of citation regarding published academic articles, the link to the number of publications, the authors, the universities, the affiliated organizations, and the countries of the publications. The use of authoring and citation analysis give valuable insights. On the topic of blockchain, we identified Financial Innovation as the most impactful journal on the topic, the National Natural Science Foundation of China as the leading funding sponsor on blockchain research, the USA as the highest publication production country, and Hong Kong as the highest country in the average citation per document produced. We finally identified the 20 most cited articles on the blockchain topics. Unlike other brief bibliometric studies, our study's investigation and findings could become a first stage of learning for those interested in carrying out a bibliometric study. In addition, our study could become the starting point for any future research on any blockchain projects.

Building parable economies embedding econometricians, we view alternative estimators (Instrumental variables, fuzzy regression discontinuity, natural experiments, OLS, event studies) from the perspective of privately informed decision-makers, e.g., CFOs. Instrumental variable estimates can be misleading since randomization through observable instruments eliminates signal content arising from discretion. If the goal is informing discretionary decisions, rather than predicting outcomes after forced/mistaken actions, instrumentation is problematic, whereas OLS or event studies can be sufficient. The analysis shows that the utility of alternative estimators hinges upon often neglected assumptions about agent/econometrician information sets, as distinct from exclusion restrictions. We recommend parable economy estimation before real-world IV estimation.

International audience; As the Saudi Stock Exchange is characterised by the domination of individual investors, we aim to study the impact of religious announcements conveyed by Imams on stock prices and investment decisions. These announcements are of two types: “downgrade announcements” (re-classifying firms from Sharia-compliant firms to non-Sharia-compliant firms), and “upgrade announcements” (re-classifying firms from non-Sharia-compliant firms to Sharia-compliant firms). In order to assess to what extent the religious factor is likely to affect the willingness to hold, purchase or sell financial securities, we first address a questionnaire to 427 individual investors. This survey demonstrates a high tendency to follow Imams’ announcements. In a next step, we apply an event study methodology to Imams’ announcements, and find a symmetrical response of stock prices, with religious downgrades (upgrades) being associated with statistically significant negative (positive) abnormal returns. This reaction is in line with the signal theory and information content hypothesis, indicating that Imams’ announcements related to the “religious status of a firm” convey valuable information to the financial market.

La libéralisation des marchés de l'énergie, l'émergence du marché du pétrole, le développement accéléré des pays émergents, l'ouverture de nombreux marchés dérivés et le développement des opérations financières adossées à des matières premières ont bouleversé le monde du négoce tel qu'il existait au milieu des années 1970. Ces transformations ont accéléré la croissance de Cargill, d'ADM, de Bunge et de Louis Dreyfus. Elles ont rendu possible l'émergence de nouveaux négociants. Vitol, Glencore, Trafigura, Mercuria, Gunvor en sont les exemples emblématiques. Elles ont donné naissance aux filiales de négoce des grandes entreprises du secteur de l'énergie : EDF Trading, Shell Trading, BP Trading, Total Trading & Shipping. De tous les facteurs qui ont fait évoluer le négoce des matières premières, la finance est celui qui a eu le plus d'impact.

We model of the search for predictors by speculators (active asset managers) and use it to analyze how the improvement in data processing power and the growth in available data (“data abundance”) affect the diversity of trading signals used by speculators, the dispersion of their profits and the similarities of their holdings. Our central message is that data abundance and computing power do not have the same effects. In particular, an improvement in computing power always raises the bar for the quality of predictors that managers consider good enough to exploit while more data lower it when data becomes sufficiently abundant. When this happens, the diversity of speculators’ signals and the dispersion of their trading profits increase in equilibrium while their holdings become less correlated.

We study how data abundance affects the informativeness of financial analysts' forecasts at various horizons. Analysts produce forecasts of short-term and long-term earnings and choose how much information to collect about each horizon to minimize their expected forecasting error, net of information acquisition costs. When the cost of obtaining short-term information drops (i.e., more data becomes available), analysts change their information collection strategy in a way that renders their short-term forecasts more informative but that possibly reduces the informativeness of their long-term forecasts. Using a large sample of analysts' forecasts at various horizons and novel measures of their exposure to abundant data (e.g., social media data), we provide empirical support for this prediction, which implies that data abundance can impair the quality of long-term forecasts.

International audience; "We study the reactions to job destructions on Twitter. We use information on large-scale job-destruction and job-creation events announced in the United Kingdom over the period 2013-2018. We match it with data collected on Twitter regarding the number and sentiments of the tweets posted around the time of the announcement and involving the company name. We show that job-destruction announcements immediately elicit numerous and strongly negative reactions. On the day of the announcement, the number of tweets and first-level replies sharply increases as does the negativity of the sentiments of the posted tweets. These reactions are systematically more important than reactions to job creations. We also show that they trigger significant losses in the market value of the downsizing firms. Our findings suggest that job destructions generate reputational costs for firms to the extent that they induce a strong negative buzz involving the company name."

International audience; We use a large dataset of one million messages sent on the microblogging platform StockTwits to evaluate the performance of a wide range of preprocessing methods and machine learning algorithms for sentiment analysis in finance. We find that adding bigrams and emojis significantly improve sentiment classification performance. However, more complex and time-consuming machine learning methods, such as random forests or neural networks, do not improve the accuracy of the classification. We also provide empirical evidence that the preprocessing method and the size of the dataset have a strong impact on the correlation between investor sentiment and stock returns. While investor sentiment and stock returns are highly correlated, we do not find that investor sentiment derived from messages sent on social media helps in predicting large capitalization stocks return at a daily frequency.

Cet article est le premier qui propose d’examiner l’influence journaliere de l’attention des investisseurs institutionnels (AII) sur le degre de liquidite boursiere. Pour ce faire, un echantillon compose de 87 titres francais de 2010 a 2018 est mobilise. De maniere originale, l’AII est estimee a partir du nombre de fois que les utilisateurs du terminal Bloomberg, qui sont pour la majorite des investisseurs institutionnels, realisent des recherches sur un titre donne et lisent des articles d’actualite sur une entreprise specifique. Les resultats empiriques indiquent que l’AII exerce un effet fortement positif sur le degre de liquidite des actions francaises.Classification JEL : G10, G14.

International audience; The stock markets in the Gulf Cooperation Council (GCC) countries are characterized by the domination of individual investors, therefore, we investigate how this characteristic may influence markets’ behavior. We examine the market reaction to the announcements conveyed by the major international credit rating agencies’ (CRAs). We assume the English language used by the CRAs to publish their news may fail to reduce the asymmetric information in GCCs, due to the low level of English knowledge amongst the individuals. We apply a questionnaire and an event-study and we find evidence for an influence of the English language on the individuals’ reaction.

Research Summary In this study, we replicate and expand Hawn et al.’s study (Strategic Management Journal, 2018, 39, 949–976) that used Dow Jones Sustainability World Index (DJSI) events to measure variations in firms' Corporate Social Responsibility (CSR)‐activism and examined their effect on a firm's stock price. We use DJSI events to capture variations in firms' CSR visibility, holding CSR activism constant by restricting our analyses to CSR‐equivalent firms. First, we find similar results on stock price (i.e., no impact) and on trading volumes. Second, because professional market participants pay more attention to CSR‐oriented firms and use visible cues such as DJSI events, we study and find that additions to DJSI lead to more analysts following a firm, and that continuations on the DJSI lead to an increase in equity being held by long‐term investors. Managerial Summary We replicate and complement a recent study that showed that the events of a firm's addition, continuation, or deletion in a major sustainability index (DJSI) had little impact on stock market reactions (Hawn et al. Strategic Management Journal, 2018, 39, 949–976). We redefine the comparison set that was previously used and compare across observationally equivalent firms in terms of CSR orientation in order to isolate the visibility effect of DJSI events. We find that these events do not significantly impact stock price and trading volumes. However, we expand the analysis and find that sustainability events attract more attention from financial analysts and lead to an increase in the percentage of shares held by long‐term investors indicative of a trend that professional investors pay more attention to CSR‐visible firms over time.

Literature suggests assets become more correlated during economic downturns. The current COVID-19 crisis provides an unprecedented opportunity to investigate this considerably further. Further, whether cryptocur-rencies provide a diversification for equities is still an unsettled issue. Additionally , the question of whether cryptocurrency futures are safe havens has received very little attention. We employ several econometric procedures , including wavelet coherence, copula principal component, and neural network analyses to rigorously examine the role of COVID-19 on the paired co-movements of six cryptocurrencies, as well as bitcoin futures, with fourteen equity indices and the VIX. We find co-movements between cryptocurrencies and equity indices gradually increased as COVID-19 progressed. However, most of these co-movements are positively correlated, suggesting that cryptocurrencies do not provide a diversification benefit during downturns. Exceptions, however, are the co-movements of bitcoin futures and tether being negative with equities. Results are consistent with investment vehicles that attract either more informed or more speculative investors differentiating themselves as safe havens.

Promotion of both market fairness and efficiency has long been a goal of securities market regulators worldwide. While previous studies mostly focused on market efficiency, our paper proposes tools to improve market fairness. We define market fairness as the ability of a market structure and its regulatory framework to guarantee unimpeded competition while curbing excessive speculation and market manipulation. Such behaviors undermine the quality of financial markets in the sense that they cause volatility and lead to instability. To encourage value generation and improve market quality, we advance a graduated Non-Value-Added Tax. The proposed tax is implemented in a simulation-based model whereby a profitable transaction is taxed at the higher rate if it does not enhance efficiency measured by deviation from fundamentals. When an agent locks in profit not supported by fundamentals but driven by trend-following strategies, the generated profit is taxed at graduate rates under the Non-Value-Added Tax regime. Unlike existing Financial Transaction Taxes, the Non-Value-Added Tax is levied on profit and not on price. More concretely, our findings show that this tool encourages profitable trades that add-value to the market and discourages valueless profit making. It significantly curtails volatility, and prevents the occurrence of extreme market events like bubbles and crashes.

International audience; Hayek and the Efficient Market Hypothesis (EMH) are often seen as proposing a similar theory of prices. Hayek is seen as proposing to understand prices as information conveyer, incorporating information during the process of competition, while EMH is defined as the fact that all information in a market is integrated into assets prices. This paper explains how a lineage between Hayek and the EMH can be illustrated while taking into account these differences. We introduce in order to defend this claim a distinction between methodological and epistemological differences: methodological differences are seen as the way an author operationalizes his broader conceptions whereas epistemology is defined as the core concepts of his theory. We particularly want to shed light on the homogeneous shift that can be identified in the epistemology of Hayek and the EMH. We conclude that this shift fleshes out the understanding that some authors have of neoliberalism.

The increasing propagation of the coronavirus pushes to urgently rethink the possible consequences for the global markets. The coronavirus combines demand, supply and uncertainty shocks, that would be harmful to the real economy mainly owing to the shutdown of factories and offices and travel restrictions. This would generate international spillover effects. In this article, we provide a first analysis of the stock price responses to the outbreak of COVID-19. To this end, we use an improved event study methodology to test how G7 (Canada, France, Germany, Italy, Japan, the United Kingdom and the United States) stock markets react to the rapid emergence of the novel epidemic.Then, we employ the volatility spillover procedure of Diebold and Yilmaz's (2012) to discern to what extent can China be a risk exporter to the G7 countries. Our results reveal that all the G7 stock markets are suffering from uncertainty caused by the COVID-19, but the responses to this shock differ from country to country. Difficulties in trade and travel interrupted the flow of goods and services, with cascading impacts on industries where supply chains depend hugely on supplies from China. In the current uncertain times, China is likely to be the major volatility transmitter (followed by the United States), whereas Japan, Germany, France and Italy are likely to be volatility receivers. The global spread of coronavirus may be an occasion for global value chains to rethink their global strategies.

We study the informative value of stress tests by investigating the impact of the disclosure of their results on banks' bonds split ratings taken as a measure of bank opacity. We consider bonds jointly rated by Moody's and Standard & Poor's and issued by banks that participated to the European and US banks' stress tests. Our results suggest that the disclosure of stress results has mixed effect on split ratings. Our findings also suggest a frequent divergence of interpretation of the stress test results between the two rating agencies meaning that information would not be as relevant as hoped by regulators. Market players certainly could not extract an unambiguous signal from all the results disclosed by the stress tests.

International audience; For decades, the two economic superpowers-the U.S and China-have been integrated. But the U.S. administration under Trump presidency is now attempting to undo that, as a deepening trade rift with China affect businesses in both economies. In July, August and September 2018, the United States successively increased tariffs on a total of $250 billion in annual imports of Chinese goods, stating that it wished to safeguard U.S. companies from unfair Chinese practices and lessen the bilateral trade deficit. China responded with tariffs on $110 billion of imports from the United States. The trade tensions between the two economic superpowers have led to a significant and rapid reduction in bilateral trade in taxed goods. This paper seeks to examine the heightened uncertainty surrounding the U.S.-China trade war to shed some light on the reactions of sectoral U.S. stock market to China tariff threats. While all sectors face increasing uncertainty, this trade war had varying sectoral effect. Specifically, the responses of information technology, industrials and energy were even more severe than the reactions of financials, consumer discretionary and staples, healthcare, real estate, aerospace and defense and utilities. Such positioning is designed to create a portfolio with balanced exposure to certain sectors for offense (information technology and industrials) and others for defense (healthcare, real estate and utilities).

International audience; We study banks' incentive to pool assets of heterogeneous quality when investors evaluate pools by extrapolating from limited sampling. Pooling assets of heterogeneous quality induces dispersion in investors' valuations without affecting their average. Prices are determined by market clearing assuming that investors can neither borrow nor short‐sell. A monopolistic bank has the incentive to create heterogeneous bundles only when investors have enough money. When the number of banks is sufficiently large, oligopolistic banks choose extremely heterogeneous bundles, even when investors have little money and even if this turns out to be collectively detrimental to the banks. If, in addition, banks can originate low quality assets, even at a cost, this collective inefficiency is exacerbated and pure welfare losses arise. Robustness to the presence of rational investors and to the possibility of short‐selling is discussed.

We investigate how Activist Short Sellers (AShSs) expose publicly listed firms in an increasingly popular form of “research reports” openly denouncing alleged frauds, flawed business models, accounting irregularities, and wrongdoings. We focus on six AShSs that issued research reports that often led to a strong negative market reaction. Our empirical analysis exploits both qualitative and quantitative methods for a comprehensive dataset of 383 research reports targeting 171 unique firms, and three first-hand interviews with AShSs. Drawing on Aristotle’s rhetoric, we first examine how AShSs use narratives in striving to convince other investors that the target firms are overvalued. Specifically, we search the documents produced by AShSs for stylized narratives related to credibility-based (ethos), emotions-based (pathos), and logic-based (logos) rhetorical strategies. To assess the impact of these strategies, we examine the extent to which the AShSs’ rhetorical strategies resonate in 3,665 press articles. As expected, the press often refers to logos-based arguments. Interestingly, the press also brings up frequently pathos-based and ethos-based statements. Considering the importance of the press in shaping investors’ opinions, our study points to AShSs’ narratives playing a major role in policing financial markets. Theoretically, we show that AShSs, as dissenting market participants, produce narratives that go beyond the language of formal rationality – as they strive to reveal new information and frame it persuasively, in order to destabilize the extent of trustworthiness surrounding target firms.

This paper explores the effects of online customer ratings on debt capacity. Using a large sample of Parisian restaurants, we find a positive and economically significant relation between customer ratings and bank debt. We use the locally exogenous variation in customer ratings resulting from the rounding of scores in regression discontinuity tests to establish causality. Customer ratings affect financial policy through a reduction in cash flow risk and higher resilience to demand shocks. Restaurants with good ratings use their extra debt capacity to invest in tangible assets. Finally, favorable online ratings relax credit constraints mostly for moderately constrained restaurants.

We study the effect of ambiguity on the formation of bubbles and on the occurrence of crashes in experimental asset markets à la Smith, Suchanek, and Williams (1988). We extend their framework to an environment where the fundamental value of the asset is ambiguous. We show that, when the fundamental value is ambiguous, asset prices tend to be lower than when it is risky although bubbles form in both the ambiguous and the risky environments. Additionally, bubbles do not crash in the ambiguous case whereas they do so in the risky one. These findings regarding depressed prices and the absence of crashes in the presence of ambiguity are in line with recent theoretical work stressing the crucial role of ambiguity to account for surprisingly low equity prices (high returns) as well as herding in asset markets.

International audience; We investigate the conditional cross effects and volatility spillover between equity markets and commodity markets (oil and gold), Fama and French HML and SMB factors, volatility index (VIX) and bonds using different multivariate GARCH specifications considering the potential asymmetry and persistence behaviours. We analyse the dynamic conditional correlation between the US equity market and a set of commodity prices and risk factors to forecast the transmission of shock to the equity market firstly, and to determine and compare the optimal hedge ratios from the different models based on the hedging effectiveness of each model. Our findings suggest that all models confirm the significant returns and volatility spillovers. More importantly, we find that GO-GARCH is the best-fit model for modelling the joint dynamics of different financial variables. The results of the current study have implications for investors: (i) the equity market displays inverted dynamics with the volatility index suggesting strong evidence of diversification benefit; (ii) of the hedging assets gold appears the best hedge for the US equity market as it has a higher hedge effectiveness than oil and bonds over time; and (iii) despite these important results, a better hedge may be obtained by using well-selected firm sized and profitability-based portfolios.

International audience; The mixture of distribution hypothesis (MDH) model offers an appealing explanation for the positive relation between trading volume and volatility of returns. In this specification, the information flows constitute the only mixing variable responsible for all changes. However, this single static latent mixing variable cannot account for the observed short-run dynamics of volume and volatility. In this paper, we propose a dynamic extension of the MDH that specifies the impact of information arrival on market characteristics in the context of liquidity frictions. We distinguish between short-term and long-term liquidity frictions. Our results highlight the economic value and statistical accuracy of our specification. First, based on some goodness of fit tests, we show that our dynamic two-latent factor model outperforms all competing specifications. Second, the information flows latent variable can be used to propose a new momentum strategy. We show that this signal improves once we allow for a second signal – the liquidity frictions latent variable – as the momentum strategies based on our model present better performance than the strategies based on competing models

Many contributions have dealt with the relation between implied and historical volatility in reference to the S&P100 index and on mostly limited samples of data. A large part of this literature finds that implied volatility defined directly from option prices is a biased estimator of future realized volatility, although some dissent has been expressed Christensen and Prabhala (1998). We investigate the issue on the larger market of the S&P500, using the VIX index as the measure of implied volatility and on a much larger sample (314 months), extending from January 1990 to December 2016. Our results are in line with most of the literature inasmuch as they invalidate the efficient market hypothesis. More originally, however, we use a time series analysis derived from Maurice Allais’s “lost” work on monetary theory and show that the VIX incorporates a subtle version of perceived and memorized past data – the “missing link” in relating implied to realized volatility - rather than reflecting any kind of “rational expectation” of future realized volatility. Incidentally, we show that the VIX seems to have been over-valued until the middle of the first decade of our century and to be since then averagely under-valued. Amazingly enough, this trend of affairs seems to be steadily confirmed by the financial market, which calls for additional research, even if we offer two possible explanations.

Using a large database of the US institutional investors’ trades, this paper revisits the question of anomalies-based portfolio transaction costs. The real costs paid by large investors to implement the well-identified size, value, and momentum anomalies are lower than what has been documented in the previous studies. We find that the average investor pays an annual transaction cost of 17bps for size, 24bps for value, and 274bps for momentum. The three strategies generate statistically significant returns of respectively 5.21%, 2.79% and 2.77% after accounting for transaction costs. When the market impact is taken into account, transaction costs reduce substantially the profitability of the well-known anomalies for large portfolios, however, these anomalies remain profitable for average size portfolios. The break-even capacities in terms of fund size are $ 206 billion for size, $ 16.1 billion for value and $ 310 million for momentum.

International audience; This paper provides a suitable model for studying the strategic behavior of uninformed investors that trade commodity derivatives via limit order books. Two main testable implications are obtained after solving for the model equilibrium. The adverse selection costs of uninformed traders depend on the inflow of market orders and their risk aversion. Next, the adverse selection costs of uninformed buyers and sellers and the difference of their asset valuations determine the size of their bid-ask spread. An analysis of European carbon futures data confirms the relevance of these implications. Moreover, we detect a diagonal effect that results in a positive correlation of market orders, which is driven by adverse selection, then by order splitting strategies and by imitative strategies of uninformed traders to a lesser extent.

International audience; Our study demonstrates the impact of CEO ascribed and achieved social status on M&A decision making and shows the firm value consequences from acquisition deals announced by executives with various status levels. Both ascribed (measured through prestigious education) and achieved (measured through receiving awards) social status are shown to be associated with reduced M&A activity and the effect is strongest among executives who possess both status types simultaneously. However, while the influence of ascribed status is permanent, higher achieved status reduces CEO acquisitiveness only in the immediate aftermath of receiving this status boost. Furthermore, while ascribed status has no significant impact on immediate announcement returns, possessing high achieved social status results in significant value destruction around deal announcements.

Bundling assets of heterogeneous quality results in dispersed valuations when these are based on investor-specific samples from the pool. A monop olistic bank has the incentive to create heterogeneous bundles only when investors have enough money as in that case prices are driven by more opti- mistic valuations. When the number of banks is sufficiently large, oligopolistic banks choose extremely heterogeneous bundles even when investors have little money and even if this turns out to be collectively detrimental to the banks, which we refer to as a Bundler.s Dilemma.