Portail HAL HEC
Not a member yet
4784 research outputs found
Sort by
Risk versus ambiguity and international security design
No full textInternational audienceWe study portfolio allocation and characterize contracts issued by firms in the international financial market when investors exhibit ambiguity aversion and perceive ambiguity in assets issued in foreign locations. Increases in the variance of their risky production process cause firms to issue assets with a higher variable payment (equity). Hikes in investors' perceived ambiguity have the opposite effect, and lead to less risk-sharing. Entrepreneurs from capital-scarce countries finance themselves relatively more through debt than equity. They are thus exposed to higher volatility per unit of consumption. The expected returns on capital invested in capital-scarce countries may also be lower. Such results do not hold in the absence of ambiguity, that is, when investors only perceive risk. New facts uncovered from cross-country firm-level data are consistent with our model
Measuring Skewness Premia
No full textWe provide a new methodology to empirically investigate the respective roles of systematic and idiosyncratic skewness in explaining expected stock returns. Using a large number of predictors, we forecast the cross-sectional ranks of systematic and idiosyncratic skewness which are easier to predict than their actual values. Compared to other measures of ex ante systematic skewness, our forecasts create a significant spread in ex post systematic skewness. A predicted systematic skewness risk factor carries a significant risk premium that ranges from 7% to 12% per year and is robust to the inclusion of downside beta, size, value, momentum, profitability, and investment factors. In contrast to systematic skewness, the role of idiosyncratic skewness in pricing stocks is less robust. Finally, we document how the determinants of systematic and idiosyncratic skewness differ
Using Social Network Activity Data to Identify and Target Job Seekers
No full textAn important challenge for many firms is to identify the life transitions of its customers, such as job searching, being pregnant, or purchasing a home. Inferring such transitions, which are generally unobserved to the firm, can offer the firm opportunities to be more relevant to its customers. In this paper, we demonstrate how a social network platform can leverage its longitudinal user data to identify which of its users are likely job seekers. Identifying job seekers is at the heart of the business model of professional social network platforms. Our proposed approach builds on the hidden Markov model (HMM) framework to recover the latent state of job search from noisy signals obtained from social network activity data. Specifically, our modeling approach combines cross-sectional survey responses to a job seeking status question with longitudinal user activity data. Thus, in some time periods, and for some users, we observe the “true” job seeking status. We fuse the observed state information into the HMM likelihood, resulting in a partially HMM. We demonstrate that the proposed model can not only predict which users are likely to be job seeking at any point in time, but also what activities on the platform are associated with job search, and how long the users have been job seeking. Furthermore, we find that targeting job seekers based on our proposed approach can lead to a 42% increase in profits of a targeting campaign relative to the approach that was used at the time of the data collection
Les Stratégies Opérationnelles pour Promouvoir l'Amélioration de la Technologie dans les Chaînes de Valeur
No full textThis research is in the interface of sustainable operations management, technology management, and finance. Specifically, in my research I strive to examine firm's incentives to adopt `technology improvement' (TI) measures that lead to the more efficient use of inputs in operations and thereby affect the cost structure, risk exposure, and environmental performance of firms. Thus I seek to identify the factors that affect---and the mechanisms by which they do so---a firm's decision to invest in TI: forces within a supply chain, price uncertainty in the markets for inputs, cash constraints, financial hedging mechanisms, industry competition, and the firm's competitive pricing strategy. By collaborating with professors in the fields of operations research, economics, and finance, I have embraced a multidisciplinary approach to studying the adoption of efficient and sustainable technologies.In particular, in my first chapter, ``Technology Improvement Contracting in Supply Chains under Asymmetric Bargaining Power'' I examine how asymmetric bargaining power---between buyers and suppliers---affects the optimal level of investment in technology improvement. In my second chapter, ``Input-price Risk Management: Technology Improvement and Financial Hedging'', I explore the mechanism driving a firm's interest in TI under increased uncertainty about input prices. Finally, in the third chapter, ``The Value of Financial Risk Management in Dynamic Capacity Investment and Technology Improvement'', I study the role of budget constraint and financial hedging on the choice of technology.Cette recherche se situe à l'interface de la gestion des opérations durables, de la gestion de la technologie et de la finance. Plus précisément, dans mes recherches, j'essaie d'examiner les mesures incitatives des entreprises pour adopter des mesures d'amélioration technologique qui conduisent à une utilisation plus efficiente des intrants et affectent ainsi la structure des coûts, l'exposition aux risques et la performance environnementale des entreprises. Ainsi, je cherche à identifier les facteurs qui affectent --- et les mécanismes par lesquels ils le font --- la décision d'une entreprise d'investir dans TI: forces dans une chaîne d'approvisionnement, incertitude des prix sur les marchés des intrants, contraintes de trésorerie, couverture financière mécanismes, la concurrence de l'industrie et la stratégie de prix compétitive de l'entreprise. En collaborant avec des professeurs dans les domaines de la recherche opérationnelle, de l'économie et de la finance, j'ai adopté une approche multidisciplinaire pour étudier l'adoption de technologies efficaces et durables.En particulier, dans mon premier chapitre, «L'amélioration des technologies dans les chaînes d'approvisionnement sous pouvoir de négociation asymétrique», j'examine comment le pouvoir de négociation asymétrique --- entre les acheteurs et les fournisseurs --- affecte le niveau optimal d'investissement dans l'amélioration technologique. Dans mon deuxième chapitre, «Gestion des risques liés aux prix des intrants: amélioration de la technologie et couverture financière», j'explore le mécanisme qui guide l'intérêt d'une entreprise pour TI en raison de l'incertitude accrue sur les prix des intrants. Enfin, dans le troisième chapitre, «La valeur de la gestion des risques financiers dans l'investissement dynamique de capacité et l'amélioration technologique», j'étudie le rôle de la contrainte budgétaire et de la couverture financière sur le choix de la technologie
Product Categories as Judgment Devices: The Moral Awakening of the Investment Industry
No full textProduct categories are more than classification devices that organize markets; when reflecting market actors' purposes, they are also judgment devices. Taking stock of the literature on product categories and drawing on the distinction between the faculties of knowing and judging, we elaborate a framework that accounts for how and why market actors include or exclude normative attributes in a product category definition. Based on a field study of the development of Socially Responsible Investment (SRI) funds in France, we describe the phases and conditions of a judgment framework for category definition, for both established and nascent categories. We discuss implications for research on product categories and the workings of markets more broadly
Moral Imaginaries of Performance Measurement Systems in the Pharmaceutical Industry: Struggles and Negotiations to Define What is an Agent and What is Not
No full textThis study explores how morality is constituted into accounting objects and how accounting becomes a moral mediator. We retrace the moral practices that subtend the field-level construction of a Principal-Agent incentive algorithm in a Big Pharma company, with particular focus on the inscribing work through which different communities of knowledge, internal and external to the organization, try to realize particular moral principles for the performance measurement system in the making. The study draws upon Science and Technology Studies (Latour, 1989; Jasanoff, 2015) to explore performance measurement systems as existing in Moral Imaginaries, ethical visions that positions accounting devices, and their material features and technical functionalities, as embedding and enacting ‘moral’ and ‘just’ viewpoints. We show how performance measurement systems emerge as moral calculating devices that are shaped by, and struggle with, the contrasting moralities of heterogeneous designers, but also act as moral mediators that reshape human actors’ moral imaginaries as their algorithmic constructions and data outputs perform. In so doing, we contribute to Science and Technology Studies by highlighting how the constitution of who / what is an “Agent”, and its actantiality, is embedded upon movements in which morality circulates, is claimed by actors and attributed to others, and finally objectified in material technologies
Stock Market Rumors and Credibility
No full textStock prices occasionally move in response to unverified rumors. I propose a cheap talk model in which a rumormonger's incentives to tell the truth depend on the interaction between her investment horizon and the information acquisition decisions of message-receiving investors. The model's key prediction is that short investment horizons can facilitate credible information sharing between investors, thereby accelerating the information capitalization into market prices. Analyzing a dataset of takeover rumors covered by US newspapers, I find suggestive evidence in support of this prediction
Second-Order Induction: Uniqueness and Complexity
No full textAgents make predictions based on similar past cases, while also learning the relative importance of various attributes in judging similarity. We ask whether the resulting "empirical similarity" is unique, and how easy it is to find it. We show that with many observations and few relevant variables, uniqueness holds. By contrast, when there are many variables relative to observations, non-uniqueness is the rule, and finding the best similarity function is computationally hard. The results are interpreted as providing conditions under which rational agents who have access to the same observations are likely to converge on the same predictions, and conditions under which they may entertain different probabilistic beliefs
The Long-Term Consequences of the Tech Bubble on Skilled Workers' Earnings
No full textWe use French matched employer-employee data to track skilled individuals entering the labor market during the late 1990s tech bubble. The boom led to a sharp increase in the share of skilled entrants in the tech sector, which offers relative higher wages at the time. When the boom ends, however, the wage premium reverses and these skilled workers end up with a 5.5% wage discount ten years out, relative to similar peers who started in a non-tech sector. Other moments of the wage distribution of the boom, pre-boom, and post-boom cohorts are inconsistent with explanations based on a selection effect or a cycle effect. Instead, we provide suggestive evidence that workers allocated to the booming tech sector accumulate human capital early in their career that rapidly becomes obsolete