76 research outputs found

    A note on wage differentials, fixed-wages and adverse selection.

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    Using a substitution property of worker’s types (productivity and time preference), we propose an explanation for both fixed-wages and wage differentials. Fixed-wages result in bunching at the optimum. Equally productive workers with different time preference accept different wages.Wage differentials; Fixed-wages; Labor contracts; Adverse selection; Heterogeneous time preference;

    Deep Prediction Of Investor Interest: a Supervised Clustering Approach

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    We propose a novel deep learning architecture suitable for the prediction of investor interest for a given asset in a given timeframe. This architecture performs both investor clustering and modelling at the same time. We first verify its superior performance on a simulated scenario inspired by real data and then apply it to a large proprietary database from BNP Paribas Corporate and Institutional Banking

    Trusted Software within Focal

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    International audienceThis paper describes the Integrated Development Environment Focal together with a brief proof of usability on the formal development of access control policies. Focal is an IDE providing powerful functional and object-oriented features that allow to formally express specification and to go step by step (in an incremental approach) to design and implement while proving that the implementation meets its specification or design requirements. These features are particularly well-suited to develop libraries for secure applications

    COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

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    Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≀ 18 years: 69, 48, 23; 85%), older adults (≄ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

    Labor Contracts With Two-Dimensional Adverse Selection

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    1 We study incentive-compatible labor contracts in the case where both individual productivity and subjective discount rate are unobservable by the rm. We rst show that unidimensional manifolds of agents group on the same contract. High , low agents may choose the same contract as low , high agents. We show existence and uniqueness of an optimal wage function which is continuous and unbounded. This optimal wage function can be determined by the ironing procedure. Keywords: Adverse Selection, Incentive-Compatible Contracts, Ironing Procedure, Heterogeneous Time Preference. J.E.L. Classication: C61, C62, D82, J31, CEREMADE, CNRS UMR 7534, Universite Paris IX Dauphine, Place de Lattre de Tassigny, 75016 Paris, e-mail: [email protected] ERMES, CNRS, UPRES-A 7017, Universite Paris II (Pantheon-Assas), 92 rue d'Assas, 75270 Paris Cedex 06, e-mail: [email protected] 1 We thank David Bell, Ivar Ekeland, Thierry Granger and Nizar Touzi for helpful comments...

    Cross-sectional explanatory power of ESG features

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    We systematically investigate the links between price returns and ESG features. We propose a cross-validation scheme with random company-wise validation to mitigate the relative initial lack of quantity and quality of ESG data, which allows us to use most of the latest and best data to both train and validate our models. Boosted trees successfully explain a single bit of annual price returns not accounted for in the traditional market factor. We check with benchmark features that ESG features do contain significantly more information than basic fundamental features alone. The most relevant sub-ESG feature encodes controversies. Finally, we find opposite effects of better ESG scores on the price returns of small and large capitalization companies: better ESG scores are generally associated with larger price returns for the latter, and reversely for the former

    Deep Prediction Of Investor Interest: a Supervised Clustering Approach

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    International audienceWe propose a novel deep learning architecture suitable for the prediction of investor interest for a given asset in a given timeframe. This architecture performs both investor clustering and modelling at the same time. We first verify its superior performance on a simulated scenario inspired by real data and then apply it to a large proprietary database from BNP Paribas Corporate and Institutional Banking
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