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作者：Neufeld, Ariel; Papapantoleon, Antonis; Xiang, Qikun
作者单位：Nanyang Technological University; Delft University of Technology; Foundation for Research & Technology - Hellas (FORTH)
摘要：We consider derivatives written on multiple underlyings in a one-period financial market, and we are interested in the computation of model-free upper and lower bounds for their arbitrage-free prices. We work in a completely realistic setting, in that we only assume the knowledge of traded prices for other single- and multi-asset derivatives and even allow for the presence of bid-ask spread in these prices. We provide a fundamental theorem of asset pricing for this market model, as well as a s...
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作者：Dieler, Tobias; Biswas, Sonny; Calzolari, Giacomo; Castiglionesi, Fabio
作者单位：University of Bristol; European University Institute; Centre for Economic Policy Research - UK; Tilburg University
摘要：We study the impact of a financial transaction tax (FTT) in a model that combines asset trading and real investment. An informed trader holds private information about the fundamental value of a firm, and the firm'smanager relies on the asset price to infer such information and invest accordingly. We characterize an informative, but illiquid, equilibrium where the firm's value is optimal but trade is inefficiently low, together with an uninformative equilibrium with maximal liquidity but ineff...
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作者：Aouad, Ali; Saban, Daniela
作者单位：University of London; London Business School; Stanford University
摘要：Motivated by online labor markets, we consider the online assortment optimization problem faced by a two-sided matching platform that hosts a set of suppliers waiting to match with a customer. Arriving customers are shown an assortment of suppliers and may choose to issue a match request to one of them. After spending some time on the platform, each supplier reviews all the match requests she has received and, based on her preferences, she chooses whether to match with a customer or to leave u...
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作者：Kallus, Nathan; Mao, Xiaojie
作者单位：Cornell University; Tsinghua University
摘要：We study contextual stochastic optimization problems, where we leverage rich auxiliary observations (e.g., product characteristics) to improve decision making with uncertain variables (e.g., demand). We show how to train forest decision policies for this problem by growing trees that choose splits to directly optimize the downstream decision quality rather than split to improve prediction accuracy as in the standard random forest algorithm. We realize this seemingly computationally intractable...
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作者：Zhang, Zelin; Yang, Kejia; Zhang, Jonathan Z.; Palmatier, Robert W.
作者单位：Renmin University of China; Colorado State University System; Colorado State University Fort Collins; University of Washington; University of Washington Seattle
摘要：Massive online text reviews can be a powerful market research tool for understanding consumer experiences and helping firms improve and innovate. This research exploits the rich semantic properties of text reviews and proposes a novel machine learning modeling framework that can reliably and efficiently extract consumer opinions and uncover potential interaction effects across these opinions, thereby identifying hidden and nuanced areas for product and service improvement beyond existingmodeli...
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作者：Chen, Xi; Liu, Quanquan; Wang, Yining
作者单位：New York University; University of Texas System; University of Texas Dallas
摘要：In this paper, we study the learning problemin contextual search, which ismotivated by applications such as crowdsourcing and personalized medicine experiments. In particular, for a sequence of arriving context vectors, with each context associated with an underlying value, the decision maker either makes a query at a certain point or skips the context. The decision maker will only observe the binary feedback on the relationship between the query point and the value associated with the context...
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作者：Wang, Qiaochu; Huang, Yan; Jasin, Stefanus; Singh, Param Vir
作者单位：Carnegie Mellon University; University of Michigan System; University of Michigan
摘要：Should firms that apply machine learning algorithms in their decision making make their algorithms transparent to the users they affect? Despite the growing calls for algorithmic transparency, most firms keep their algorithms opaque, citing potential gaming by users that may negatively affect the algorithm's predictive power. In this paper, we develop an analytical model to compare firm and user surplus with and without algorithmic transparency in the presence of strategic users and present no...
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作者：Mariotti, Thomas; Schweizer, Nikolaus; Szech, Nora; von Wangenheimg, Jonas
作者单位：Centre National de la Recherche Scientifique (CNRS); Universite de Toulouse; Universite Toulouse 1 Capitole; Toulouse School of Economics; Centre for Economic Policy Research - UK; Leibniz Association; Ifo Institut; Tilburg University; Helmholtz Association; Karlsruhe Institute of Technology; University of Bonn
摘要：We study the optimal design of information nudges directed to present-biased consumers who make consumption decisions over time without exact prior knowledge of their long-term consequences. For any distribution of risks, there exists a consumer optimal information nudge that is of cutoff type, recommending abstinence if the risk is high enough. Depending on the distribution of risks, more or fewer consumers have to be sacrificed, as they cannot be credibly warned even though they would like t...
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作者：Imhof, Lorens A.; Kraekel, Matthias
作者单位：University of Bonn
摘要：This paper analyzes how the degree of task-related team diversity influences the team outcome. The focus is on a novel benefit of team diversity that does not depend on complementary skills or mutual learning. We consider a multiagent setting where the employer makes use of career competition to motivate the team. Our analysis reveals incentive effects that do not exist in the well-studied case of teams of size 2. In teams with more than two members, diversity may have a positive effect on the...
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作者：Fischetti, Martina; Fischetti, Matteo
作者单位：University of Padua
摘要：We address a very important problem in offshore wind farm design, namely, the combined optimization of the turbine location and of the connection cables required to bring the electrical power produced by the turbines to a given substation, and eventually to shore. We first describe a mixed-integer linear programming model that combines previous proposals from the literature. Then we improve it by a number of additional inequalities intended to strengthen its linear programming relaxation. In p...
