Marco LiCalzi

Ca' Foscari University of Venice

CombinatoricsDiscrete mathematicsMathematical optimizationTrading strategyMathematical economicsOutcome (game theory)EconometricsEconomicsCommon value auctionMicroeconomicsDecision analysisAllocative efficiencyExpected utility hypothesisStock marketMathematicsProspect theoryComputer scienceMarket microstructureFunction (mathematics)Upper and lower boundsVolatility (finance)

104Publications

14H-index

682Citations

Publications 74

#1Robert Gibbons (MIT: Massachusetts Institute of Technology)H-Index: 61

#2Marco LiCalzi (Ca' Foscari University of Venice)H-Index: 14

Last. Massimo Warglien (Ca' Foscari University of Venice)H-Index: 18

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We study agents who distill the complex world around them using cognitive frames. We assume that agents share the same frame and analyze how the frame affects their collective performance. In one-s...

#1Marco LiCalziH-Index: 14

In 2009, the photographer Marianna Cook published a fascinating collection of 92 photographic portraits of mathematicians. Her single-page preface to the book exudes the same insight and sensibility that animate her pictures. The first sentence, presumably written after having met and photographed so many of them, claims that “mathematicians […] may look like the rest of us, but they are not the same.” If the external appearance is the same, the differences must be somewhere else: here we sketch...

#1Lorenzo BastianelloH-Index: 2

#2Marco LiCalziH-Index: 14

We revisit the Nash bargaining model and axiomatize a procedural solution that maximizes the probability of successful bargaining. This probability-based approach nests both the standard and the ordinal Nash solution, and yet need not assume that bargainers have preferences over lotteries or that choice sets are convex. We consider both mediator-assisted bargaining and standard unassisted bargaining. We solve a long-standing puzzle and offer a natural interpretation of the product operator under...

#1Marco LiCalziH-Index: 14

#2Roland MühlenberndH-Index: 6

We study a model where agents face a continuum of two-player games and categorize them into a finite number of situations to make sense of their complex environment. Agents need not share the same categorization. Each agent can cooperate or defect, conditional on the perceived category. The games are fully ordered by the strength of the temptation to defect and break joint cooperation. In equilibrium agents share the same categorization, but achieve less cooperation than if they could perfectly ...

#1Robert F. Bordley (UM: University of Michigan)H-Index: 4

#2Marco LiCalzi (Ca' Foscari University of Venice)H-Index: 14

Last. Luisa Tibiletti (UNITO: University of Turin)H-Index: 9

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The “hard-easy effect” is a well-known cognitive bias on self-confidence calibration that refers to a tendency to overestimate the probability of success in hard-perceived tasks, and to underestimate it in easy-perceived tasks. This paper provides a target-based foundation for this effect, and predicts its occurrence in the expected utility framework when utility functions are S-shaped and asymmetrically tailed. First, we introduce a definition of hard-perceived and easy-perceived task based on ...

#1Marco LiCalzi (Ca' Foscari University of Venice)H-Index: 14

#1Marco LiCalzi (Ca' Foscari University of Venice)H-Index: 14

#2Nadia Maagli (University of Paris)H-Index: 1

Two agents endowed with different categorisations engage in bargaining to reach an understanding and agree on a common categorisation. We model the process as a simple non-cooperative game and demonstrate three results. When the initial disagreement is focused, the bargaining process has a zero-sum structure. When the disagreement is widespread, the zero-sum structure disappears and the unique equilibrium requires a retraction of consensus: two agents who individually associate a region with the...

#1Lorenzo Bastianello (Pantheon-Sorbonne University)

#1Marco LiCalzi (Ca' Foscari University of Venice)H-Index: 14

Last. L. Bastianello (University of Paris)

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We revisit the Nash model for two-person bargaining. A mediator knows agents' ordinal preferences over feasible proposals, but has incomplete information about their acceptance thresholds. We provide a behavioural characterisation under which the mediator recommends a proposal that maximises the probability that bargainers strike an agreement. Some major solutions are recovered as special cases; in particular, we offer a straightforward interpretation for the product operator underlying the Nash...

#1Lorenzo BastianelloH-Index: 2

#2Marco LiCalziH-Index: 14

We revisit the Nash model for two-person bargaining. A mediator knows agents' ordinal preferences over feasible proposals, but has incomplete information about their acceptance thresholds. We provide a behavioural characterisation under which the mediator recommends a proposal that maximises the probability that bargainers strike an agreement. Some major solutions are recovered as special cases; in particular, we offer a straightforward interpretation for the product operator underlying the Nash...

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