Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Pooya Molavi"'
This paper analyzes how limits to the complexity of statistical models used by market participants can shape asset prices. We consider an economy in which agents can only entertain models with at most k factors, where k may be distinct from the true
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4585d9c0d93f2b262f3984d04f14f663
https://doi.org/10.3386/w28408
https://doi.org/10.3386/w28408
Publikováno v:
SSRN Electronic Journal.
Publikováno v:
Econometrica. 86:445-490
This paper studies the behavioral foundations of non‐Bayesian models of learning over social networks and develops a taxonomy of conditions for information aggregation in a general framework. As our main behavioral assumption, we postulate that age
Publikováno v:
IEEE Signal Processing Magazine. 30:30-42
The role of social networks in learning and opinion formation has been demonstrated in a variety of scenarios such as the dynamics of technology adoption [1], consumption behavior [2], organizational behavior [3], and financial markets [4]. The emerg
Publikováno v:
IEEE Journal of Selected Topics in Signal Processing. 7:358-369
This paper focuses on a model of opinion formation over networks with continuously flowing new information and studies the relationship between the network and information structures and agents' ability to reach agreement. At each time period, agents
Autor:
Pooya Molavi
Publikováno v:
SSRN Electronic Journal.
In this paper I propose an equilibrium search and matching model with worker heterogeneity, asymmetric information, and endogenous separations, and argue that it can help our understanding of the U.S. labor market experience following the Great Reces
Publikováno v:
SSRN Electronic Journal.
In this paper, we study the problem of non-Bayesian learning over social networks by taking an axiomatic approach. As our main behavioral assumption, we postulate that agents follow social learning rules that satisfy imperfect recall, according to wh
Publikováno v:
CDC
This work is concerned with the problem of social learning. A network of agents attempt to learn some unknown state of the world which is drawn by nature from a finite set. The sources of information available to the agents are their own private obse
Publikováno v:
ICASSP
We consider a repeated game in which a team of agents share a common, but only partially known, task. The team also has the goal to coordinate while completing the task. This creates a trade-off between estimating the task and coordinating with other
Publikováno v:
CDC
We study a dynamic game in which a group of players attempt to coordinate on a desired, but only partially known, outcome. The desired outcome is represented by an unknown state of the world. Agents' stage payoffs are represented by a quadratic utili