Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Aymanns, Christoph"'
We model the spread of news as a social learning game on a network. Agents can either endorse or oppose a claim made in a piece of news, which itself may be either true or false. Agents base their decision on a private signal and their neighbors' pas
Externí odkaz:
http://arxiv.org/abs/1708.06233
Autor:
Aymanns, Christoph
This thesis studies systemic risk in financial markets and how it emerges through dynamical and structural amplification mechanisms. In part (1) I study the dynamics and control of Basel leverage cycles. For this I develop a simple model of a financi
Externí odkaz:
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.712109
Effective risk control must make a tradeoff between the microprudential risk of exogenous shocks to individual institutions and the macroprudential risks caused by their systemic interactions. We investigate a simple dynamical model for understanding
Externí odkaz:
http://arxiv.org/abs/1507.04136
Autor:
Aymanns, Christoph, Georg, Co-Pierre
When banks choose similar investment strategies the financial system becomes vulnerable to common shocks. We model a simple financial system in which banks decide about their investment strategy based on a private belief about the state of the world
Externí odkaz:
http://arxiv.org/abs/1408.0440
Autor:
Aymanns, Christoph, Farmer, J. Doyne
We present a simple agent-based model of a financial system composed of leveraged investors such as banks that invest in stocks and manage their risk using a Value-at-Risk constraint, based on historical observations of asset prices. The Value-at-Ris
Externí odkaz:
http://arxiv.org/abs/1407.5305
Publikováno v:
In Handbook of Computational Economics 2018 4:329-391
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
In Journal of Financial Stability December 2016 27:263-277
Autor:
Aymanns, Christoph, Farmer, J. Doyne
Publikováno v:
In Journal of Economic Dynamics and Control January 2015 50:155-179
We propose multi-agent reinforcement learning as a new method for modeling fake news in social networks. This method allows us to model human behavior in social networks both in unaccustomed populations and in populations that have adapted to the pre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_________2::d01cf6e0da9da526ff85dfbe3d44e98e
http://www.alexandria.unisg.ch/266841/
http://www.alexandria.unisg.ch/266841/