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Enseignant chercheurResponsable de la majeure Ingénierie Financière
- Tel : +33 (0)651096939
Duc PHAM-HI
Axe(s) de recherche : Mathématiques pour les sciences de l’ingénieur
Domaine(s) de compétence :
Modélisation de dynamiques macroéconomiques
Diplôme(s) :
Ingénieur ECP, Docteur, diplômé IEP Paris
Biographie
Pas de biographie pour le moment.
Retour à la liste des membresPublications de Duc PHAM-HI
« Prototyping the macroeconomic impact of cryptomoney with a small agent-based model »
par Duc PHAM-HI
Conférence à comité de revue , Ljubljana, Slovenia , 2017
Liste des auteurs : D. Pham-Hi
« A stochastic, Agents-based, actioned by heterogeneous adaptivity model »
par Duc PHAM-HI
Conférence à comité de revue , Genoa, Italy , 2015
Liste des auteurs : D. Pham-Hi
Abstract
University of Genova, Italy Conference Evolutionary Political Economics
« Vietnamese Bank Liquidity Risk Study Using The Risk Assessment Model of Systemic Institutions »
par Duc PHAM-HI
Modelling, Computation and Optimization, Springer ISBN: 978-3-319-18166-0 , pages 401-412 , Hochiminh, Vietnam , 2015
Liste des auteurs : T. Duong, D. Phamhi, P. Phan
Abstract
This study presents a liquidity risk management model allows to assess the impact of stress scenarios on a banking system within a top-down approach. The impact of stress scenarios on a banking system includes: (i) individual bank reactions to the shock, (ii) the shock transmission across banks, through interbank networks and nancial markets channels and (iii) the recover rate, the proportion of the debt a creditor receives in an event of a default. The macro economic model is estimated and simulated quarterly and the data in balance sheet is yearly for the Vietnamese banking system. The results show a high vulnerability of the trading portfolios and interbank market.
« Shadow banking dynamics and Learning behaviour »
par Duc PHAM-HI
Conférence à comité de revue , Bali, Indonesia , 2010
Liste des auteurs : D. Pham-Hi
Abstract
This paper presents the ongoing effort of setting up a model based on interactions between Agents in the banking sector endowed with some heterogeneous mechanism of learning and optimizing independently their differentiated utilities. The construction of the system is presented in detail, as are the components starting from a mini set of DSGE equations, and going through the reasons for adopting Q-Learning, part of Adaptive Learning mechanism, to animate these agents. An Interacting Particle System filter is also justified to serve as a human psychological bias generator for each type of agents who then can behave differently even though presented with the same arriving online bit of news. Finally a quick overview of the rough results obtained so far is presented at high level.