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Agent-based Modeling and Statistical...

El-Masri, Fatena.

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Agent-based Modeling and Statistical Analysis of Complex Systems, with Applications to Financial Network for Failing Banks.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Agent-based Modeling and Statistical Analysis of Complex Systems, with Applications to Financial Network for Failing Banks./
作者:	El-Masri, Fatena.
面頁冊數:	171 p.
附註:	Source: Dissertation Abstracts International, Volume: 76-10(E), Section: B.
Contained By:	Dissertation Abstracts International76-10B(E).
標題:	Statistics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3706745
ISBN:	9781321808179

Agent-based Modeling and Statistical Analysis of Complex Systems, with Applications to Financial Network for Failing Banks.
El-Masri, Fatena.

Agent-based Modeling and Statistical Analysis of Complex Systems, with Applications to Financial Network for Failing Banks. - 171 p.

Source: Dissertation Abstracts International, Volume: 76-10(E), Section: B.

Thesis (Ph.D.)--George Mason University, 2015.

This item must not be sold to any third party vendors.

This dissertation describes the application of Agent-Based Modeling (ABM) to the study of complex networked systems. Such complex systems cannot be simulated with a deterministic model, but they require models that respond to collective intelligence, that exhibit emergent behavior, and that undergo state transitions (such as tipping points) which cannot be explicitly coded in an equation. ABM is specifically applied in this dissertation to financial networks involving failing banks. Because all banks (including domestic and international banks) are connected to each other through inter-bank financial transactions (exchange of assets and liabilities), they are therefore exposed to risk and potential failure conditions. Investigation of the conditions that lead to financial network instability and bank failures is the core of this dissertation. The ABM modeling approach presented in this work provides a framework for the analysis of systemic risk, as well as cascading and contagion processes, in different banking network scenarios and for both large and small banks. The big research questions posed by this dissertation are: (a) What are the major emergent modes of behavior in the banking network, and are they stable or unstable? (b) Can we inform financial policymakers what the safe policy should be in order to keep the failure rate in the banking network below a pre-specified fraction?

ISBN: 9781321808179Subjects--Topical Terms:

517247
Statistics.

Agent-based Modeling and Statistical Analysis of Complex Systems, with Applications to Financial Network for Failing Banks.
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245 1 0 $a Agent-based Modeling and Statistical Analysis of Complex Systems, with Applications to Financial Network for Failing Banks.
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500 $a Source: Dissertation Abstracts International, Volume: 76-10(E), Section: B.
500 $a Adviser: Kirk Borne.
502 $a Thesis (Ph.D.)--George Mason University, 2015.
506 $a This item must not be sold to any third party vendors.
520 $a This dissertation describes the application of Agent-Based Modeling (ABM) to the study of complex networked systems. Such complex systems cannot be simulated with a deterministic model, but they require models that respond to collective intelligence, that exhibit emergent behavior, and that undergo state transitions (such as tipping points) which cannot be explicitly coded in an equation. ABM is specifically applied in this dissertation to financial networks involving failing banks. Because all banks (including domestic and international banks) are connected to each other through inter-bank financial transactions (exchange of assets and liabilities), they are therefore exposed to risk and potential failure conditions. Investigation of the conditions that lead to financial network instability and bank failures is the core of this dissertation. The ABM modeling approach presented in this work provides a framework for the analysis of systemic risk, as well as cascading and contagion processes, in different banking network scenarios and for both large and small banks. The big research questions posed by this dissertation are: (a) What are the major emergent modes of behavior in the banking network, and are they stable or unstable? (b) Can we inform financial policymakers what the safe policy should be in order to keep the failure rate in the banking network below a pre-specified fraction?
520 $a The major discoveries that we have found through investigation of these research questions are the following: (1) The well-known real-world Too Big To Fail (TBTF) instability mode is seen, thereby validating our modeling methodology. (2) The existence of two new instability modes is demonstrated: (a) Too Connected To Fail (TCTF) and (b) Too Small To Fail (TSTF). These modes represent new discoveries in the field of financial networks. (3) The discovery of tipping points in the financial network, seen in the bi-modal behavior of some simulations that are almost schizophrenic: for the same input parameters, the simulation yields either massive network failure or nearly zero failures. (4) Heuristics have been found to inform policymakers regarding financial policies to minimize instability and failure in the banking network.
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