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Multi-agent Network Models of Financial Stability
Název práce v češtině: Multiagentní síťové modely finanční stability
Název v anglickém jazyce: Multi-agent Network Models of Financial Stability
Klíčová slova: finanční krize, finanční nákaza, finanční podpora, finanční regulace, finanční stabilita, multiagentní modely, riziko likvidity, síťové modely, státní podpora, systémové riziko
Klíčová slova anglicky: agent-based models, bailout, contagion, financial crises, financial regulation, financial stability, liquidity risk, network models, state support, systemic risk
Akademický rok vypsání: 2013/2014
Typ práce: disertační práce
Jazyk práce: angličtina
Ústav: Institut ekonomických studií (23-IES)
Vedoucí / školitel: doc. PhDr. Petr Teplý, Ph.D.
Řešitel: skrytý - zadáno a potvrzeno stud. odd.
Datum přihlášení: 13.11.2015
Datum zadání: 13.11.2015
Datum potvrzení stud. oddělením: 13.11.2015
Datum a čas obhajoby: 21.09.2016 00:00
Místo konání obhajoby: IES
Datum odevzdání elektronické podoby:09.07.2016
Datum odevzdání tištěné podoby:08.07.2016
Datum proběhlé obhajoby: 21.09.2016
Oponenti: prof. BcA. David Tripe
  doc. Ing. Daniel Stavárek, Ph.D.
  doc. PhDr. Ing. et Ing. Petr Jakubík, Ph.D., Ph.D.
 
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Předběžná náplň práce
Tato práce pojednává o mezinárodní bankovní regulaci a na vazby mezi krizemi finančního systému a dluhovými krizemi jednotlivých států. Po ilustraci hlavních vztahů na nedávné finanční krizi zkonstruujeme několik multiagentních síťových modelů finančního systému pro testování jeho stability při různých nastaveních jeho parametrů.
V první části se zaměřujeme na důvody regulace bank a popisujeme vývoj mezinárodní bankovní regulace včetně aktuálně představených dokumentů známých jako Basel III. Hlavním závěrem této části je skutečnost, že regulace je z velké míry ovlivňována samotnými bankami a ne vždy slouží k zajištění stability finančního systému.
Ve druhé části zkonstruujeme multiagentní model, který umožňuje simulovat dopady negativních šoků při různých nastaveních parametrů bankovního systému a regulatorního prostředí. Naše simulace ukazují zaprvé, že dostatečná míra kapitálu je nezbytná pro zajištění systémové stability, zadruhé, že jakmile se systém octne v systémové krizi, diskreční zásahy mají jen velmi malý účinek a zatřetí poukazují na užitečnost regulace likvidity.
Ve třetí části model rozšíříme tak, aby umožnil analyzovat efekty státní podpory na systémovou stabilitu a efekty zpětné vazby, při kterých se riziko přenáší ze států zpět na bankovní systém. Dále testujeme různé parametrizace modelu pomocí Monte Carlo simulací.
Ve čtvrté části je model zkalibrován pomocí jedinečné sady dat složené z různých zdrojů. Klíčové výsledky naší analýzy jsou následující: Zaprvé, v krátkodobém horizontu veškerá opatření na podporu bank zlepšují systémovou stabilitu. Za druhé, v delším časovém horizontu závisí účinky státní podpory na parametrizaci modelu, ale stále existují nastavení, za kterých státní pomoc výrazně zmírňuje systémovou krizi. A konečně, existují rozdíly mezi účinky různých typů podpůrných opatření.
Předběžná náplň práce v anglickém jazyce
The thesis focuses on the international banking regulation and on the nexus between financial sovereign crises. After illustrating the main mechanisms on the recent financial crisis, we construct several multi-agent network models of a financial system for testing its stability under different setting of parameters.
In the first part, we focus on the rationale for banking regulation and we describe its development including the recently introduced Basel III measures. The main conclusion of this part is that regulation is to a large extent influenced by the banks and it does not always secure financial system stability.
In the second part, we build an agent-based model which enables us to simulate the impacts of various types of negative shocks given various settings of the banking system and the regulatory environment, including the capital and liquidity measures. Our simulations show firstly that sufficient capital buffers are crucial for systemic stability, secondly that the discretionary measures have little effect once a crisis breaks out and thirdly that liquidity measures are a relevant regulatory tool.
In the third part, the model is extended so that it allows for testing effects of state support on systemic stability is tested with various parameter settings in Monte Carlo simulations and for testing of feedback loops in which the risk is transferred from the sovereigns back to the financial system. Different parameter settings are tested in Monte Carlo simulations.
In the fourth part, the model is calibrated to the real world data using a unique dataset put together from various sources. Our analyses yield the following key results: Firstly, in the short term, all the support measures improve the systemic stability. Secondly, in the longer run, the effects of state support depend on several parameters but still there are settings in which it significantly mitigates the systemic crisis. Finally, there are differences among the effects of the different types of support measures.
 
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