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Contract Theory in Continuous-Time Models
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Contract Theory in Continuous-Time Models

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ISBN-13:
9783642142000
Einband:
eBook
Seiten:
256
Autor:
JakSa Cvitanic
Serie:
Springer Finance
eBook Typ:
PDF
eBook Format:
PDF
Kopierschutz:
1 - PDF Watermark
Sprache:
Englisch
Beschreibung:

There has been increased interest in continuous-time Principal-Agent models and their applications. This monograph surveys results of the theory using the approach of the so-called Stochastic Maximum Principle, in models driven by Brownian Motion.

Preface.- PART I Introduction: 1.The Principal-Agent Problem.- 2.Single-Period Examples.- PART II First Best. Risk Sharing under Full Information: 3.Linear Models with Project Selection, and Preview of Results.- 4.The General Risk Sharing Problem.- PART III Second Best. Contracting Under Hidden Action- The Case of Moral Hazard: 5.The General Moral Hazard Problem.- 6.DeMarzo and Sannikov (2007), Biais et al (2007) - An Application to Capital Structure Problems: Optimal Financing of a Company.- PART IV Third Best. Contracting Under Hidden Action and Hidden Type - The Case of Moral Hazard and Adverse Selection: 7.Controlling the Drift.- 8.Controlling the Volatility-Drift Trade-Off with the First-Best.- PART IV Appendix: Backward SDEs and Forward-Backward SDEs.- 9.Introduction.- 10.Backward SDEs.- 11.Decoupled Forward Backward SDEs.- 12.Coupled Forward Backward SDEs.- References.- Index.
In recent years there has been a significant increase of interest in continuous-time Principal-Agent models, or contract theory, and their applications. Continuous-time models provide a powerful and elegant framework for solving stochastic optimization problems of finding the optimal contracts between two parties, under various assumptions on the information they have access to, and the effect they have on the underlying "profit/loss" values. This monograph surveys recent results of the theory in a systematic way, using the approach of the so-called Stochastic Maximum Principle, in models driven by Brownian Motion.

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