Continuous-Time Models in Corporate Finance, Banking, and Insurance

Continuous-Time Models in Corporate Finance, Banking, and Insurance
Author :
Publisher : Princeton University Press
Total Pages : 176
Release :
ISBN-10 : 9781400889204
ISBN-13 : 1400889200
Rating : 4/5 (04 Downloads)

Book Synopsis Continuous-Time Models in Corporate Finance, Banking, and Insurance by : Santiago Moreno-Bromberg

Download or read book Continuous-Time Models in Corporate Finance, Banking, and Insurance written by Santiago Moreno-Bromberg and published by Princeton University Press. This book was released on 2018-01-08 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: Continuous-Time Models in Corporate Finance synthesizes four decades of research to show how stochastic calculus can be used in corporate finance. Combining mathematical rigor with economic intuition, Santiago Moreno-Bromberg and Jean-Charles Rochet analyze corporate decisions such as dividend distribution, the issuance of securities, and capital structure and default. They pay particular attention to financial intermediaries, including banks and insurance companies. The authors begin by recalling the ways that option-pricing techniques can be employed for the pricing of corporate debt and equity. They then present the dynamic model of the trade-off between taxes and bankruptcy costs and derive implications for optimal capital structure. The core chapter introduces the workhorse liquidity-management model—where liquidity and risk management decisions are made in order to minimize the costs of external finance. This model is used to study corporate finance decisions and specific features of banks and insurance companies. The book concludes by presenting the dynamic agency model, where financial frictions stem from the lack of interest alignment between a firm's manager and its financiers. The appendix contains an overview of the main mathematical tools used throughout the book. Requiring some familiarity with stochastic calculus methods, Continuous-Time Models in Corporate Finance will be useful for students, researchers, and professionals who want to develop dynamic models of firms' financial decisions.


Continuous-Time Models in Corporate Finance, Banking, and Insurance Related Books

Continuous-Time Models in Corporate Finance, Banking, and Insurance
Language: en
Pages: 176
Authors: Santiago Moreno-Bromberg
Categories: Business & Economics
Type: BOOK - Published: 2018-01-08 - Publisher: Princeton University Press

DOWNLOAD EBOOK

Continuous-Time Models in Corporate Finance synthesizes four decades of research to show how stochastic calculus can be used in corporate finance. Combining mat
The Economics of Continuous-Time Finance
Language: en
Pages: 641
Authors: Bernard Dumas
Categories: Business & Economics
Type: BOOK - Published: 2017-10-27 - Publisher: MIT Press

DOWNLOAD EBOOK

An introduction to economic applications of the theory of continuous-time finance that strikes a balance between mathematical rigor and economic interpretation
A Game Theory Analysis of Options
Language: en
Pages: 183
Authors: Alexandre C. Ziegler
Categories: Business & Economics
Type: BOOK - Published: 2012-11-02 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

Modern option pricing theory was developed in the late sixties and early seventies by F. Black, R. e. Merton and M. Scholes as an analytical tool for pricing an
The Oxford Guide to Financial Modeling
Language: en
Pages: 762
Authors: Thomas S. Y. Ho
Categories: Business & Economics
Type: BOOK - Published: 2004-01-15 - Publisher: Oxford University Press

DOWNLOAD EBOOK

The essential premise of this book is that theory and practice are equally important in describing financial modeling. In it the authors try to strike a balance
New Horizons for a Data-Driven Economy
Language: en
Pages: 312
Authors: José María Cavanillas
Categories: Computers
Type: BOOK - Published: 2016-04-04 - Publisher: Springer

DOWNLOAD EBOOK

In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They