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    Structural models for the pricing of corporate securities and financial synergies. Applications with stochastic processes including arithmetic Brownian motion.

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    AFArikan_Final_Amended.pdf (1.062Mb)
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    Publication date
    2012-04-19
    Author
    Arikan, Ali F.
    Supervisor
    Kenc, Turalay
    Keyword
    Mergers
    Operational synergies
    Financial synergies
    Corporate securities
    Stochastic processes
    Organisations
    Rights
    Creative Commons License
    The University of Bradford theses are licenced under a Creative Commons Licence.
    Institution
    University of Bradford
    Department
    School of Management
    Awarded
    2010
    
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    Abstract
    Mergers are the combining of two or more firms to create synergies. These synergies may come from various sources such as operational synergies come from economies of scale or financial synergies come from increased value of securities of the firm. There are vast amount of studies analysing operational synergies of mergers. This study analyses the financial ones. This way the dynamics of purely financial synergies can be revealed. Purely financial synergies can be transformed into financial instruments such as securitization. While analysing financial synergies the puzzle of distribution of financial synergies between claimholders is investigated. Previous literature on mergers showed that bondholders may gain more than existing shareholders of the merging firms. This may become rather controversial. A merger may be synergistic but it does not necessarily mean that shareholders¿ wealth will increase. Managers and/or shareholders are the parties making the merger decision. If managers are acting to the best interest of shareholders then they would try to increase shareholders¿ wealth. To solve this problem first the dynamics of mergers were analysed and then new strategies developed and demonstrated to transfer the financial synergies to the shareholders.
    URI
    http://hdl.handle.net/10454/5416
    Type
    Thesis
    Qualification name
    PhD
    Collections
    Theses

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