Leveraged Buyouts : An LBO Valuation Model
During the eighties a new type of financial transaction started to emerge on an increasing basis. It was the so called “leveraged buyout” also known as the LBO. In the US private equity firms made it to the headlines in financial media from engaging in leveraged buyouts with small equity investments and large amounts of borrowed capital, their targets where large solid multinational corporations. Much has happened since the eighties. Back then leveraged buyouts where often associated with terms such as “Slash and Burn” or “Buy, Flip and Strip” often meaning hostile takeovers and huge layoffs. Today private equity firms focus more on active ownership, fast decisions without the bureaucracy of the stock market and long term value creation in order to profit from their buyouts.
As private equity firms today invest tremendous amounts of capital through their private equity funds. Leveraged buyouts have become one of the major areas within investment banking. Even though the LBO is a common transaction it is often hard to find models used for valuation of such a deal. Private equity funds and investment banks all have their own valuation models but these are regarded as strictly confidential and seldom revealed to the public. Therefore the creation and publication of an LBO valuation model should be of great interest for everyone aiming at a future career within private equity, corporate finance or investment banking.
This thesis derives a complete LBO valuation model including a framework for finding a suitable LBO target. The LBO valuation model is created in cooperation with the debt capital markets department at one of the leading investment banks in the Nordic region. The framework is based on a qualitative study conducted on seven of the most distinguished private equity firms active in Sweden. In order to show how the LBO valuation model and the framework works, both are applied on the retail company Björn Borg listed on NASDAQ OMX. To verify the accuracy of the framework, calculated return from the model is analyzed and compared to the indications given by the framework.
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