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A study in the effectiveness of predicting default using the Merton model during financial distress

A study in the effectiveness of predicting default using the Merton model during financial distress

Abstract
Bachelor thesis in financial economics Applied financial pricing theory Department of finance School of Business, Economics and Law Gothenburg University 9 June 2014. Title: A study in the effectiveness of predicting default using the Merton model during financial distress Author: Martin Gholami and Andreas Hjelm Supervisor: Evert Carlsson, Ph.D. Background: There are many approaches for calculating the default probability for a corporate bond, but none so important and widely used as the Merton model. The Merton model is a firm value model for pricing risky corporate bonds, from 1974 by Robert Merton. Purpose: The purpose of this paper is to show how well the Merton model predicts corporate default during a period of financial distress. Motivation: We intend to give the reader a step-by-step introduction to the Merton model and how to apply the model on real corporate data. Methodology: First, we extract all the necessary data from the balance sheet and market quotes for equity. Second, a risk-free discount rate is constructed from two generic US government bonds. Then, we discount all future cash flows of the bond to be able to solve for the volatility. Finally, default probabilities are calculated. Conclusion and Discussion: In our study we analyzed the outcome of the results and tried to find shortcomings and advantages in the Merton model. However in a period of financial distress it is hard to say if the model predicts default better or worse than more complex models. Further research: There are many more developed and complex firm value models. An interesting approach would be to convey a comparative study of different models to conclude each model’s advantages and limitations.
Degree
Student essay
URI
http://hdl.handle.net/2077/35973
Collections
  • Kandidatuppsatser / Institutionen för nationalekonomi och statistik
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Thesis frame (3.300Mb)
Date
2014-06-09
Author
Gholami, Martin
Hjelm, Andreas
Keywords
Balance sheet
Bloomberg
Default probability
Excel
Ford Motor Company
Volatility
Series/Report no.
201406:91
Uppsats
Language
eng
Metadata
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