A Theoretical Model for the Term Structure of Corporate Credit based on Competitive Advantage

Published date01 March 2017
Date01 March 2017
A Theoretical Model for the Term
Structure of Corporate Credit based
on Competitive Advantage
Bala Rajaratnam
Department of Statistics, Stanford University, USA; and Financial and Risk Modeling Institute,
Stanford University, USA
E-mail: brajaratnam01@gmail.com
Kanshukan Rajaratnam
Department of Finance, Tax & African Collaboration for Quantitative Finance and Risk Research,
University of Cape-town, Rondebosch, South Africa
E-mail: kanshukan.rajaratnam@uct.ac.za
Myuran Rajaratnam
School of Economics & Business Sciences, University of the Witwatersrand, South Africa
E-mail: myuranraj@gmail.com
We derive the term structure of co rporate credit based on the comp etitive
advantage of a rm and the tax deductibility of its interest payments. We
consider the competitive a dvantage enjoyed by the rm as the ce ntral tenet of
our model and capture its event ual demise in a probabilisti c manner. We
compensate the bond holder for exp ected losses and then provide an add itional
spread based on the tax deducti bility of interest payments. Our simple intuitive
model appears to overcome some of the well-known sho rtcomings of structural
credit risk models.
Keywords: term structure, corporate credit, competitive advantage, value-investing,
credit spread puzzle
JEL classification: G12
Bala Rajaratnam was supported in part by the National Science Foundation under Grant
DMS-1106642. Bala Rajaratnam also gratefully acknowledges Stanford Management
Company (SMC) for useful discussions and funding support. The authors are grateful to the
anonymous referee and the managing Editor for their deep insights as well as their
thoughtful and valuable comments. Correspondence: Myuran Rajaratnam.
European Financial Management, Vol. 23, No. 2, 2017, 183210
doi: 10.1111/eufm.12095
© 2016 John Wiley & Sons, Ltd.
1. Introduction
In the literature, corporat e credit is generally analyse d using one of two types of
models: structural-for m models or reduced-form mo dels. Structural models hav e the
advantage that they explicitly mo del a rms assets, generally assu ming that the rms
assets follow a geometric Brownian motion or so me modication thereof. Re duced-
form models, as the name implies , are much simpler in that they need not formally link
arms assets to the corporate cred it issued by it. Instead, th ey rely on exogenously
specied parameters (such as h azard rates and recovery rates ) to value corporate
In this paper, we present a novel alternative approach to an alysing corporate
credit. Our approach has som e similarities to both stru ctural form models and redu ced
form models but also has some fund amental differences that di stinguish it from these
two classes. Although our mode l parameters have some parall els to reduced form
models, the key difference is that we start off with a model fo r an unlevered rm and
only thereafter we conside r the various claims on the rm. Fu rthermore, our model
parameters are endogenous ly and explicitly linked to t he economics of rm
protability. The key difference between our model and structu ral models is that
we place less signicance on the volatility of the rms assets; instead, we concentrate
on an important factor that her eto has been largely ignored in the literature: the
competitive advantage enjoyedbytherm.
Robert Mertons seminal work (Merton, 1974) stands out as a towering achievement
in the eld of Corporate Debt Valuation. Mertons work assumes that a rms value
follows a diffusion process with constant volatility (as described by the Geometric
Brownian Motion). On the one hand, share prices, rm values and debt values clearly
exhibit volatility and therefore it is not unexpected that volatility plays an integral part in
modern nancial literature. However, on the other hand, asset volatility, which is
employed in structural models, is not directly observable and has to be estimated from
other metrics such as equity volatility.
The eld of behavioural nance also suggests
that a market derived parameter like equity volatility can be an impure signal given that it
can be contaminated by the emotional perception (fear and greed) of the market
participants (see Shleifer, 2000; Tversky and Kahneman, 1974; Thaler, 1993; and
Akerlof and Shiller, 2009 and references therein for further details on behavioural
nance). Furthermore, as pointed out by Eom et al. (2004), standard structural models
have difculty in accurately predicting credit spreads and the major challenge facing
them is to raise model spreads, without resorting to overly aggressive assumptions on
parameters like volatility and leverage, to try and match observed spreads. It is therefore
not unreasonable, in our view, to consider an alternative to asset volatility as a measure of
risk in credit risk models.
Our exposition on Corporate Credit Valuation (presented here) takes a different
approach. In the place of volatility, we employ another oft-forgotten but perhaps equally
A survey on both these classes of credit risk models can be found in, for example, Altman
et al. (2004), Dai and Singleton (2003) and Sundaresan (2000).
To be fair, our competitive advantage parameter, p, is also not directly observable and has to
be inferred from other metrics. However, as we show in the results section, for investment
grade debt, our results are reasonably robust to a sensitivity test on the competitive advantage
parameter, p.
© 2016 John Wiley & Sons, Ltd.
184 Bala Rajaratnam, Kanshukan Rajaratnam and Myuran Rajaratnam

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