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Abstract and Applied Analysis
Volume 2014 (2014), Article ID 412890, 12 pages
Total Return Swap Valuation with Counterparty Risk and Interest Rate Risk
1School of Business Information, Shanghai University of International Business and Economics, Shanghai 201620, China
2Department of Mathematics, Shanghai Jiaotong University, Shanghai 200240, China
Received 17 January 2014; Accepted 28 April 2014; Published 28 May 2014
Academic Editor: Imran Naeem
Copyright © 2014 Anjiao Wang and Zhongxing Ye. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
We study the pricing of total return swap (TRS) under the contagion models with counterparty risk and the interest rate risk. We assume that interest rate follows Heath-Jarrow-Morton (HJM) forward interest rate model and obtain the Libor market interest rate. The cases where default is related to the interest rate and independent of interest rate are considered. Using the methods of change of measure and the “total hazard construction,” the joint default probabilities are obtained. Furthermore, we obtain the closed-form formulas of TRS under different contagion models, respectively.
Total return swap (TRS), as a type of credit derivatives and a financing and leverage tool, is an important off-balance sheet tool, particularly for hedge funds and for banks seeking additional fee income. The corporate bonds and their credit derivatives are typically financial tools in the markets which undertake and avoid the credit risk of the companies. Therefore, the key of management of credit risk is the fair pricing of credit derivatives. Especially after 2007 financing crisis, the contagion effect of credit risk has attracted huge attention of financial market regulators and financial institutions. To price credit derivatives, default contagion models are developed rapidly in order to make them more realistic after the subprime mortgage crisis.
The approaches of modeling the pricing of credit derivatives are mainly the value-of-the-firm (or structural) approach and the intensity-based approach (or reduced form approach). The structural model is based on the work of Merton , Black and Cox , and Geske : the default occurs when the firm assets are insufficient to meet payments on debt or the value of the firm asset falls below a prespecified level.
Reduced-form models are developed by Artzner and Delbaen , Duffie et al. , Jarrow and Turnbull , and Madan and Unal . Duffie and Lando  show that a reduced-form model can be obtained from a structural model with incomplete accounting information. The simplest type of reduced-form model is where the default time or the credit migration is the first jump of an exogenously given jump process with an intensity. In Jarrow et al. , the intensity for credit migration is constant; see also Litterman and Iben  for a Markov chain model of credit migration. In the papers by Duffie et al. , Duffie and Singleton , and Lando , the intensity of default is a random process. The common feature of the reduced-form models is that default cannot be predicted and can occur at any time. Therefore, reduced-form models have been used to price a wide variety of instruments. In recent years, some papers on estimating the parameters of these models are given by Collin-Dufresne and Solnik  and Duffee . Jarrow and Yu  set up a reduced-form model in which estimation can be based on bond prices as well as credit default swap prices. A systematic development of mathematical tools for reduced-form models has been given by Elliott et al. . Jamshidian  develops change of numeraire methodology for reduced-form models.
A TRS is a bilateral financial contract between a total return payer and a total return receiver. One party (the total return payer) pays the total return of a reference security (or reference securities) and receives a form of payment from the other party (the receiver of the total rate of return). Often payment is a floating rate payment, a spread to LIBOR. The reference assets can be indices, bonds (emerging market, sovereign, bank debt, mortgage-backed securities, or corporate), loans (term or revolver), equities, real estate receivables, lease receivables, or commodities. Ye and Zhuang  consider the pricing of TRS only when reference asset defaults; they obtain TRS pricing formula when default is independent of the interest rate. When default is related to the interest rate, using the hybrid model given in Das and Sundaram , they model default time and the interest rate and give the Monte Carlo simulation result.
In this paper, we consider the counterparty default contagion risk between total return receiver (firm ) and the reference asset (firm ) and study two-firm contagion models. The cash flow of a TRS in this model is provided by Figure 1.
Suppose that firm (a corporate bond investing firm, credit protection buyer) holds a corporate bond (reference asset) issued by firm (a corporate bond issuer) (refer to 2A in Figure 1), and firm is subject to default. At bond maturity, if firm does not default, it will pay the bond principle and interest to firm (refer to 2B). On the other hand, to hedge the default risk of firm , firm and firm (credit protection seller, subject to default also) enter into a TRS contract. If firm has no default, firm will make its total return to firm (refer to 2C), and, in exchange, firm gives the Libor plus a spread to (refer to 2D). Firm promises to compensate for its loss in the event of default of firm (refer to 2E).
The structure of this paper is organized as follows. In Section 2, we give the basic setup and HJM forward interest rate model. In Section 3, we study the two-firm contagion models when default is independent of stochastic interest rate and obtain the closed-form formulas of TRS. In Section 4, we consider the case that default is related to interest rate. Using the “total hazard” approach, joint survival probabilities are derived and analytic formulas are obtained under two-firm contagion models. Section 5 is the conclusion.
2. Basic Setup and HJM Forward Interest Rate Model
We consider a filtered probability space which is an uncertain economy with a time horizon of , satisfying the usual conditions of right-continuity and completeness with respect to -null sets, where and is an equivalent martingale measure under which discounted bond prices are martingales. We assume the existence and uniqueness of so that bond markets are complete and there is no arbitrage, as shown in discrete time case by Harrison and Kreps  and in continuous time case by Harrison and Pliska . Subsequent specifications of the model are all under the equivalent martingale measure (or risk neutral measure) .
On this probability space there is an -valued process , which presents dimensional economy-wide state variables. In this paper, we consider the only one state variable which is the interest rate denoted by . There are also two point processes, , initialized at 0, representing the default processes of the firm and firm , respectively, such that the default of the firm occurs when jumps from 0 to 1.
According to the information contained in the state variables and the default processes, the enlarged filtration is defined by where are the filtrations generated by and , respectively.
Let where contains complete information on the state variables and the default processes of all firms up to time other than that of the th firm.
Let denote the default time of firm ; namely, is the first jump time of , which can be defined as where is independent of .
According to the Doob-Meyer decomposition, we have that is a -martingale.
Due to the impact of counterparty risk, the default intensities and of firms and are no longer independent under the condition . The conditional survival probability and the unconditional survival probability of firm are given by respectively.
As a type of market risk, interest rate risk analysis is almost always based on simulating movements in one or more yield curves using the Heath-Jarrow-Morton (HJM) framework to ensure that the yield curve movements are both consistent with current market yield curves and such that no riskless arbitrage is possible. HJM model was developed in early 1992 by Heath et al. . In this paper, we assume the default free interest rate is stochastic forward interest rate , which follows the HJM model where is the drift term and is the volatility term, and they are both stochastic. For every fixed time , they are adapted processes to .
The arbitrage free condition  shows that the Brown movement under each real probability measure can be transformed into the Brown movement under the risk neutral measure. For simplification, in this paper, we assume the Brown movement is standard under the risk neutral measure , where satisfies
The solution of (9) is where is the initial forward interest rate curve, which is known.
At time the instantaneous interest rate . is the discounted process. Let be the time- value of a zero-coupon bond with face value 1 at maturity ; we have Under the risk neutral measure , satisfies the following differential equation:
Denote to be the time- locked investment yield curve from to ; then, For , is called forward Libor interest rate, and, for , is called spot Libor interest rate. is the duration of Libor, normally 0.25 year or half year.
In the next two sections of this paper, we discuss the pricing of TRS with default risk and interest rate risk under different contagion models.
3. TRS Valuation When Default Is Independent of the Interest Rate
Assume that reference asset is a defaultable coupon bond with face value 1 and the same maturity with TRS contract. are bond interest payment dates, where , for , , .
Denote to be the time- cash flow of TRS payer, where are the interest payments at time and is the sum of interest payment and value-added of the bond at time , which are all determined at . Let be notional principal, and is the maturity of Libor interest rate, the same with bond’s payment cycle , namely, . For simplification, the default recovery rate of reference asset is 0.
At time , for TRS payment leg, the discounted expectation of the cash flow is
At time , for TRS recipient leg, the discounted expectation of the cash flow is where is the expectation under risk neutral measure , is the length of settlement period, and is settlement date. is time- locked -Libor interest rate. is the TRS spread and is the discounted factor.
We assume the market is complete; namely, there is no arbitrage. Therefore, according to the arbitrage-free principle, we have The general pricing formula of TRS is derived as
3.1. TRS Valuation under Two-Firm Looping Default Contagion Model
In this subsection we assume that the default intensities of credit protection seller and reference asset are given, respectively, by where and are nonnegative, satisfying and .
With the result in Leung and Kwok , the joint survival probability and the joint density of default time are given by respectively.
When the default process and the interest rate process are independent, by computing formula (18), we can obtain the following result.
Proof. By the arbitrage free principle, the price formula (18) becomes To obtain the analytic solution of , we need to compute the following three expectation values: where Substitute , , and into formula (24), and we obtain We complete the proof.
Remark 2. From (23), we can conclude that when the length of settlement period is zero, the swap rate is only related to the systematic factors and , irrelative to the default contagion between two firms.
3.2. TRS Valuation under Two-Firm Attenuation Contagion Model
In this subsection, we consider the default contagion to have the hyperbolic attenuation effect. Default intensities of firms and have the following forms: where ,, , and are nonnegative, satisfying and . and reflect the impact strength of the counterparty and and show the attenuation speed of one party default on the other party. For , the model becomes the looping default model (19)-(20).
Then the expression of is given by the following theorem.
Remark 4. Combining formula (34) with formula (23), we can conclude that firm ’s default contagion on firm has effect in the pricing of TRS (there is in formula (34)). However, firm ’s default contagion on firm has no effect in the pricing of TRS (there is no in (34)). Therefore, in the complex contagion model, we can assume that the reference asset is the primary firm, and the protection seller is the secondary firm.
4. TRS Valuation When Default Is Related to the Interest Rate
Empirical studies show that in the vast majority of cases default is related to the interest rate or, in other words, credit risk is related to interest rate risk. In this section, we assume that their correlation is described by default intensities. For simplification, we assume that the length of the reference asset’s settlement period is zero.
4.1. TRS Valuation under Two-Firm Looping Default Contagion Model
We consider that default intensities of firms and have the following form: where , ,, and are nonnegative, satisfying and . and satisfies model (9).
The joint conditional density function is where is the cumulative interest rate process and is the filter generated by up to .
When default is related to interest rate, computing expectations in formula (18) becomes complicated. We give the following lemma first.
Lemma 5. The interest rate process is given by (9), , for . Denote then,
We can deduce
By using the formula
And substituting (45), (46) into (47), we can obtain (43).
Formula (43) can be rewritten as Similar to the computation of (42), (43) can be obtained, and we omit it here.
Since the length of settlement period for reference asset is 0; namely, if firm has no default, pays compensation for ’s loss immediately once defaults, thus (18) becomes
The price of TRS is given by the theorem below.
Proof. Consider To compute (48), we need to only deduce the following three expectation values: where Substituting the expression (14) of Libor interest rate into the formula above, we have Thus, substituting (52)–(54) into (48), we obtain The proof is complete.
Remark 7. From the expression (49), the price of TRS is related to the default free interest rate risk (because there are and ). So the interest rate risk is not negligible in the pricing of credit derivatives.
4.2. TRS Valuation under Two-Firm Attenuation Contagion Model
In this subsection, besides that default is related to interest rate, we assume that default contagion has the hyperbolic attenuation effect. Default intensities of firms and are described as follows: where , , , , , and are nonnegative, satisfying and . When , model is simplified to the looping default model (38).
To obtain the analytic solution of , we consider the following simplified model: By the result in , the joint conditional survival probability of under the model (57) is given by and the joint conditional density function is given by
Under the model (57), the price formula of is given by
Combining with Lemma 5, we can obtain the price of TRS, and the result is the following theorem.
Proof. From (60), to obtain the analytic solution of , we need to only compute three expectation values: where Substituting expressions (63) of , , and into (60), we can obtain (61). We complete the proof.
In this paper, we mainly study the pricing of TRS under the framework of two-firm contagion models and HJM forward interest rate model. We obtain the analytic price expressions of TRS, respectively, based on whether the default is related to the interest rate. From these expressions, we claim that both default risk and the default-free interest rate risk have effects on the valuation of TRS. Moreover, the contagion effect between the reference asset and the protection seller is not ignorable. Therefore, the models in our paper have certain practical significance. We will further discuss other contagion models and interest rate models and compare them with the models in this paper by using Monte Carlo simulation.
Conflict of Interests
The authors declare that there is no conflict of interests regarding the publication of this paper.
The research was supported by the National Natural Science Foundation of China under Grants no. 11326168 and no. 11171215 and Yangcai Project (no. YC-XK-13106).
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