Skip to content
All library documents

Pricing First-to-Default Basket Swaps and Premium Payments

Article Quant Q&A · Author: Ryan J. Shrott

Summary

The document explains how to value the protection and premium legs of a homogeneous basket default swap when constituent default times are independent and exponentially distributed. It derives the first-to-default survival probability and density, then discounts a recovery-adjusted payment either at the default time or at the next scheduled premium date. The latter convention groups defaults by payment period.

For the premium leg, scheduled coupons are paid only if the basket survives to the payment date, with accrued premium added when default occurs during a period. The example approximates accrued premium by assuming default occurs halfway through that period. The exposition also gives a general order-statistic survival expression for later defaults, but develops leg valuation mainly for the first-to-default case. Results depend on the assumed independence, constant hazard and discount rates, payment timing, and recovery convention; these formulas do not incorporate correlated defaults or more detailed credit-market features.

Key ideas

  • Independent exponential default times imply a first-to-default hazard equal to the sum of constituent hazards.
  • The protection leg is discounted using either the actual default time or the next payment date, depending on settlement convention.
  • Premium valuation includes scheduled payments conditional on survival and may include accrued premium after an in-period default.
  • The midpoint approximation simplifies accrued premium but is not an exact valuation for finite payment intervals.
  • Order statistics can describe the timing of the m-th default, though the worked leg calculations focus on first default.

Tags

Full text
# Pricing homogeneous Basket Default Swap


# Pricing homogeneous Basket Default Swap












> Consider a basket with $K=10$ names. Default times of the names, $\tau_k$, are i.i.d. random variables with distribution $P(\tau_k \leq t) = 1 - e^{-\lambda t}$. Suppose that each name in the basket has a notional $N_k = N$, the basket notional, $N=KN$, the discount factors, $D(t) = exp(-rt)$. Denote by $s$ the payment rate (also called the spread). Denote by $T$ the maturity of the $m$-to-default BDS written on this basket. Assume that the number of payment dates in $M$. Find the value of the default and premium legs for $m=1$ and $m=2$.

My attempt: For $m=1$: Let the random variable $\tau^* = \min_{i\in \{1,...,K \}}\tau_i$ denote the first order statistic. The distribution of $\tau^*$ is easily calculated: $$ f_{\tau_1^*}(t) = {K \choose 1} f_{\tau}(t) F_{\tau}(t)(1-F_{\tau}(t))^{k-1}$$

Let $T_1,...T_M$ denote the term structure of payment dates.

The event {$\tau^*<T_i$} implies that the first default occurred before $T_i$.

For the default leg, I think: $$V_0^{Def} = E_0^{Q}[\sum_{i=1}^Me^{-rT_i} s *N*\mathbb{1}_{{0<\tau ^* <T_i}}]$$

But I unsure about this logic. I have little background with these financial terms.

## Answer by Gordon (score 4, accepted)

https://quant.stackexchange.com/a/22296

Let $\tau_{(1)} = \min(\tau_1, \ldots, \tau_K)$ be the first-to-default time. Moreover, for $1< m \le K$, let \begin{align*} \tau_{(m)} = \min\left(\tau_k: k=1, \ldots, K, \tau_{k} > \tau_{(m-1)}\right). \end{align*} be the $m^{\rm th}$-to-default time. In particular, $\tau_{(K)} = \max(\tau_1, \ldots, \tau_K)$. Note that, for $t \ge 0$, \begin{align*} P\left(\tau_{(1)} > t\right) &= \prod_{i=1}^K P(\tau_i > t)\\ &=e^{-K \lambda t}. \end{align*} Then, the density function is of the form \begin{align*} \frac{d P\left(\tau_{(1)} \le t\right)}{dt} &= K \lambda\, e^{-K \lambda t}. \end{align*} Generally, for $1 \le m \le K$, the event $\left(\tau_{(m)} > t\right)$ happens as long as there are $K-m+1$ defaults happen later than time $t$, while the remaining $m-1$ defaults happens earlier than $t$. That is, \begin{align*} P\left(\tau_{(m)} > t\right) &= \sum_{j=K-m+1}^K \sum_{\pi \in \Pi_j}\prod_{i_k \in \pi}P(\tau_{i_k} > t) \prod_{i_l \not\in \pi}P(\tau_{i_l} \le t)\\ &=\sum_{j=K-m+1}^K {K \choose j} e^{-j\lambda t} \Big(1-e^{-(K-j)\lambda t} \Big), \end{align*} where $\Pi_j$ denotes the family of subsets of $(1, \ldots, K)$ consisting of $j$ elements. Here, $ \prod_{i_l \not\in \pi}P(\tau_{i_l} \le t)=1$, if $j=K$. The density function is then given by \begin{align*} \sum_{j=K-m+1}^K {K \choose j} \lambda\, e^{-j\lambda t}\Big(j-Ke^{-(K-j)\lambda t} \Big). \end{align*} We consider the first-to-default case below, that is, $m=1$. The general $m^{\rm th}$-to-default case is similar based on the density function above.

Let $R$ be the recovery rate (e.g., R = 40 %). Note that the default leg is also called the protection leg.

Default Leg. The value of the default leg, if we assume that the default payment is made at the default time, is given by \begin{align*} (1-R)N \, E\Big( D\big(\tau_{(1)}\big) 1_{0 < \tau_{(1)} \le T} \Big) &= (1-R)N K \lambda \int_0^T e^{-(r+K \lambda)t}dt\\ &=\frac{(1-R)N K \lambda}{r+K \lambda}\left(1- e^{-(r+K \lambda)T}\right). \end{align*} However, if we assume that the default payment is made at the next premium payment date, then the value of the default leg is given by \begin{align*} (1-R)N \, E\left(\sum_{j=1}^M D(T_j) 1_{T_{j-1} < \tau_{(1)} \le T_j} \right) &= (1-R)N K \lambda\sum_{j=1}^M e^{-rT_j} \int_{T_{j-1}}^{T_j} e^{-K \lambda t}dt\\ &=(1-R)N \sum_{j=1}^M e^{-rT_j} \left(e^{-K \lambda T_{j-1}} - e^{-K \lambda T_j}\right). \end{align*}

Premium Leg. For $j=1, \ldots, M$, let $\Delta T_j = T_j - T_{j-1}$. We assume that the premium $s$, for the payment period $(T_{j-1}, \, T_j]$ $(j=1, \ldots, M)$, is paid at the end date $T_j$. Moreover, the accrued interest to default, $s(\tau_{(1)}-T_{j-1}) 1_{T_{j-1} < \tau_{(1)} \le T_j}$, is also paid at $T_j$. Then value of the premium leg is then given by \begin{align*} &\ N s E\left(\sum_{j=1}^M D(T_j) \Big[\Delta T_j 1_{\tau_{(1)} > T_j} + \big(\tau_{(1)}-T_{j-1}\big) 1_{T_{j-1} < \tau^* \le T_j} \Big] \right) \\ =& \ N s\sum_{j=1}^M e^{-r T_j} \bigg[\Delta T_j e^{-K \lambda T_j} + K \lambda \int_{T_{j-1}}^{T_j}(t-T_{j-1})e^{-K \lambda t} dt \bigg]\\ \approx& \ N s\sum_{j=1}^M e^{-r T_j} \bigg[\Delta T_j e^{-K \lambda T_j} +\frac{\Delta T_j}{2} \left(e^{-K \lambda T_{j-1}} - e^{-K \lambda T_j}\right) \bigg]. \end{align*} For the last step, we basically assume that, if the default happens, it happens in the middle of the payment period.

Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.