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Collateralized Borrowing and Default Risk

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Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 189))

Abstract

We study how margin requirements in the collateralized borrowing affect banks’ risk exposure. In a model where a firm’s asset value and margin requirement follow correlated geometric Brownian motions, we derive analytic expressions for firm’s default probability and debt value. Our results show that variations in margin requirements, reflecting funding liquidity shocks in the short-term collateralized lending market, can lead to a significant increase in firms’ default risks, in particular for those firms heavily relying on short-term collateralized borrowing. Moreover, our results imply that reducing margin in liquidity crises can be very effective to restore market lending confidence.

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Notes

  1. 1.

    Former Federal Reserve Chair Ben Bernanke provided a definition in April 2012 at the 2012 Federal Reserve Bank of Atlanta Financial Markets Conference: “Shadow banking, as usually defined, comprises a diverse set of institutions and markets that, collectively, carry out traditional banking functions–but do so outside, or in ways only loosely linked to, the traditional system of regulated depository institutions. Examples of important components of the shadow banking system include securitization vehicles, asset-backed commercial paper (ABCP) conduits, money market mutual funds, markets for repurchase agreements (repos), investment banks, and mortgage companies”.

  2. 2.

    This transformation facilitates the analysis and will make the drift parameter redundant in the numerical experiments. However, with drifts present, the semi close-form solutions are still achievable and it causes no loss of efficiency in the simulations.

  3. 3.

    This result can already be found in [19].

  4. 4.

    Rolling over short-term debt is common practice as firms can reclassify short-term debt as long-term according to the Statement of Financial Accounting Standards.

  5. 5.

    See, e.g., “International banking and financial market developments”, BIS Quarterly Review December 2011, or “The role of margin requirements and haircuts in procyclicality”, CGFS Papers, No 36.

  6. 6.

    Be aware that we use \(n_0=1-m_0\) in our simulations not \(m_0\) directly.

  7. 7.

    There is no authoritative data on the use of haircuts/initial margins in the repo market in either Europe or the US. Table 1 in the research report published by Committee on the Global Financial System Study Group shows margin data in bilateral interviews in various financial centers with various market users, including banks, prime brokers, custodians, asset managers, pension funds and hedge funds. For reference see http://www.bis.org/publ/cgfs36.pdf.

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Acknowledgements

This work was jointly supported by the German Research Foundation through the project Modelling of market, credit and liquidity risks in fixed-income-markets and the UTS Business School Research Funds. The financial support is gratefully acknowledged by the authors.

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Correspondence to Eva Lütkebohmert .

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Appendix

Appendix

Proof of Proposition 3

We first calculate the value of short-term debt \(D_S\),

$$\begin{aligned} \begin{array}{lll} &{} D_S(V,B)\\ =&{} \mathbb {E}\left[ \int \limits _0^{T\wedge \tau } C_S e^{-r_fs}ds\right] + \mathbb {E}\left[ e^{-r_fT}\chi _{\{T<\tau \}}S\right] + \frac{S}{S+L}\mathbb {E}\left[ e^{-r_f\tau }\bar{V}_{\tau }\chi _{\{\tau \le T\}}\right] \\ =&{} T_1 + T_2 + T_3. \end{array} \end{aligned}$$
(A.1)

The first term is

$$\begin{aligned} \begin{array}{lll} T_1 &{}=&{} \mathbb {E}\left[ \int \limits _0^{T\wedge \tau } C_k e^{-r_f s}ds \right] \\ &{}=&{} \frac{C_S}{r_f}\left( 1 - e^{-r_f (T\wedge \tau )} \right) \\ &{}=&{} \frac{C_S}{r_f} -\frac{C_k}{r_f}\mathbb {E}\left[ e^{-r_f T}\chi _{\{\tau> T\}}\right] - \frac{C_S}{r_f}\mathbb {E}\left[ e^{-r_f \tau }\chi _{\{\tau \le T\}}\right] \\ &{}=&{} \frac{C_S}{r_f} \left( 1- e^{-r_fT}P(\tau >T) \right) - \frac{C_S}{r_f} \int \limits _0^T e^{-r_fs} P(\tau \in ds), \end{array} \end{aligned}$$

where the survival probability \(P(\tau >T)\) and the default density function are given in (4) and (5). The second term can be computed as

$$\begin{aligned} T_2 = \mathbb {E}\left[ e^{-r_fT}\chi _{\{T<\tau \}}S\right] = S e^{-r_fT} P(\tau >T). \end{aligned}$$

The last term is

$$\begin{aligned} \begin{array}{lll} T_3 &{}=&{} \frac{RS}{S+L}\mathbb {E}\left[ e^{-r_f\tau }\bar{V}_{\tau }\chi _{\{\tau \le T\}}\right] \\ &{}=&{} \frac{RS}{S+L} \mathbb {E}\left[ e^{-r_f\tau _m}\bar{V}_{\tau _m} \chi _{\{\tau _m<\tau _i<T\}} + e^{-r_f\tau _i}\bar{V}_{\tau _i} \chi _{\{\tau _i<\tau _m<T\}} \right. \\ &{} &{} \left. + e^{-r_f\tau _m}\bar{V}_{\tau _m} \chi _{\{\tau _m<T<\tau _i\}} + e^{-r_f\tau _i}\bar{V}_{\tau _i} \chi _{\{\tau _i<T<\tau _m\}}\right] \\ &{}=&{} \frac{RS}{S+L} \left( \int \limits _0^T \int \limits _0^u e^{-r_fv}\bar{V}_v P_{v<u}(\tau _m\in dv,\tau _i\in du) + \int \limits _0^T \int \limits _u^T e^{-r_fu}\bar{V}_u P_{u<v}(\tau _m\in dv,\tau _i\in du) \right. \\ &{}&{} \qquad \qquad \left. + \int \limits _T ^\infty \int \limits _0^T e^{-r_fv}\bar{V}_v P_{v<u}(\tau _m\in dv,\tau _i\in du) + \int \limits _0^T \int \limits _T^\infty e^{-r_fu}\bar{V}_u P_{u<v}(\tau _m\in dv, \tau _i\in du) \right) , \end{array} \end{aligned}$$
(A.2)

where the joint default density is given in (6) and (7). For the default time \(v<u\), we know

$$\bar{V}_v = e^{\lambda _m v}S,$$

and for \(u<v\)

$$\bar{V}_u = e^{\lambda _i u}B.$$

The long-term debt value will be the same by replacing principal and coupon. The total firm value is the unlevered firm value plus tax shields minus bankruptcy costs

$$\begin{aligned} \begin{array}{ll} &{} v(V,B) \\ = &{} V_0 + \mathbb {E}\left[ \int \limits _0^{T\wedge \tau }\iota (C_S+C_L)e^{-r_fs}ds\right] -(1-R)\mathbb {E}\left[ e^{-r_f\tau }\bar{V}_\tau \chi _{\{\tau \le T\}}\right] \\ = &{} V_0 \frac{\iota (C_S+C_L)}{r_f} \left( 1- e^{-r_fT}P(\tau >T) \right) - \frac{\iota (C_S+C_L)}{r_f} \int \limits _0^T e^{-r_fs} P(\tau \in ds) \\ &{} -\,(1-R) \left( \int \limits _0^T \int \limits _0^u e^{-r_fv}\bar{V}_v P_{v<u}(\tau _m\in dv,\tau _i\in du) \right. \\ &{} \qquad \qquad + \int \limits _0^T \int \limits _u^T e^{-r_fu}\bar{V}_u P_{u<v}(\tau _m\in dv,\tau _i\in du) \\ &{} \qquad \qquad + \int \limits _T ^\infty \int \limits _0^T e^{-r_fv}\bar{V}_v P_{v<u}(\tau _m\in dv,\tau _i\in du) \\ &{} \qquad \qquad \left. + \int \limits _0^T \int \limits _T^\infty e^{-r_fu}\bar{V}_u P_{u<v}(\tau _m\in dv, \tau _i\in du) \right) . \end{array} \end{aligned}$$
(A.3)

Finally, equity value is calculated as total firm value net the debt value

$$\begin{aligned} \begin{array}{lll} E(V,B)= & {} v(V,B) - D(V,B). \end{array} \end{aligned}$$
(A.4)

\(\square \)

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Lütkebohmert, E., Xiao, Y. (2016). Collateralized Borrowing and Default Risk. In: Kallsen, J., Papapantoleon, A. (eds) Advanced Modelling in Mathematical Finance. Springer Proceedings in Mathematics & Statistics, vol 189. Springer, Cham. https://doi.org/10.1007/978-3-319-45875-5_8

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