## Sharp Probability Tail Estimates for Portfolio Credit Risk

Research output: Contribution to journal › Journal article › peer-review

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**Sharp Probability Tail Estimates for Portfolio Credit Risk.** / Collamore, Jeffrey F.; Silva, Hasitha de; Vidyashankar, Anand N.

Research output: Contribution to journal › Journal article › peer-review

#### Harvard

*Risks*, vol. 10, no. 12, 239, pp. 1-20. https://doi.org/10.3390/risks10120239

#### APA

*Risks*,

*10*(12), 1-20. [239]. https://doi.org/10.3390/risks10120239

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#### Bibtex

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#### RIS

TY - JOUR

T1 - Sharp Probability Tail Estimates for Portfolio Credit Risk

AU - Collamore, Jeffrey F.

AU - Silva, Hasitha de

AU - Vidyashankar, Anand N.

PY - 2022/12/14

Y1 - 2022/12/14

N2 - Portfolio credit risk is often concerned with the tail distribution of the total loss, defined to be the sum of default losses incurred from a collection of individual loans made out to the obligors. The default for an individual loan occurs when the assets of a company (or individual) fall below a certain threshold. These assets are typically modeled according to a factor model, thereby introducing a strong dependence both among the individual loans, and potentially also among the multivariate vector of common factors. In this paper, we derive sharp tail asymptotics under two regimes: (i) a large loss regime, where the total number of defaults increases asymptotically to infinity; and (ii) a small default regime, where the loss threshold for an individual loan is allowed to tend asymptotically to negative infinity. Extending beyond the well studied Gaussian distributional assumptions, we establish that—while the thresholds in the large loss regime are characterized by idiosyncratic factors specific to the individual loans—the rate of decay is governed by the common factors. Conversely, inthe small default regime, we establish that the tail of the loss distribution is governed by systemic factors. We also discuss estimates for Value-at-Risk, and observe that our results may be extended to cases where the number of factors diverges to infinity.

AB - Portfolio credit risk is often concerned with the tail distribution of the total loss, defined to be the sum of default losses incurred from a collection of individual loans made out to the obligors. The default for an individual loan occurs when the assets of a company (or individual) fall below a certain threshold. These assets are typically modeled according to a factor model, thereby introducing a strong dependence both among the individual loans, and potentially also among the multivariate vector of common factors. In this paper, we derive sharp tail asymptotics under two regimes: (i) a large loss regime, where the total number of defaults increases asymptotically to infinity; and (ii) a small default regime, where the loss threshold for an individual loan is allowed to tend asymptotically to negative infinity. Extending beyond the well studied Gaussian distributional assumptions, we establish that—while the thresholds in the large loss regime are characterized by idiosyncratic factors specific to the individual loans—the rate of decay is governed by the common factors. Conversely, inthe small default regime, we establish that the tail of the loss distribution is governed by systemic factors. We also discuss estimates for Value-at-Risk, and observe that our results may be extended to cases where the number of factors diverges to infinity.

UR - https://doi.org/10.3390/risks10120239

U2 - 10.3390/risks10120239

DO - 10.3390/risks10120239

M3 - Journal article

VL - 10

SP - 1

EP - 20

JO - Risks

JF - Risks

SN - 2227-9091

IS - 12

M1 - 239

ER -

ID: 330537869