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A characterization of the Lender's position in the context of contractual loan conditions

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  • Michael L. McIntyre

    (Carleton University)

Abstract

In this paper, we use a recombining binomial tree to simultaneously model, as time unfolds, the amount owing on a loan, the theoretical value of the loan, and the value of the borrower's assets that back up the loan. We do so because this approach illustrates the operation of credit conditions in a way that we cannot see in any other work. Therefore, the approach is unique and fills a gap in the literature. In our setup, we can assess the lender's exposure to credit risk at every node in the tree and flexibly impose a broad range of loan-to-value covenant thresholds. From this, we can observe the relationship between the choice of threshold and expected credit losses. Importantly, our results provide valuable insights for loan officers who specify and act on loan conditions. Specifically, we demonstrate a window of opportunity within which the lender can protect its interests, provided loan conditions empower it to act. We provide examples of strict, medium, and loose loan conditions and evaluate the effect of these on credit riskiness and loan pricing. The main conclusion is that loan covenants are better linked to the declining theoretical value of a loan than to impending asset shortfalls. We also demonstrate how elevated leverage and increased volatility of the value of the firm's assets increase the need for lenders to write conditions that trigger well before credit losses are manifest and act on them expeditiously.

Suggested Citation

  • Michael L. McIntyre, 2023. "A characterization of the Lender's position in the context of contractual loan conditions," SN Business & Economics, Springer, vol. 3(8), pages 1-27, August.
    • Handle: RePEc:spr:snbeco:v:3:y:2023:i:8:d:10.1007_s43546-023-00522-4
    DOI: 10.1007/s43546-023-00522-4
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