Complexity, Standardization, and the Design of Loan Agreements

Ganglmair, Bernhard; Wardlaw, Malcolm

doi:10.2139/ssrn.2952567

Cited by 9 publications

(9 citation statements)

References 37 publications

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“…Instead, we employ LDA to measure the extent to which digitalization is discussed in the reports. Although there is no clear guidance in the literature on how to select the optimal number of topics as most researchers apply different rules based on the task at hand, in many applications a number of topics between 10 and 50 seems to be appropriate (see, e.g., Bao & Datta, 2014; Bellstam et al, 2020; Ganglmair & Wardlaw, 2017; Weiss Hanley & Hoberg, 2019; Israelsen, 2014; Lopez‐Lira, 2019).…”

Section: Measuring Digitalization Using Ldamentioning

confidence: 99%

“…More recent papers (e.g., Hanley & Hoberg, 2010; Hoberg & Maksimovic, 2015; Hoberg et al, 2014; Jegadeesh & Wu, 2013; Ke et al, 2017, 2019) conduct text‐based analyses to examine a wide variety of finance research questions. Intriguingly, within the field of text analysis and machine learning, LDA is becoming more and more popular (see, e.g., Ganglmair & Wardlaw, 2017; Goldsmith‐Pinkham et al, 2016; Hoberg & Lewis, 2017; Huang et al, 2018; Lopez‐Lira, 2019). Within this growing strand of literature, our paper is most closely related to Bellstam et al (2020) and Lowry et al (2019), who derive topics based on LDA and employ the KL divergence as a measure of similarity between probability distributions.…”

Section: Introductionmentioning

confidence: 99%

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Estimating the relation between digitalization and the market value of insurers

Fritzsch

Scharner

Weiß

2021

J of Risk & Insurance

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We analyze the relation between digitalization and the market value of US insurance companies. To create a text‐based measure that captures the extent to which insurers digitalize, we apply an unsupervised machine learning algorithm—Latent Dirichlet Allocation—to their annual reports. We show that an increase in digitalization is associated with an increase in market valuations in the insurance sector. In detail, capital market participants seem to reward digitalization efforts of an insurer in the form of higher absolute market capitalizations and market‐to‐book ratios. Additionally, we provide evidence that the positive relation between digitalization and market valuations is robust to sentiment in the annual reports and the choice of the reference document on digitalization, both being issues of particular importance in text‐based analyses.

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Section: Measuring Digitalization Using Ldamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Estimating the relation between digitalization and the market value of insurers

Fritzsch

Scharner

Weiß

2021

J of Risk & Insurance

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“…To prevent potential disputes between contracting parties, contracts are intentionally written with many details and a large number of clauses presenting promises, obligations and processes (Ariño and Reuer, 2006;Poppo and Zenger, 2002). However, Ganglmair and Wardlaw (2017) reject the idea that loan provisions are purely made from "boilerplate" language that can be replicated in every contract. They find that contracts are customized to suit the needs of different borrowers, and the design of loan contracts is separately negotiated for each borrowing firm.…”

Section: Introductionmentioning

confidence: 99%

Confidentiality in loan credit agreements

Nguyen

Pacheco

2021

IJMF

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PurposeThis study has two primary objectives. First, it analyzes the information content of confidentiality strictness in corporate loan credit agreements. Second, it examines how confidentiality strictness impacts covenant design, lending syndicate structure and loan pricing.Design/methodology/approachUsing a sample of 6,327 loan credit agreements originated by US public firms in the period of 1996–2017, this study measures the confidentiality strictness in loan contracts using textual analyses that capture the appearance of confidentiality-related words and the length of confidentiality provision. All regressions include relevant loan characteristics, firm-specific accounting variables, industry and year fixed effects. To address the endogeneity concern, the paper uses borrowing firms' rival cash holdings and R&D expenditures to instrument for confidentiality strictness in two-staged least square regressions.FindingsBorrowers which have higher R&D and operate in more competitive product markets have tighter confidentiality policies. Furthermore, this study reveals that confidentiality strictness is negatively associated with the imposition of financial covenants, especially performance covenants. Loan contracts for borrowers with stricter confidentiality on average have more relaxed covenant intensity, measured by the number of covenants. The study also shows that stricter confidentiality attracts finance companies, which have strong expertise in product markets of their parent firms, into the lending syndicate. However, confidentiality-conscious borrowers with higher degree of information asymmetry are subject to higher loan spreads.Originality/valueThis study provides the first examination of confidentiality policies in loan contracts and supports the idea that loan provisions are not simply made of “boilerplate” language. The results suggest that, for confidentiality-sensitive borrowers, the greater exposure to product market competition helps control managerial slack and substitute monitoring from financial markets.

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“…Incompleteness might also be inevitable due to parties' limited cognition (Tirole (2009)). Despite a large theoretical literature, our empirical understanding of why contracts are incomplete is still in its infancy (Chiappori and Salanié (2003); Eigen (2012); Ganglmair and Wardlaw (2017); Gennaioli and Ponzetto (2017); Iyer and Schoar (2015); Buchak (2016); Jeffers and Lee (2019); Gennaioli, La Porta, Lopez-de Silanes, and Shleifer (2020)).…”

Section: Introductionmentioning

confidence: 99%