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Disentangling the impact of securitization on bank profitability

TLDR
In this article, the role played by bank risk, cost of funding, liquidity and regulatory capital in explaining the relationship between securitization and bank profitability was analyzed, and the contribution of each individual transmission channel in the overall impact on bank profitability were identified.
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This article is published in Research in International Business and Finance.The article was published on 2019-01-01 and is currently open access. It has received 15 citations till now. The article focuses on the topics: Capital requirement & Market liquidity.

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Citations
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Security by Design

TL;DR: In supermarkets, food manufacturers fight – even pay – to get the best locations for their products: at eye level, or at the ends of aisles, where they better attract the attention of questing shoppers and therefore are more likely to be bought.
Journal ArticleDOI

Asset securitizations and bank stability: Evidence from different banking systems

TL;DR: In this article, the authors examined the impact of asset securitizations on the performance and financial stability of banks in a dual banking system (i.e., Islamic and conventional) using a unique sample of international banks located in 21 countries.
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Effects of securitization and covered bonds on bank stability

TL;DR: In this paper, the authors investigated the relationship of securitization and covered bonds with bank stability and highlighted that this relationship varies with the level of a bank's involvement in a specific instrument.
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Is there a nonlinear relationship between nonperforming loans and bank profitability? Evidence from dynamic panel threshold

TL;DR: In this paper, the authors examined the threshold effect in the nonperforming loans-profitability nexus within the Nigerian banking industry using the innovative dynamic panel threshold of Seo, Kim, and Kim (2019).
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Impact of the Basel IV framework on securitization and performance of commercial banks in South Africa

TL;DR: Oyetade et al. as mentioned in this paper investigated the impact of the Basel IV framework on securitization and performance of commercial banks in South Africa, and concluded that the impact was minimal.
References
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The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations.

TL;DR: This article seeks to make theorists and researchers aware of the importance of not using the terms moderator and mediator interchangeably by carefully elaborating the many ways in which moderators and mediators differ, and delineates the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena.
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Comparative fit indexes in structural models

TL;DR: A new coefficient is proposed to summarize the relative reduction in the noncentrality parameters of two nested models and two estimators of the coefficient yield new normed (CFI) and nonnormed (FI) fit indexes.
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Significance tests and goodness of fit in the analysis of covariance structures

TL;DR: In this article, a general null model based on modified independence among variables is proposed to provide an additional reference point for the statistical and scientific evaluation of covariance structure models, and the importance of supplementing statistical evaluation with incremental fit indices associated with the comparison of hierarchical models.
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Corporate financing and investment decisions when firms have information that investors do not have

TL;DR: In this paper, a firm that must issue common stock to raise cash to undertake a valuable investment opportunity is considered, and an equilibrium model of the issue-invest decision is developed under these assumptions.
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Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models

TL;DR: For comments on an earlier draft of this chapter and for detailed advice I am indebted to Robert M. Hauser, Halliman H. Winsborough, Toni Richards, several anonymous reviewers, and the editor of this volume as discussed by the authors.
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Frequently Asked Questions (19)
Q1. What have the authors contributed in "Disentangling the impact of securitization on bank profitability" ?

To this end, the authors analyze the role played by bank risk, cost of funding, liquidity and regulatory capital in explaining the relationship between securitization and bank profitability. The authors also show that bank risk, cost of funding, liquidity and regulatory capital individually and jointly act as transmission channels in the securitization-profitability relationship. 

There are some opportunities to extend the current analysis in different dimensions. Additionally, further analysis can be done to investigate the impact of different types of securitization, including ABS or MBS, on bank profitability. 

The outstanding amount of securitization is used as the main explanatory variable for explaining the variation in bank profitability. 

The bank size is expected to positively affect its profitability due to the economies of scale or the ability of large banks to lend more. 

Loutskina (2011) argues that the availability of securitization as an internal source of funds reduces the sensitivity of the bank cost of funding to the availability of other external sources of funds such as traditional liquid funds and deposits. 

Jones (2000) finds that banks securitize, among other reasons, to diversify funding sources, reduce the costs of external financing through debt and deposits, and accordingly to reduce the overall cost of funding. 

Their results show that bank risk, cost of funding, liquidity and regulatory capital work as transmission channels in the securitizationprofitability relationship. 

In the US, securitization origins go back to the early 1970s, when Government National Mortgage Association (Ginnie Mae) started to sell mortgage loans (Ibanez and Scheicher, 2012). 

To measure the on-balance sheet liquidity of the bank, a widely-used measure is core liquidity ratio (CORELIQ) which is estimated as the ratio of cash to total assets, and the liquidity ratio (LIQ) which is estimated as the ratio of cash and securities to total assets. 

The authors estimate the model with clustered standard errors at the bank level, which enables us to use within-bank variations to estimate the parameters of the relationship between securitization and profitability. 

their empirical framework is based on a Structural Equations Modeling (SEM) approach that can simultaneously test the different relationships comprised in the proposed empirical model. 

until mid-2007 it was widely perceived that the US banking system was sound and performing well, particularly because banks capital holdings and profitability appeared to be high and at record levels. 

The increased number of foreclosures and defaults in mortgages led to a decline in the value of securitized assets and reduced investors’ appetite for such securities and accordingly problems within the US banking industry (Gerardi et al., 2008). 

With respect to bank risk measures, panel D shows that risk-weighted assets to total assets ratio has a high standard deviation of 0.270 compared to 0.021 of the charge-offs ratio. 

In so doing, the authors argue that the impact of securitization on bank profitability is transmitted through four main channels, namely bank risk, cost of funding, liquidity and regulatory capital. 

On the other hand, securitization may increase bank risk due to the increase in risk taking and recourse or other seller-provided credit enhancements (Higgins and Mason, 2004). 

In this regard, the authors follow the method applied by Iacobucci (2008) to estimate the percentage of indirect effect using the estimated indirect and direct path coefficients as follows:34 = 678 9:7678 9:7 1 6; (8)where km is the indirect effect that is transmitted through mediator m as a percentage of total effect. 

The next step in testing the hypothesized mediation model is to construct and test a model that incorporates all the four proposed mediators at the same time. 

The final step in analyzing the theoretical mediation model is computing the percentage contribution of each mediator in explaining the variation in bank profitability.