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    Monitoring transmission of systemic risk: Application of partial least squares structural equation modeling in financial stress testing
    (2018-06)
    Avkiran, Necmi K.
    ;
    Ringle, Christian M.
    ;
    Low, Rand
    Regulators need a method that is versatile, is easy to use and can handle complex path models with latent (not directly observable) variables. In a first application of partial least squares structural equation modeling (PLS-SEM) in financial stress testing, we demonstrate how PLS-SEM can be used to explain the transmission of systemic risk. We model this transmission of systemic risk from shadow banking to the regulated banking sector (RBS) using a set of indicators (directly observable variables) that are sources of systemic risk in shadow banking and consequences of systemic risk measured in the RBS. Procedures for predictive model assessment using PLS-SEM are outlined in clear steps. Statistically significant results based on predictive modeling indicate that around 75% of the variation in systemic risk in the RBS can be explained by microlevel and macrolevel linkages that can be traced to shadow banking (we use partially simulated data). The finding that microlevel linkages have a greater impact on the contagion of systemic risk highlights the type of significant insight that can be generated through PLS-SEM. Regulators can use PLS-SEM to monitor the transmission of systemic risk, and the demonstrated skills can be transferred to any topic with latent constructs.
    Publicationtype: Journal Article
      188
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    Partial Least Squares Structural Equation Modeling : Recent Advances in Banking and Finance
    (Springer, 2018)
    Avkiran, Necmi K.
    ;
    Ringle, Christian M.
    This book pulls together robust practices in Partial Least Squares Structural Equation Modeling (PLS-SEM) from other disciplines and shows how they can be used in the area of Banking and Finance. In terms of empirical analysis techniques, Banking and Finance is a conservative discipline. As such, this book will raise awareness of the potential of PLS-SEM for application in various contexts. PLS-SEM is a non-parametric approach designed to maximize explained variance in latent constructs. Latent constructs are directly unobservable phenomena such as customer service quality and managerial competence. Explained variance refers to the extent we can predict, say, customer service quality, by examining other theoretically related latent constructs such as conduct of staff and communication skills. Examples of latent constructs at the microeconomic level include customer service quality, managerial effectiveness, perception of market leadership, etc.; macroeconomic-level latent constructs would be found in contagion of systemic risk from one financial sector to another, herd behavior among fund managers, risk tolerance in financial markets, etc. Behavioral Finance is bound to provide a wealth of opportunities for applying PLS-SEM. The book is designed to expose robust processes in application of PLS-SEM, including use of various software packages and codes, including R. PLS-SEM is already a popular tool in marketing and management information systems used to explain latent constructs. Until now, PLS-SEM has not enjoyed a wide acceptance in Banking and Finance. Based on recent research developments, this book represents the first collection of PLS-SEM applications in Banking and Finance. This book will serve as a reference book for those researchers keen on adopting PLS-SEM to explain latent constructs in Banking and Finance.
    Publicationtype: Book
      139
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      78