☆ 4.5 Article

Constructing early warning indicators for banks using machine learning models

NORTH AMERICAN JOURNAL OF ECONOMICS AND FINANCE (2024)

Machine learning for liquidity risk modelling: A supervisory perspective

Pedro Guerra et al.

Summary: The purpose of an effective liquidity risk assessment policy is to ensure a credit institution's ability to fulfill cash flow obligations amid uncertainties. This study investigates the use of machine learning techniques to model liquidity risk in the Portuguese banking sector and finds that extreme gradient boosting (XGBoost) outperforms other methods in classification.

ECONOMIC ANALYSIS AND POLICY (2022)

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Article Economics

Risk committee complexity and liquidity risk in the European banking industry

Simona Galletta et al.

Summary: The study shows that the risk committee plays a crucial role in adequately protecting banks against liquidity risk. The presence of a certain number of risk supervisors helps reduce liquidity risk and mitigate risk-taking behaviors.

JOURNAL OF ECONOMIC BEHAVIOR & ORGANIZATION (2021)

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Review Management

Multivariate portfolio optimization under illiquid market prospects: a review of theoretical algorithms and practical techniques for liquidity risk management

Mazin A. M. Al Janabi

Summary: This study focuses on the theoretical foundations for multivariate portfolio optimization algorithms under illiquid market conditions, examining the modeling parameters of LVaR technique and integrating asset liquidity risk into the models. It provides detailed operational methodology and discusses potential applications for the research.

JOURNAL OF MODELLING IN MANAGEMENT (2021)

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Article Business, Finance