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A new approach to optimal capital allocation for RORAC maximization in banks

机译:银行RORAC最大化的最优资本配置新方法

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We introduce a new model for optimal internal capital allocation, which would allow banks to maximize their Return on Risk-Adjusted Capital (RORAC) under regulatory and capital constraints. We extend the single period model of Buch et al., (2011) to a multi-period model and improve its forecasting accuracy by including the debt effect and Bayesian learning innovations. The empirical application shows that our model significantly improves the RORAC of a sample of banks listed in the S&P 500 index. Crown Copyright (C) 2019 Published by Elsevier B.V. All rights reserved.
机译:我们引入了一种用于优化内部资本分配的新模型,该模型将使银行在监管和资本约束下能够最大化其风险调整后资本收益率(RORAC)。我们将Buch等人(2011)的单周期模型扩展到多周期模型,并通过包括债务效应和贝叶斯学习创新来提高其预测准确性。实证应用表明,我们的模型显着改善了标普500指数中所列银行样本的RORAC。官方版权(C)2019由Elsevier B.V.保留所有权利。

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