Arka P. Bandyopadhyay releases paper on distinguishing commercial mortgage default types with DNNs
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Arka P. Bandyopadhyay published an academic paper that uses deep neural networks (DNN) to distinguish liquidity-constrained defaults from strategic defaults, based on proprietary panel data of commercial mortgages from 1998 to 2021. The study finds that, under delinquency conditions, property net operating income (NOI) has a more significant impact on default rates than the loan-to-value (LTV) ratio, and the threshold dividing the two types of defaults remained stable during the 2008 financial crisis and the 2020-2021 COVID-19 commercial real estate shock.
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- arXiv q-finHow to Distinguish Liquidity-Constrained Default from Strategic Default Using Deep Learning
Researchers used proprietary panel data of commercial mortgages from 1998 to 2021 and adopted deep neural networks (DNN) to distinguish liquidity-constrained default from strategic default. The study found that, under delinquency conditions, property net operating income (NOI) has a more significant impact on default rates than loan-to-value ratio (LTV), and the threshold for dividing the two types of defaults remained stable during the 2008 financial crisis and the 2020-2021 COVID-19 commercial real estate shock.
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