Attaining stochastic optimal control over debt ratios in U.S. markets

We propose a refined dynamic programming model based on a hidden Markov chain formulation and a nonlinear filtering technique to calculate the optimal debt ratio for public and private sectors for different scenarios. We then conduct the empirical analysis of the U.S. markets in real estate and equi...

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Veröffentlicht in:Review of quantitative finance and accounting 2023-10, Vol.61 (3), p.967-993
1. Verfasser: Liu, Wei-han
Format: Artikel
Sprache:eng
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Zusammenfassung:We propose a refined dynamic programming model based on a hidden Markov chain formulation and a nonlinear filtering technique to calculate the optimal debt ratio for public and private sectors for different scenarios. We then conduct the empirical analysis of the U.S. markets in real estate and equities during 1991.Q1 and 2020.Q1, comparing them with the theoretical results. It indicates that U.S. households and governments spent more than they can afford. While households reduced their debt ratio during times of economic distress, the public sector hiked its debt ratio to stimulate the economy. The policy effect took a long time to accumulate, and the outcome was lower than expected to revitalize the economy in time.
ISSN:0924-865X
1573-7179
DOI:10.1007/s11156-023-01173-0