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Early commercial mortgage terminations and real estate supply constraints

Tong, L. M. M. (2019) Early commercial mortgage terminations and real estate supply constraints. PhD thesis, University of Reading

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To link to this item DOI: 10.48683/1926.00086318

Abstract/Summary

The early termination of commercial mortgages represents a financial risk for lenders. Default and prepayment risks are the two main options priced in the main literature, where competing risk models are adopted to analyze both risks simultaneously. In this research, we examines the impact of collateral underlying real estate supply constraints on early mortgage termination. To achieve this, we suggest three original ideas. First, as we need to estimate supply elasticities of office markets in the US, we develop a mismatch conceptual model estimating long run supply elasticity and computing the correlation between structural vacancy and supply constraints. The results imply that low controlling power of landlords reduces the flexibility in adjusting equilibrium vacancies to respond to market shocks. Second, we suggest adopting the installment option valuation model for pricing early mortgage termination options. Early mortgage termination (joint mortgage default and prepayment) is analogous to an American continuous installment option embedded with straddle or strangle like payoff as this can capture the decision path that keeps the option alive by making scheduled mortgage payments. Third, we suggest two pairs of early termination options: (1) mortgage default vs restructuring; and (2) full prepayment in cash vs defeasance in empirical analysis. The significant impacts of tightening property supply constraints on the likelihood of different types of early mortgage termination are proved. Overall, we expect that these three original ideas offer a helpful insight for mortgage originators and regulators as well as policymakers to manage related risk by including the geographical composition of collateral by supply constraints in risk models.

Item Type:Thesis (PhD)
Thesis Supervisor:Marcato, G.
Thesis/Report Department:Henley Business School
Identification Number/DOI:https://doi.org/10.48683/1926.00086318
Divisions:Henley Business School > Real Estate and Planning
ID Code:86318

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