In recent years, reverse mortgages have gained attention as suitable financial instruments for individuals of retirement age, particularly those classified as “house-rich but cash-poor.” Despite growing interest in countries such as the US, the UK, and Australia, the Italian market remains underdeveloped in this area. From a lender’s perspective, these contracts are perceived as complex, mainly due to the management of various risk components: longevity risk, financial risk, and house price risk. Our goal is to provide lenders with insights into the impact of each risk factor through a time-dependent profit/loss function. This approach aids in identifying the most critical sources of risk, enabling lenders to take appropriate measures to mitigate potential financial threats. We conduct Monte Carlo simulations of the chosen stochastic risk models and apply a single-component VaR assessment procedure. Our findings indicate that house price risk is the most significant risk factor of a Reverse Mortgage portfolio. Moreover, the lender can control the financial risk through the analysis of the risk premium values. The results also highlight that, beyond a certain time horizon, the lender’s exposure stabilizes, with profitability emerging in the long run.

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Reverse Mortgages: Exploring the Impact of Risk Factors by Source

  • Emilia Di Lorenzo,
  • Giulia Magni,
  • Marilena Sibillo

摘要

In recent years, reverse mortgages have gained attention as suitable financial instruments for individuals of retirement age, particularly those classified as “house-rich but cash-poor.” Despite growing interest in countries such as the US, the UK, and Australia, the Italian market remains underdeveloped in this area. From a lender’s perspective, these contracts are perceived as complex, mainly due to the management of various risk components: longevity risk, financial risk, and house price risk. Our goal is to provide lenders with insights into the impact of each risk factor through a time-dependent profit/loss function. This approach aids in identifying the most critical sources of risk, enabling lenders to take appropriate measures to mitigate potential financial threats. We conduct Monte Carlo simulations of the chosen stochastic risk models and apply a single-component VaR assessment procedure. Our findings indicate that house price risk is the most significant risk factor of a Reverse Mortgage portfolio. Moreover, the lender can control the financial risk through the analysis of the risk premium values. The results also highlight that, beyond a certain time horizon, the lender’s exposure stabilizes, with profitability emerging in the long run.