The valuation of the exposure to real estate market risk has traditionally been difficult due to the lack of appropriate data, returns that do not follow a normal distribution and a lack of adequate methodology. However, regulations such as Basel II, Basel III and Solvency II make it possible to assess real estate market risk using an internal model and through Value at Risk. The study develops a procedure to provide an internal model that values real estate market risk and calculates the capital that guarantees it. Monte Carlo simulations are used to calculate Value at Risk. As result, capital requirements can be established from these results to help with portfolio decision-making of insurance companies that hold real estate. Data used in the study is taken from the General Council of Notaries registered dwellings databases from the Spanish National Statistics Institute covering the time period of 2007-2017. This paper contributes to the literature by proposing a model that incorporates the characteristics of investments, allowing a real and market measure of the risk of loss from real estate.
Immunization is an investment strategy often used by insurance companies. Usually, this strategy takes into account the first‐ and second‐order of Taylor series (Duration and Convexity). However, the model itself has risk because of the difference between the real and estimated value via duration and convexity approximation. Therefore, the aim of this article is to find a better immunization model avoiding the effect of unexpected interest rate shocks by adding more terms of Taylor series to an immunization strategy. As criteria of efficiency, the paper checks the effect of interest rate risk in several immunization models upon a 99.5% confidence level (risk level of 1 in 200 scenarios), as required by Solvency II in Europe, to determine a better immunization strategy. This work analyses the skewness and, consequently, the fitness of adding third‐ and fourth‐order Taylor series. The main finding is that the model with four factors avoids the influence of interest rate shocks. Therefore, the capital on risk in near zero.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.