Valuation of real-estate losses via Monte Carlo simulation

Abstract

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.

The Importance of Establishing Financial Valuation of Fixed Assets in Public Companies whose Founders Are Local Self-Government Units in the Republic of Serbia

“…Deepening of the research was done by continuing the study with already published research which was focused on practical application of international financial reporting standards (Babatunde, 2019). Essentially, this study did not focus on presenting the property valuation model (Prusak, 2017;Baranano et al, 2020). Therefore, the focus of the study was to observe the consequences of making a valid decision of top management to realistically value and present such valued assets of the company in business books.…”

The effects of skewness on hedging decisions: an application of the skew-normal distribution in WTI and Brent futures

“…No matter which risk measure is adopted, the key point is that we need some assumption or cognition about the distribution of data before conducting a study. Most of existing literature argue that the asset return follows a normal distribution, however, the actual return distribution of assets has more leptokurtosis and fatter tails than the normal distribution (Naqvi et al,2017, Barañano et al, 2020, so it's likely that the normal assumption would lead up to the underestimate of risks and the bias of hedging strategy to a large extent. In light of this, this paper investigates the effect of skewness on hedging decision through numerical analysis and empirical test to WTI crude oil and Brent crude oil.…”