Housing market dynamics and advances in mortgages: option based modeling and hedging

Yılmaz, Bilgi
In the last two decades, academicians and professionals intending to study in any area of real estate and finance not only must master advanced financial mathematics concepts and mathematical/econometric models but also should be able to implement those concepts computationally to improve real estate markets' efficiency. This comprehensive thesis mainly aims to combine the theory of financial mathematics with an emphasis on real-life applications in keeping with the way, both investors and policymakers, in today's real estate markets. Unlike most studies on real estate markets, housing markets and mortgages, the thesis covers both non-parametric statistical modeling methods (Multivariate Adaptive Regression Splines (MARS) and Generalized Linear Models (GLM)) and stochastic calculus (Stochastic Differential Equations (SDE), Malliavin calculus theory) with Monte Carlo simulations, Capital Asset Pricing Model (CAPM) and Fama French three-factor model with its extensions. The thesis offers thorough models in the subject of housing markets and provides hedging strategies of default and prepayment options embedded into mortgage contracts. Along with with the theoretical aspects, the thesis presents numerous applications for pricing, investment decision, risk management via hedging strategies, and portfolio management. The numerical illustrations are on determining the housing market price drivers and the effect of large investors, house price forecasting by using the US housing market data, determining hedging strategies for both mortgage default and prepayment options by computing the hedging coefficients via using Monte Carlo simulations and analyzing the T-REITs returns performance in various aspects.
Citation Formats
B. Yılmaz, “Housing market dynamics and advances in mortgages: option based modeling and hedging,” Thesis (Ph.D.) -- Graduate School of Applied Mathematics. Financial Mathematics., 2019.