Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Analyzing Housing Market Dynamics using Linear and non-Parametric Models
Date
2018-10-07
Author
Yılmaz, Bilgi
Yerlikaya Özkurt, Fatma
Kestel, Sevtap Ayşe
Metadata
Show full item record
Item Usage Stats
273
views
0
downloads
Cite This
This paper analyzes the dynamic effect of macroeconomic indicators, such as financial and commodity market indicators on national housing markets. Furthermore, it does not only focus on the impact of the variables but also introduces a variety of models that based on the generalized linear models and multivariate adaptive regression splines. The models help us to identify the macroeconomic drivers of housing markets. Since the US has an adequate housing market data, the empirical analysis within the paper focuses on the US national housing market. Namely, the illustration of the proposed models is done through the historical realizations of S&P/Case-Shiller National Home Price Index (HPI) and US macroeconomic indicators for the period 2000 to 2017. The empirical results indicate that although the efficiency of the models may be questionable for their variable selection and their accuracy, the directions of the indicators effect are consistent with the standard expectation, and a proposed model estimates the trend of the market successively.
URI
https://hdl.handle.net/11511/73369
Conference Name
11. International Statistics Days Conference,( 3-07 Ekim 2018)
Collections
Graduate School of Applied Mathematics, Conference / Seminar
Suggestions
OpenMETU
Core
The Impact of Macro-Economic Drivers in Housing Markets: The US Cas
Yılmaz, Bilgi; Yerlikaya Özkurt, Fatma; Kestel, Sevtap Ayşe (2021-08-01)
This paper analyzes the effect of macro-economic, financial and commodity market indicators on housing markets. We compare the efficiency of the models generated by Generalized Linear Models (GLM) and Multivariate Adaptive Regression Splines (MARS) according to method free measures for estimating the housing market trend. These models are used for the first time to identify the influence of macro-economic indicators on housing markets and the estimation of the trend in housing markets to our best knowledge....
Computation of Hedging Coefficients for Mortgage Default and Prepayment Options: Malliavin Calculus Approach
YILMAZ, BİLGİ; Kestel, Sevtap Ayşe (2019-11-01)
This study explores the hedging coefficients of the financial options to default and to prepay embedded into mortgage contracts based on the change in spot rate, underlying house price and its volatility. In the computations, the finite-dimensional Malliavin calculus is applied since the distribution of both options is unknown and their payoffs are non-differentiable. Naturally, the hedging coefficients are obtained as a product of option's payoff and an independent weight, which permits the user to derive ...
Optimal monetary policy and the timing of asset trade in open economies
Senay, Ozge; Sutherland, Alan (2007-05-01)
This paper analyses the timing of asset trade and its implications for monetary policy and welfare in open economies. Optimal policy is shown to differ significantly depending on whether asset trade takes place before or after policy decisions are made.
Analysis of volatility feedback and leverage effects on the ISE30 index using high frequency data
Inkaya, A.; Okur, Y. Yolcu (Elsevier BV, 2014-03-15)
In this study, we employ the techniques of Malliavin calculus to analyze the volatility feedback and leverage effects for a better understanding of financial market dynamics. We estimate both effects for a general semimartingale model applying Fourier analysis developed in Malliavin and Mancino (2002) [10]. We further investigate their joint behaviour using 5 min data of the ISE30 index. On the basis of these estimations, we look for the evidence that volatility feedback effect rate can be employed in the s...
Nonlinear models for UK macroeconomic time series
Ocal, N (2000-09-01)
This paper examines possible nonlinearities in growth rates of nine U.K. macroeconomic time series, namely gross domestic product, price, consumption, retail sales, personal disposable income, savings, investment, industrial production and unemployment, chosen as representative of series typically used to investigate business cycle fluctuations. By basing analysis on the class of smooth-transition autoregressive (STAR) models, it is assumed that the economy can be in one of two states with distinct dynamics...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
B. Yılmaz, F. Yerlikaya Özkurt, and S. A. Kestel, “Analyzing Housing Market Dynamics using Linear and non-Parametric Models,” presented at the 11. International Statistics Days Conference,( 3-07 Ekim 2018), Muğla, Turkey, 2018, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/73369.