scholarly journals International Real Estate Review

2018 ◽  
Vol 21 (4) ◽  
pp. 419-446
Author(s):  
Jing-Tang Tsay ◽  
◽  
Che-Chun Li ◽  
Jerry T. Yang ◽  
◽  
...  
Keyword(s):  
Real Estate ◽  
Interest Rates ◽  
Trigger Point ◽  
House Prices ◽  
House Price ◽  
Price Volatility ◽  
Barrier Option ◽  
High Concentration ◽  
Interest Rate Volatility ◽  
House Price Volatility

This paper develops a pricing model and derives a closed-form formula for valuing mortgage-backed securities (MBSs) that embed a barrier option feature while the optimal prepayment or refinancing choices of borrowers are endogenously determined. Given that ¡§real estate investors¡¨ tend to prepay a loan relentlessly, an MBS with a high concentration of investor borrowers implies a lower MBS value. We specify the prepayment behavior of borrowers by using the first hitting time as a proxy for the trigger point of prepayment when house prices or interest rates hit a pre-determined barrier. Our results show that the MBS value is positively related to loan to value and house price volatility while negatively related to the proportion of real estate investors and interest rate volatility. We also find evidence which shows that the MBS value may increase due to the effects of the ¡§longevity¡¨ of mortgages, which outweigh the effects of default or prepayment as house price volatility increases. This model provides a faster pricing tool of MBSs than Monte Carlo simulation while retaining higher model accuracy and consistency than the hazard model approach.

scholarly journals International Real Estate Review

2014 ◽  
Vol 17 (1) ◽  
pp. 109-135
Author(s):  
Marsha J. Courchane ◽  
◽  
Cynthia Holmes ◽  
Keyword(s):  
Real Estate ◽  
Interest Rates ◽  
House Prices ◽  
House Price ◽  
Price Indices ◽  
Real Estate Markets ◽  
House Price Indices ◽  
Mortgage Interest Rates ◽  
Precipitous Decline ◽  
The U.S

Canadian and U.S. real estate markets have compared similarly along dimensions such as inflation, mortgage interest rates, population and income growth and other measures. With respect to house prices, however, the series have moved in similar ways at some times, but then significantly diverged by the second quarter of 2007. For example, Canadian and U.S. house price indices reached essentially identical levels in 1987Q2, 1995Q1 and 2007Q2. As a consequence of the U.S. financial crisis and precipitous decline in house prices, the U.S. and Canadian indices have sharply diverged. Our paper examines whether or not the house price indices were driven by fundamentals during these time periods, or whether they diverged from fundamentals. We find that the U.S. house prices closely aligned with fundamentals until the mortgage markets crashed in 2008. We find that Canadian house prices continue to align with fundamentals. However, there have been some significant market changes between the two countries and key housing market measures indicate that Canadian markets are now moving along some paths similar to those taken by the U.S. prior to the crash.

scholarly journals Forty years of real-estate bubbles in the US and the macroeconomy: a Keynesian perspective

2019 ◽  
Vol 16 (3) ◽  
pp. 381-402
Author(s):  
Herbert Walther
Keyword(s):  
Real Estate ◽  
Banking Sector ◽  
House Prices ◽  
Asset Price ◽  
House Price ◽  
Price Volatility ◽  
Asset Price Bubbles ◽  
Us Economy ◽  
Real Estate Sector ◽  
The Us

This paper presents a dynamic, non-linear, stock–flow consistent aggregate Keynesian model with a banking sector, a household sector, a government sector, and a real-estate sector, to study the interactions between booms and busts in the real-estate sector and the macroeconomy. Using this model we try to simulate some ‘stylized facts’ about the US economy observable during the last four decades. It is argued that for various reasons house-price volatility in the US has increased since the 1980s: house prices seem to have followed a ‘cobweb’ pattern of accelerating instability, leading to the climax of the financial crises in 2007/2008. A new run-up of house prices has already started, pointing towards a looming bubble ahead. The US economy seems to have become addicted to asset-price bubbles as the driving force of the business cycle. It is argued that various institutional changes, which can be linked to the dominant economic ideology, are responsible for these developments.

scholarly journals DYNAMIC INTERACTION BETWEEN HOUSE PRICES AND STOCK PRICES IN MALAYSIA

2014 ◽  
Vol 18 (2) ◽  
pp. 163-177 ◽  
Author(s):  
Hooi Hooi Lean ◽  
Russell Smyth
Keyword(s):  
Real Estate ◽  
Interest Rates ◽  
Stock Prices ◽  
House Prices ◽  
House Price ◽  
Dynamic Interaction ◽  
Kuala Lumpur ◽  
Price Indices ◽  
House Price Indices ◽  
Causality Testing

This paper examines the dynamic linkages between house price indices, interest rates and stock prices in Malaysia using cointegration and Granger causality testing. For Malaysia as a whole, we find that house prices, stock prices and interest rates are not cointegrated. For Kuala Lumpur, Penang and Selangor we find that house prices, stock prices and interest rates are cointegrated for 40% of the house price indices. When there is evidence of cointegration in these regions, we find that stock prices lead house prices. While there are alternative potential reasons for this finding, such as slow adjustment of house prices in response to a shock in the fundamentals, it is consistent with a wealth effect. A likely explanation for this result is that in these states, compared with the Malaysian average, housing is expensive, income is high and real estate is used much more as an investment vehicle by both wealthy Malaysians and foreigners leveraging of the share market.

scholarly journals Making sense of increased synchronization in global house prices

2020 ◽  
Vol 13 (1) ◽  
pp. 5-16
Author(s):  
John V. Duca
Keyword(s):  
Real Estate ◽  
Interest Rates ◽  
House Prices ◽  
House Price ◽  
Substitution Effects ◽  
Content Type ◽  
International Portfolio Diversification ◽  
Gateway Cities ◽  
The Impact ◽  
International House

Purpose The purpose of this paper is to provide perspective on whether and why global metro house prices have become more synchronized, and perspective on the limited implications of this for investing in international real estate. Design/methodology/approach This paper reviews main findings from the literature on house price determination, reviews the emerging literature on global synchronization, and provides graphs to illustrate main points and trends. Findings House prices have become somewhat more synchronized likely reflecting greater correlation in long-term interest rates and macroeconomic cycles related to trends in globalization and international portfolio diversification. Nevertheless, this trend has not been continuous, reflecting that house prices depend on other fundamentals, which are not uniform across areas. Theory and evidence indicate that the more common are fundamentals, the more synchronized are house price cycles and the more substitution effects may matter. Also, real estate markets that are open to immigration and foreign investment have become more sensitive to shifts in the international demand for property by migrants or investors. Research limitations/implications Changes in international house price synchronization stem from variation in two categories of key drivers of house prices. The first are traditional supply and demand fundamentals. The second include international capital flows and immigration. Both sets of factors are sensitive to the economic environment and public policy. Increased synchronization of business cycles, the Euro currency union, and more common monetary policy strategies and tactics have fostered greater correlation of real interest rates across countries, which tend to increase house price synchronization. These effects can be amplified by the tendency for property owners to use extrapolative expectations of future house prices. Practical implications Shifts in prospective returns and the synchronization of international property returns not only on arbitrage of general property price differentials but also on underlying factors driving those differentials. Investors need to be mindful of the risks that metro prices sometimes reflect bubble-builder dynamics that can give rise to over-shooting of house prices. Observing simple correlations and changes in those correlations does not do away with the need for careful analysis of property investment, and if anything, warrant analysis of both how and why one may observe changes in the extent to which international house prices is synchronized. Social implications Despite the rise of globalization and of new technologies, the author has seen substantial divergences in house prices emerge across gateway cities and metros in less vibrant areas within countries. These reflect not only the impact of stronger income and population in more tech, educated and global oriented cities but also changes in the demand for amenities toward more culturally appealing cities, often – but not exclusively in – warmer or coastal areas where the supply elasticity of housing is often limited. Further complicating investment decisions are potential shifts in housing or immigration policy that can notably affect the demand for housing. Originality/value The paper provides practical perspective on why different groups of international cities have seen their house prices become more sychronized. Nevertheless, increased synchronization has occurred within an elite set of major cities, but in an environment house prices have diverged across gateway cities and metros in less vibrant areas within countries. The paper helps investors make sense of some recent patterns and recent prospects for investing in international real estate.

Determinants of house price volatility in Namibia

2019 ◽  
Vol 12 (4) ◽  
pp. 807-823 ◽  
Author(s):  
Teresia Kaulihowa ◽  
Katrina Kamati
Keyword(s):  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Price Volatility ◽  
Policy Implications ◽  
Mortgage Loans ◽  
Causal Relations ◽  
Content Type ◽  
House Price Volatility ◽  
Macroeconomic Determinants

Purpose This paper aims to test the volatility and analyses the macroeconomic determinants of house price volatility in Namibia over the period 2007 Quarter 1 to 2017 Quarter 2. It further explores the causal relations between house price volatility and its determinants. Design/methodology/approach The study used autoregressive conditional heteroskedastic and generalized autoregressive conditional heteroskedastic models to test for volatility. The vector error correction model was used to analyse the determinants and causal relations. Findings The results support the hypothesis that house prices in Namibia exhibits persistent volatility. It was further established that past period volatility’ GDP and mortgage loans are the key determinants of house price volatility. Additionally’ there exists unidirectional causality from GDP and mortgage loans to house price volatility. Practical implications Policy implications emanating from the study implies that macroeconomic fundamentals should be monitored closely to mitigate the issues of house price volatility. Originality/value The study is the first of its kind in Namibia to address the pertinent issues of ever increasing housing prices.

scholarly journals The Behavioral Mechanism and Forecasting of Beijing Housing Prices from a Multiscale Perspective

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yan Li ◽  
Zhaoyang Xiang ◽  
Tao Xiong
Keyword(s):  
Real Estate ◽  
Multiscale Analysis ◽  
House Prices ◽  
Housing Prices ◽  
Hybrid Approach ◽  
House Price ◽  
Price Volatility ◽  
Practical Significance ◽  
Critical Element ◽  
Behavioral Mechanism

The first-hand house price in Beijing, the capital of China, has skyrocketed with 43 percent annual growth from 2005 to 2017, exerting tremendous adverse effects on people’s livelihood and the development of real estate. Thus, exploring the behavioral mechanism and accurate forecasts of house prices is a critical element in making decisions under uncertain conditions and is of great practical significance for both participants and policymakers in real estate. According to the complex features of house price, including nonlinear, nonstationary, and multiscale, and considering the remarkable time and frequency discrimination capability of multiscale analysis in dealing with house price problems, we develop an ensemble empirical mode decomposition- (EEMD-) based multiscale analysis paradigm to investigate the behavioral mechanism and then obtain accurate forecasts of house prices. Specifically, the monthly house price in Beijing over the period January 2005 to November 2018 is first decomposed into several different time-scale intrinsic-mode functions (IMFs) and a residual via EEMD, revealing some interesting characteristics in house price volatility. Then, we compose the IMFs and residual into three components caused by normal market disequilibrium, extreme events, and the economic environment using the fine-to-coarse reconstruction algorithm. Finally, we propose an improved hybrid prediction model for forecasting house prices. Our experimental results show that the proposed multiscale analysis paradigm is able to clearly reveal the behavioral mechanism hidden in the original house price. More importantly, the mean absolute percentage errors (MAPEs) of the proposed EEMD-based hybrid approach are 5.62%, 7.24%, and 8.63% for one-, three-, and six-step-ahead prediction, respectively, consistently lower than the MAPE of the three competitors.

The Granular Origins of House Price Volatility

2017 ◽  
Author(s):  
Isaiah Hull ◽  
Conny Olovsson ◽  
Karl Walentin ◽  
Andreas Westermark
Keyword(s):  
House Price ◽  
Price Volatility ◽  
House Price Volatility

Heterogeneous expectation, beliefs evolution and house price volatility

2016 ◽  
Vol 53 ◽  
pp. 409-418 ◽  
Author(s):  
Hao Zhang ◽  
Yuyuan Huang ◽  
Haixiang Yao
Keyword(s):  
House Price ◽  
Price Volatility ◽  
House Price Volatility
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