Clustering has a potentially important contribution to real estate portfolio analysis. In this study several hierarchical clustering algorithms are applied to rental returns for seventy-one metropolitan residential markets in Turkey. The aim is to develop homogeneous groupings for real estate portfolios. The historical clustering algorithms documented in this study provides a useful guideline for real estate investors to select appropriate market areas and formulate efficiently diversified investment portfolios. The empirical findings support the three-cluster partition of the districts that reveals a clear rental return distinction of residential markets in Turkey. Cluster 1 is composed of twenty nine districts, which have the lowest rental return levels over the period of 2007:M6 to 2011:M6. Thirty four districts are grouped in Cluster 2. The cities in this group have relatively higher rental returns. The rest eight cities belong to Cluster 3. Rental return levels are distinctively higher than the other two groups. On the other hand, high rental returns are associated with higher levels of risk (standard deviation), and vice versa.

Purpose -It is important to forecast index series to identify future rises, falls, and turning points in the property market. From the point of this necessity and importance, the main purpose of this paper is to forecast the future trends in Dubai housing market. Design/methodology/approach -This paper uses the monthly time series of Reidin.com Dubai Residential Property Price Index (DRPPI) data. In order to forecast the future trends in Dubai housing market, Box-Jenkins autoregressive integrated moving average (ARIMA) forecasting method is utilized. Findings -The results of the ARIMA modeling clearly indicate that average monthly percentage increase in the Reidin.com DRPPI will be 0.23 percent during the period January 2011-December 2011. That is a 2.44 percent increase in the index for the same period. Practical implications -Reidin.com residential property price index is a crucial tool to measure Dubai's real estate market. Based on the current index values or past trend, real estate investors (i.e. developers and constructors) decide to start new projects. Attempts have also been made in the past to forecast index series to identify future rises, falls, and turning points in the property market. The results of this paper would also help government and property investors for creating more effective property management strategies in Dubai. Originality/value -There is no previous study analyzing the future trends in Dubai housing market. At this point, the paper is the first academic study that identifies this relationship.

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Purpose The main purpose of this study is to detect homogeneous housing market areas among 196 districts of 5 major cities of Turkey in terms of house sale price indices. The second purpose is to forecast these 196 house sale price indices. Design/methodology/approach In this paper, the authors use the monthly house sale price indices of 196 districts of 5 major cities of Turkey. The authors propose an autoregressive (AR) model-based fuzzy clustering approach to detect homogeneous housing market areas and to forecast house price indices. Findings The AR model-based fuzzy clustering approach detects three numbers of homogenous property market areas among 196 districts of 5 major cities of Turkey where house sale price moves together (or with similar house sales dynamic). This approach also provides better forecasting results compared to standard AR models by higher data efficiency and lower model validation and maintenance effort. Research limitations/implications In this study, the authors could not use any district-based socioeconomic and consumption behavioral indicators and any discrete geographical and property characteristics because of the data limitation. Practical implications The finding of this study would help property investors for establishing more effective property management strategies by taking different geographical location conditions into account. Social implications From the government side, knowing future rises, falls and turning points of property prices in different locations can allow the government to monitor the property price changes and control the speculation activities that cause a dramatic change in the market. Originality/value There is no previous research paper focusing on neighborhood-based clusters and forecasting house sale price indices in Turkey. At this point, it is the first academic study.

The main purpose of this study is to investigate whether there is a long-run relationship between macroeconomic indicators and property price index in Dubai. This paper uses the monthly data for the eight year period from January 2003 to December 2010. In order to identify long term equilibrium between property price index and macroeconomic indicators, cointegration analyses are utilized for the study. The results of the empirical analyses show that there is a long term positive equilibrium relationship not only between RE IDIN.com Dubai Residential Property Price Index (DRPPI) and gold prices; but also between DRPPI and volume of total direct foreign trade. On the other hand, there is a negative long-run relationship between DRPPI and the number of completed residential units. In addition, there is a significant positive relation between DRPPI and the first lag of DRPPI and also the first lag of error term. Our paper is the first academic study that identifies this relationship in Dubai. Santrauka Pagrindinis tyrimo tikslas – išnagrinėti, ar makroekonominius rodiklius ir NT kainų indeksą Dubajuje sieja ilgalaikis santykis. Darbe naudojami aštuonerių metų (nuo 2003 m. sausio iki 2010 m. gruodžio) mėnesiniai duomenys. Siekiant nustatyti ilgalaikę pusiausvyrą tarp NT kainų indekso ir makroekonominių rodiklių, tyrimui naudojamos kointegracijos analizės. Empirinių analizių rezultatai rodo ilgalaikį teigiamą pusiausvyros santykį ne tik tarp REIDIN.com skelbiamo Dubajaus gyvenamojo NT kainų indekso (DRPPI) ir aukso kainų, bet ir tarp DRPPI ir bendros tiesioginės užsienio prekybos apimčių. Kita vertus, nustatytas ilgalaikis neigiamas santykis tarp DRPPI ir pastatytų būstų skaičiaus. Be to, nustatytas reikŠmingas teigiamas santykis tarp DRPPI ir jo pirmojo vėlavimo (angl. first lag) bei paklaidos pirmojo vėlavimo. Šis darbas – pirmas mokslinis tyrimas, kuriame nustatomas Šis santykis Dubajaus atveju.