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Real Estate Price Volatility - Research Paper Example

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Housing price behavior has always been an area of interest to all participants in the housing sector as it is one of the investment avenues in the market like any other profitable opportunity. The recent developments in the housing sector and economic turmoil as a result of the subprime crisis in the United States of America have compounded the need to accurately predict the price of houses as it is subject to perennial volatility…
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Real Estate Price Volatility
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In this context, the present paper attempts to discuss about one of the early developed models that is still prevalent in the present economic scenario. The model was developed by R. Engle in 1982, which came to be known as Autoregressive Conditional Heteroskedasticity (ARCH). The paper also attempts to through lights on how effective is the model in the present real estate climate in the United States of America with particular reference to California. The paper takes an analytical approach wherein the model is suggested with a brief explanation of its application, merits and demerits.

The various stakeholders (participants) in the real estate market comprising of real estate investors, banks, non-bank financial institutions, portfolio managers have always been curious to predict the local housing prices. Naturally, they have always encouraged the attempts to evolve mathematical models that can prevent the losses and chaos from the volatility of real estate prices. Parties who are also interested in housing prices estimating models include managers of banks, Real Estate Investment Trusts (REITs), and homebuilding companies.

Prior models have tried to incorporate many of the macroeconomic variables including the bubbles and crashes in the stock market. Experts such as Alan Stockman and Tesar Linda, Lane Philip and Girouard N and Bl'ndal have described the housing price behavior from a dynamic general equilibrium point of view (Stockman and Tesar, 1995, Girouard and Bl'ndal, 2001 and Lane, 2001). Studies undertaken by Driffill John and Sola Martin explored the model in the context of market bubbles (Driffill and Sola 1998).

Attempts have also been done to evolve a model that incorporate the interaction of an array of variables such as transactions in the real estate sector, changes in the demography of participants, and macro factors comprising of diversity in the income distribution and changes in the economic activity as a whole. For example, Francois Ortalo-Magne and Rady Sven have studied these aspects through a significant research (Ortalo-Magne and Rady 1998, 1999, 2003a and 2003b). Economic Analysis The model developed by R.

Engle in 1982 is found relevant in the present scenario where traditional models that describe variables such as location factors, structural variables and floor area and income are no longer valid (Engle 1982). This model was coined as Autoregressive Conditional Heteroskedasticity (ARCH). The basic contention of this model is that housing price prediction should take care of time-varying volatility and studied through time series analysis.The ModelThe ARCH model was developed using mathematical and statistical notations and theories.

For a better understanding of the model, the ARCH process consisting of conditional mean process and a conditional variance process will have to be known. The conditional mean process is developed in conformity to the standard Autoregressive Moving Average (ARMA) equation (Engle 1982). Where, Rt is the return on average home prices on a monthly basis, e, and s2 are constants. Through this model, Engle try to analyze and incorporate the pricing behavior with two

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