Real Estate Investment Decisions Research Articles

The Price per Pound and Replacement Cost: The Effects of Q on Office Investment

Despite the reality that price versus replacement cost, or Tobin’s Q, is commonly used in making commercial real estate investment decisions, its efficacy has not been widely explored academically. Nordby and Taylor address this by examining the relationship between Q and office construction starts and pricing trends. By using CoStar property and land transaction sale price data and RSMeans construction cost data from 2000 to 2012, the authors are able to construct comprehensive national and market-level Q indices. The results indicate a strong relationship between Q and investment in office properties. The authors also find that this relationship differs across markets and is generally related to the level of barriers to construction present in these markets. <b>TOPICS:</b>Real estate, in markets, portfolio construction

Applied Research of Composite Weights – TOPSIS Method in Real Estate Investment Decision

According to the shortage of the method in real estate investment decision, in order to supplement the deficiency of this one.this paper on the basis of comprehensive consideration of Effects of various factors of real estate project decision, this paper constructs the real estate investment decision-making multi-objective planning evaluation model.Into composite weights,determined by weightthrough the subjective evaluation method combined with the objective evaluation method,and by using the ideal point method (TOPSIS) to evaluate the real estate investment decision-making. This kind of method in view of the present real estate investment decision method is the present situation of the lack of certain to give support and complement, because real estate investment decision is a multi-objective process, so the method is introduced in this paper the method will be more close to the actual situation. Finally, combining with an example, this method is feasible and simple and practical, scientific and reasonable.

Real Options and Urban Land Values: A Review of the Literature

This critical analysis contributes to a better understanding of urban land values by unifying the real option and redevelopment decision literatures within a broader context of real estate valuation. By combining these heretofore disparate literatures in this way, both academics and practioners should find the analysis relevant to their own real estate studies or investment decisions.

Real estate investment decision making – a review

Real estate investment decision making – a review

A Study of Factors Affecting Decision and Real Estate Investment

Real Estate investment decision process make a purpose of the investment, the investment environment, cost convenience ananlysis and the investment validity. For this, Real Estate investment intention decision has investment ananlysis and grope for practice. therefore this paper has a purpose for Real Estate investment decision process that solve the more than brilliant course about Real Estate investment.

Coherent risk measures in real estate investment

PurposeThe purpose of this paper is to propose a new way to measure risk in real estate investment, which departs from traditional statistical methodology borrowed from finance.Design/methodology/approachAn argument is advanced for the use of so‐called coherent risk measures for real estate investment decisions. Central to this class of measure is the computation of spectral risk, a measure that covers the spectrum of an individual's risk aversion function. Intuition being hard to observe, empirical data from two large databases are presented as support.FindingsAt the heart of the controversy is a discussion of the nature of risk and how it should be measured. This paper seeks common ground where peace may be made between these two warring factions. Scenarios are tested wherein different risk aversion functions are used to compute spectral risk for different sectors. Ex‐post analysis shows that reasoning of this nature can lead to improved risk‐adjusted investment results.Practical implicationsThe route to finding an appropriate risk measure for real estate investment has been tortuous. It is not certain that the destination has been reached. Complicating the task is a considerable gap between academic and practitioner methodology, the former relying on the mathematics of objective probability, the latter dwelling quite successfully in a habitat of subjective risk measures.Social implicationsIt is widely accepted that risk represents a cost to society. Real estate, as a repository of roughly half the world's wealth, can be viewed as having risk of a structurally different nature. The better understanding of this risk reduces the cost to society.Originality/valueFor practitioners, spectral measures offer formal support for something they have been doing their entire careers: evaluating risk subjectively. The simple dot product of weights and ordered outcomes is an extension of the widely used “Best case – Worse case – Most likely” methodology that has served professionals well for decades. Perhaps a by‐product of spectral measures is to bring academics and field gladiators closer together. If there is merit to a new way of thinking about risk independent of its implementation, real estate investment could benefit from that thinking. Among those who doubt that everything is “normal” are those who believe that previous attempts to explain risk in real estate have fallen far short of the mark. The challenge to those still not satisfied by the spectral approach is to offer an alternative that represents both a departure from and an improvement of the old methods.

The Integrative Application of GAHP and FCE Method in Real Estate Investment Decision

Based on analysising the influence factors of real estate investment decision, the paper establishes an evaluation index system of real estate investment decision, and applies integratively Group analytic hierarchy process(GAHP) and Fuzzy comprehensive evaluation(FCE) method to analysis the decision-making of real estate investment, to provide a more scientific quantitative basis for the decision-maker of real estate investment, so real estate investment decision has stronger scientificity.

A Real Option Model Suitable for Real Estate Project Investment Decision

Real estate investment is distinctively different from others with its high input capital, long period of recycling, huge fluctuation of house price and high sensitivity to other factors. The traditional decision method could not make a rational judgment of the flexible management value in real estate project investment. With regards to the policy and market features of real estate investment in China, a real option model suitable for real estate project investment decision under high uncertainty in China is constructed. At last, a case of a real estate company is studied to test the real estate investment decision model.

Mental Accounting and False Reference Points in Real Estate Investment Decision Making

This study examines a number of behavioral finance issues as they relate to real estate investments. We find a statistically significant degree of mental accounting at all points throughout the disposition effect curve when holding a real estate investment in isolation versus holding the asset as part of a mixed-asset portfolio. We also identify four distinct disposition curve shapes beyond the traditional “S-shaped” curve, where investors are more willing to sell an asset that is in the gains domain. Furthermore, we conclude that an investor's willingness to sell jumps by the greatest amount when going from zero return into profitable territory. Finally, this false reference point does take into consideration transaction costs.

Illiquidity, transaction cost, and optimal holding period for real estate: Theory and application

Choosing the optimal holding period is an important part of real estate investment decisions, because “when to sell” affects “whether to buy”. This paper presents a theoretical model for such decision making. Our model indicates that the optimal holding period is affected by both systematic and non-systematic factors—market conditions (illiquidity and transaction cost) and property performance (return and return volatility). Other things being equal, higher illiquidity and transaction costs lead to longer holding periods, while higher return volatility implies shorter holding periods. Our empirical application suggests that the optimal holding period based on our model is quite consistent with previous empirical findings. In addition, we find that when illiquidity risk is incorporated the true real estate risk is significantly higher than the conventional risk estimate. Therefore, the current practice of real estate valuation, which is naively borrowed from finance theory, substantially underestimates real estate risk.

Deciphering real estate investment decisions through fuzzy logic systems

PurposeThe purpose of this paper is to explore the application of fuzzy logic in real estate investment in Hong Kong. There have been sufficient debates on the literature, providing the theoretical background on real estate investment decisions but there has been a lack of empirical support in this regard. This paper attempts to fill the gap between theorem and application.Design/methodology/approachThe fuzzy logic system is adopted to evaluate the situation of a real estate market with imprecise and vague information. An indicator‐portfolio, rather than a specific indicator/index usually employed by practitioners, is explored to assist investors in risk management. The result derived from this framework is then compared to the property price index. This approach provides a framework in understanding the market without statistical and mathematical models. It tries to stimulate the complex human cognitive process involving decision making.FindingsThe housing‐indicator portfolio composition produces an outcome value which is able to reflect the complexities of both the real estate market and investors' expectations. An increase of this value implies that the investment condition is becoming more positive.Research limitations/implicationsThe paper reveals that fuzzy logic can provide some insights in an intuitive manner and is capable of obtaining information not found in market data. It is particularly useful to investors without experience in mathematical modeling.Practical implicationsThis paper establishes a basic framework of fuzzy logic for real estate investment on which a base is formed as a reference for practitioners and investors. However, they should make references to the specific housing‐indicator portfolio composition in their own regions.Originality/valueThis paper has used a fuzzy logic system to assist practitioners as well as investors on decision making in real estate investment with imperfect market information. With the aid of the system, practitioners and investors are able to enhance their investment decision‐making quality by reducing the risk incurred by such uncertainties.

Application of PPC Model Based on RAGA in Real Estate Investment Decision-Making

According to the size of the projector function to evaluate the merits of the program, Projection Pursuit method is applied to real estate investment decision-making by using the real coding based on Accelerating Genetic Algorithm (RAGA) to optimize the Projection Pursuit Classification (PPC) process and a wide range of indicators value was projected linearly. The results are reasonable and verified with an example. At the same time, the subjective of the target weight can be avoided. It provides decision-makers with comprehensive information on all the indicators of new ideas and new methods

An Investigation of Real Estate Investment Decision-Making Practices

This survey investigation reports on the investment decision-making processes used by equity investors in real estate. The survey covers the entire investment decision-making process, from setting ...

An Investigation of Real Estate Investment Decision-Making Practices

(2007). An Investigation of Real Estate Investment Decision-Making Practices. Journal of Real Estate Practice and Education: Vol. 10, No. 2, pp. 209-222.

The Labor Component of Private Investor Real Estate Returns

Executive Summary. This paper offers theoretical foundation as to how the addition of human capital enters into the return calculation for privately owned real estate investments. A two-part model of investor behavior discloses that real estate investment decisions are a labor trade-off rather than a portfolio trade-off. Using differential equations that do not admit a closed form solution, the paper provides simulations to illustrate the working model. One conclusion is a natural point in time where real estate investing is supplanted by investing in financial assets.

Forecasting UK commercial real estate cycle phases with leading indicators: a probit approach

This paper examines the significance of widely used leading indicators of the UK economy for predicting the cyclical pattern of commercial real estate performance. The analysis uses monthly capital value data for UK industrials, offices and retail from the Investment Property Databank (IPD). Prospective economic indicators are drawn from three sources namely, the series used by the US Conference Board to construct their UK leading indicator and the series deployed by two private organisations, Lombard Street Research and NTC Research, to predict UK economic activity. We first identify turning points in the capital value series adopting techniques employed in the classical business cycle literature. Probit models are then estimated using the leading economic indicators as independent variables and forecast the probability of different phases of capital values, that is, periods of declining and rising capital values. The forecast performance of the models is tested and found to be satisfactory. The predictability of lasting directional changes in property performance represents a useful tool for real estate investment decision-making.

What Makes a Landlord? Ownership of Real Estate by US Households

Households supply about three-quarters of US rental housing. The paper examines the real estate investment decision and the proportion of wealth invested in real estate. Hypotheses drawn primarily from the real estate finance literature about the role of wealth, expected inflation, human capital, income tax rates, race, health, risk aversion and inheritance are tested against data from the Health and Retirement Study. Wealth has a powerful non-linear effect on ownership of real estate, but ownership is negatively associated with human capital. Marginal tax rates, race and property gifts affect real estate investment; poor health, risk aversion and expected inflation do not seem to.

What Makes a Landlord? Ownership of Real Estate by US Households

Households supply about three-quarters of US rental housing. The paper examines the real estate investment decision and the proportion of wealth invested in real estate. Hypotheses drawn primarily from the real estate finance literature about the role of wealth, expected inflation, human capital, income tax rates, race, health, risk aversion and inheritance are tested against data from the Health and Retirement Study. Wealth has a powerful non-linear effect on ownership of real estate, but ownership is negatively associated with human capital. Marginal tax rates, race and property gifts affect real estate investment; poor health, risk aversion and expected inflation do not seem to.

The present value model with time-varying discount rates: Implications for commercial property valuation and investment decisions

A vector autoregressive model is developed for predicting cash flow and returns in the private (unsecuritized) commercial property markets. The model predicts both of these variables quite well during the sample period. The forecasting model is then used to develop a simple “buy/sell” rule for identifying property market value peaks aud troughs. An improved present value model, taking account of the predictability of property returns, is described and found to track historical market values much more closely than does either the appraisal-based index or the traditional present value model with constant expected returns. Analysis in this paper suggests that most of the change in commercial property market values has been due to changes in expected returns, rather than to changes in expected future operating cash flows. Key Wordsr valuation, investment, present value model, timing, cycles, discount rates The present value model underlies all of modern financial economics, and lies at the heart of commercial property valuation and real estate investment decision making. Traditionally this model is applied by forecasting property net cash flows and discounting those cash flows at a constant discount rate. In this model the discount rate is meant to represent the expected return (that is, the internal rate of return or total return) to an investment in the property, thereby reflecting the opportunity cost of capital. In practice, the discount rate used in the present value model as applied to property valuation has not changed much over time, largely because analysts have not known how to quantify changes in the market’s expected return on pr0perty.i Recently, evidence has mounted that asset value changes in the securities markets are not consistent with the constant discount rate model or the constant expected return assumption? Campbell and Mei (1993), among others, have found that changes in stock prices over time are due more to changes in the market’s required total returns (including price changes), than to changes in the market’s cash flow expectations.3 Furthermore, changes in the market’s expected return can be forecasted to some extent, as has been demonstrated by Liu and Mei (1992, 1994) in the case of REITs, small stocks, and large stocks. This implies that asset price changes are more predictable than was previously thought, and that turning points in asset price cycles may be somewhat identifiable in advance!

Decision Support and Expert Systems for Real Estate Investment Decisions: A Review

Decisions about investment in commercial real estate projects are influenced by many factors, both quantitative and qualitative. With the aid of computerized decision support and expert systems, investors and developers are applying increasingly sophisticated forms of analyses to project screening, portfolio management, and other high-level decisions related to real property assets. In this field, even small improvements in decision making can have major monetary impact. Although many off-the-shelf and custom-built systems have been developed, these computer technologies have yet to be fully exploited by the real estate investment industry.