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The purpose of this study is to evaluate the impact of theoretical knowledge related to financial behaviour and especially anchor effects.

The study design is based upon an experiment divided into two parts, before and after the development of the course curriculum for the course introducing behavioural finance for undergraduate real estate students.

The study concludes that the anchor effect is persistent also after introducing theoretical knowledge regarding financial behaviour and anchor effects. To conclude the results, in this study, indicates that the appraisal of properties are dependent on the individual’s cognitive capacity to mitigate anchor effects. There are epistemological assumptions underlying the belief in the individuals’ capacity to handle anchor effects that might provide biased appraisals. These assumptions need to be carefully tested and treated to increase the accuracy of property appraisals.

The study result also highlights the possibility that current literature in valuation, and learning activities, does not emphases and stimulate readers to critical thinking. This paper would, therefore, propose also other real estate education programmes to be aware of the potential lack of critical thinking among the students.

It provides an insight regarding how appraisal of properties is dependent on the individual’s cognitive capacity to mitigate anchor effects.

Building developments are often capital intensive, have a long payback period and many associated risks and uncertainties. This makes investments in building projects to be a big challenge. This study aims to develop a computerized simulation-based binomial model (CSBBM) for building investment appraisal with a view to improving the economic sustainability of proposed building projects.

Mathematical equations and algorithms were developed based on the binomial method (BM) of real options analysis and then implemented on a computer system. A hybrid algorithm that integrates Monte Carlo simulation (MCS) and BM was also developed. A real-life project was used to test the model. Sensitivity analysis was also conducted to explore the influence of input variables on development option value (DOV).

The test result shows that the model developed provides a better estimate of the value of an investment when compared with traditional net present value technique, which underestimate the value. Moreover, inflation rate (i) and rental value (Ri) are the most sensitive variables for DOV. An increase in i and Ri by just 5% causes a corresponding increase in DOV by 202% and 132%, respectively. While the least sensitive variable is the discount rate (r), as an increase in r by 5% causes a corresponding decrease in DOV by just 9%. The CSBBM is capable of determining the optimal time of development of buildings with an accuracy of 80.77%.

The hybrid model produces higher DOV than that of only the BM because MCS considers randomness in uncontrollable variables. Thus, building investment decision-makers should always use MCS to complement the BM in an investment analysis.

There is limited evidence on the use of this kind of hybrid model for determining DOV in practice.

The purpose of this paper is to present a basic model of commercial real estate valuation in which the capitalization rate is the critical variable, and to present empirical results for a study of office building capitalization rates.

The model is derived from standard economic and financial theories. The empirical study uses data from the sale of office buildings in 37 downtown markets for 2012. The empirical results are related to concepts of asset market efficiency.

The empirical results show that capitalization rates depend on features of the office buildings, vacancy rate, and recent change in the office building market as captured by the vacancy rate. In other words, investors are using variables implied by standard economic and financial theory and basic economic data from the recent past to determine the capitalization rate.

The empirical results show how investors determine capitalization rates for office buildings, so potential investors can gauge the state of a property market.

The paper shows that changes in capitalization rates are predictable; investors use past data to adjust their capitalization rates. Furthermore, if an investor does not agree that current trends will continue, then the investment decision should be determined accordingly. For example, if an investor thinks that the future will not be as robust as the recent past, then other investors will bid more than the investor thinks is reasonable. However, if the investor sees a future that is brighter than the recent past, it is time to buy.