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The purpose of this paper is to present a methodology based on the transactional asset pricing approach (TAPA) and to illustrate the application of TAPA within the context of professional property valuation.

The TAPA is a novel analytical valuation methodology recasting the traditional derivations of the income approach techniques, including DCF, from a transactional perspective based on the principle of inter-temporal transactional equity, instead of the conventional investor-specific view originating from I. Fisher (1907, 1930).

The authors present DCF analysis as a specific case of a more general TAPA approach to valuation under the income method. This also leads to novel analytical derivations of the Direct income capitalization, Gordon, Inwood, Hoskold and Ring models. Based on the TAPA framework, the authors also research the value-enhancing effects of benchmark market volatility on the subject property value and conclude that such effects can be statistically significant depending on the DCF analysis period.

The research has a direct bearing on time-variable discount rate forecasting capabilities, as it uses a time-variant structure for the discount rates.

Using the US Case-Shiller and BLS rental indices as a valuation benchmark, the paper contains an example of applying the general TAPA framework to value a notional property under a TAPA’s DCF version. Such property valuations can be easily replicated in practice – especially in the context of equitable/fair value determination under the International Valuation Standards Council valuation standards.

TAPA is a deductive principles-based theory of asset valuation especially fit for the transactional and illiquid asset valuation contexts – thus enabling a more efficient pricing for such assets in a sense of reflecting the transactional interests of the parties more closely than achievable under the conventional valuation methods.

TAPA is an original filiation of research with roots going as far back as Aristotelian Catallactics. It contains analytical formalizations of certain transactional equity principles.

After completing this case, students should be able to: identify and compute relevant cash flows in relation to a real estate project and compute the net present value (NPV). Determine the target return or cost of capital (by looking at historical economic indicators). Design or formulate a sensitivity analysis to determine the drivers of the project value. Evaluate real estate and other investments taking qualitative and quantitative factors into consideration. Demonstrate the computation of a break-even rate to determine the minimum or maximum revenue or cost required for a project to be viable.

This case study is about the Golden Beak Securities Pension Fund that wanted to invest in a Hostel Project in one of the universities in Ghana. Most universities in Ghana faced an acute shortage of on-campus accommodation. Also, the Government of Ghana, in 2017, implemented a programme to make Senior High School in Ghana free. This was expected to increase the number of students who will enter the existing universities. The project was therefore seen as strategic, as it would help ease the pressure of on-campus accommodation while providing diversification for the pension fund. As part of the investment committee’s (IC) quest to improve the skill set available to it, especially in relation to real estate investments, Esi Abebrese was appointed as one of the members of the IC of GSB. Her main task was to collect information on key macroeconomic variables, as well as granular information on project costs and revenues and conduct investment appraisal. Esi was scheduled to make a presentation to the IC on the 15th of October 2019 following which the Committee will debate and make a decision. The project had an estimated cost of GH¢52m with a total number of 3,424 student beds and ancillary facilities. Undertaking the project required moving funds from investments in money market securities with one of the banks in Ghana. The investments in the money market securities were currently yielding about 16% a year. The determination of the cost of capital was critical and Esi and Nana eventually settled on a long-term weighted average cost of capital of 14%. This was after considering the trend of inflation, monetary policy rates, treasury rates, stock market returns and a report on returns on commercial real estate properties in Ghana. An exit capitalisation rate of 20% was also estimated for the purposes of determining the value of the property at the end of the investment horizon. Esi also obtained estimates of cost and revenue for the project and proceeded to carry out a feasibility analysis on the project. This consisted of an NPV analysis and sensitivity analysis on various factors to determine the drivers of the project value. The IC had to take several factors (both quantitative and qualitative) into consideration before making a decision. Esi believed that these factors included the diversification of the fund’s assets, the return on investment, potential oversupply of hostel accommodation, the social responsibility of providing student accommodation and the impact of any prolonged shutdown of the university.

Masters/advanced undergraduate.

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CSS 1: Accounting and Finance.

The purpose of the paper is to introduce a novel methodology to identify and quantify the difference of financial risks exhibited by listed and unlisted companies in their debt payments from an empirical point of view.

The paper attempts to establish the theoretical relationship between the agreed original periods and their corresponding periods of real payments. It is based on Krugman’s curve. This relationship has been implemented using data from listed and unlisted companies of Spain and from Western Europe countries (divided by companies, size and industry).

An alternative model has been implemented with the available information about listed and unlisted companies. There is not a significant difference in the financial risk level corresponding to listed and unlisted firms in Spain.

The paper could provide a useful guidance in applying the risk in project assessment.

This paper provides a new methodology to reduce the subjectivity shown in the treatment of risk by traditional approaches. The method allows to including the financial risk in the time parameter of the discount function. Analysis of the delays in debt payments by both listed and unlisted companies; Alternative model able to describe the expected delays from the initial agreed period; Inclusion of the financial risk in the parameter “time” of a discount function.

Believes that a feature of most closed‐end automobile leases is the right to purchase the car for a specified price at the termination of the lease. This characteristic of a closed‐end autombile lease is similar to a European call option and is transferred to the lessee at no explicit charge. Develops a methodology to calculate the value of the call option feature embedded in closed‐end automobile leases. Concludes that the rational lessee should lease autos that generate low option values.

This paper offers an introduction to dynamic economic planning under uncertainty, i.e. the use of econometric models together with mathematical optimization methods for the analysis and quantitative determination of optimal economic policies. The corresponding basic methodology (optimal feedback stochastic control of linear econometric models given a quadratic cost functional) is presented with particular regard to its practical application. The method is then applied for demonstration purposes to an econometric model of the Federal Republic of Germany.

The purpose of this study is to examine how the lodging market and the state economy affected by Hurricane Sandy have recovered from the damages sustained. Specifically, this study examines and predicts the influence of revenue management key performance indicators (KPIs) on recovery and lodging revenue in the affected states and the states’ economies. These KPIs include average daily rate (ADR), occupancy and revenue per available room (RevPAR).

Secondary financial data were collected for the states most damaged by Hurricane Sandy. Subsequently, pooled Ordinary Least Square (OLS) regression was conducted combining time and non-time dependent variables based on the states and radius from the landfall.

The results indicate that although the lodging market and the state economies have recovered since the onslaught of Hurricane Sandy, certain KPIs still need to improve.

Managerial implications are suggested in terms of dynamic pricing, market-based recovery, the KPIs, federal aid and facility management.

Despite its importance, research on the effects of climate change in the hospitality context has not actively progressed after Hurricane Katrina. Time and non-time dependent variables are combined in this analysis to gain a richer understanding of the impacts and recovery of KPIs on the revenue in the lodging market and the revenue on states’ economies. Additional analysis based on the radius from the landfall of the hurricane was performed to examine the impact and recovery based on geographical proximity.

The purpose of this paper is to assess life cycle costing (LCC) of the equipment in a more realistic, precise, and applicable manner, and to apply it to a real industrial problem.

Based on the failure rates of the components of a machine, the LCC is assessed, mathematically modeled, and incorporated to the parallel machine replacement problem with capacity expansion consideration. The problem is modeled as mixed integer programming which intends to minimize the total costs incurred during a planning horizon of several periods for the machines of the same type with different ages. The decision variables are the number of machines to be purchased/salvaged in each period. A genetic algorithm (GA) is developed for solving the problem and its efficiency is verified.

In conventional models presented for calculation of LCC, corrective maintenance (CM) costs of the machines are incorporated to the model as a whole which may result in inaccurate calculations. Obtaining this value is also very difficult and it can be different for machines with different ages. By calculating the CM costs of a machine based on the failure rates of its components, the LCC can be properly estimated in a realistic and precise manner. The presented GA is also proven to be efficient for solving problems of almost any size with different number of machines, components, and planning periods.

The presented model and GA are applied to a real case of a construction company that needs to determine a purchase/salvage schedule for its loaders in the next ten years. Results of the calculated schedule imply that employing new loaders rather than maintaining the aged ones generally results in the minimum LCC.

This paper presents a novel approach for precise, meaningful, and practical LCC calculation. The mathematical model and its solving method can be utilized by both the manufacturers and buyers of equipment as a tool which determines a parallel machine purchase/salvage schedule for a planning horizon of several periods which incurs minimum overall cost. The presented material can be also applied to other industrial problems and cases.

The purpose of this research is to show how the measurement of the effect of flooding on house value can be invaluable information for professional valuers and homeowners alike. In the UK, even for an event as devastating as the autumn 2000 flood, the number of properties affected in any one town is small and so robust estimation is problematic and methodology applied elsewhere needs modification. A new framework for analysing the effect of flooding on house value in the UK is presented.

Data issues play a crucial role in determining the methodology employed in any analysis. A repeat sales methodology is proposed which allows for the tracking of effects through time. The analysis can be extended to multiple sites via a block design thereby increasing the sample size.

Empirical analysis of one case study site demonstrates the inherent small sample problem and yet reveals patterns that fall in line with expected outcomes in many respects.

The case study results are illustrative only. A programme of further analysis is planned which includes comparison of the new framework with more traditional approaches.

A novel methodology is developed tracking the temporal variability in flood effect. The minimisation of data requirements inherent in the model allows for transfer to multiple sites and easy updating of the analysis.

The purpose of this study is to use a lifetime income measure to evaluate the long-run housing affordability for an understudied cohort of households in the literature – the millennials. The authors do this in the context of Malaysia, measuring long-run affordability for four housing types across geographic locations and income distributions.

This study calculates a long-run housing affordability index (HAI) using data on house prices and household incomes. Essentially a ratio of predicted lifetime incomes to house prices, the HAI is computed for four common housing types in Malaysia from 2005 to 2016 and for six states in the country. The HAI is also compared across four income percentiles.

The analysis reveals varying patterns of housing affordability among different states in Malaysia. Housing affordability has declined since 2010, with most housing types being unaffordable for millennial-led households with the lowest income. Housing is most affordable for those in the highest income bracket, although even here, there are pockets of unaffordable housing as well.

Based on the findings, this study proposes three targeted interventions to improve housing affordability for Malaysian millennials.

This study fills a gap in the literature by examining the long-run housing affordability of Malaysian millennial-led households based on both geographic location and income distribution. The millennial population is understudied in the housing affordability literature, making this study a valuable contribution to the field.