In recent times the emergence of the property cycle and the effects that it has on the property market has caused the relevant parties involved in the market to start placing more emphasis on how these cycle works. The overall objective of this study is to try establish if the interpretation of market related data affects at what position these parties are relative to one another on the property curve. The study concentrates on the use of market indicators, indices and variables in trying to determine an individual’s position on the property market curve. It also concentrates on how this market data is retrieved and what effect it has on how they interpret the data. The methodology adopted for this study involves the collecting and interpretation of market related indices and indicators relevant to the property market over a ten year period from 1996 through to 2006. This data was then used to establish the key indicators used. A questionnaire was sent out to the relevant parties involved in the property market to ascertain the extent of what the main sources of market information are and how this data is collected and interpreted. This was limited to individuals in the Gauteng region. The data was examined and collected in the form of line graphs, histograms and pie charts. The data was then examined and presented in four areas: the major sources of information used by parties for market related data, to try and establish where these parties are relative to one another on the property curve, the effect that the different types of sources of information has on each party and finally to try determine by how much these parties lag or lead one another on the curve.

The number of building projects in Taiwan has rapidly increased each year, and the vacancy rate has reached a peak at 19.7%, an astonishing number. Therefore, this study examines the financial performance of property firms who execute building projects by calculating their Economic Value Added (EVA) and Economic Value Added Momentum (EVA Momentum). In addition, because numerous financial factors may affect EVA, this study examines how these factors influence the EVA of property firms to ascertain which factors are relevant. Furthermore, this study monitors the EVA of these firms to determine their relationship with the property cycle index to establish whether a causality exists between them.