Dynamism of Property Market in Malaysia- An Empirical Perspective

Property cycle can be regarded as a logical order of recurrent happenings with irregular fluctuations in the property market. These events influence property’s supply and demand and consequently affect the property sector. property cycle indicator (PCI) is crucial to foretelling and determining the real property cycle fluctuation in a particular country and even globally where policy makers and investors can employ early precautions and alternatives to avoid any detrimental circumstances that can be foreseen. The government plays a crucial role in promoting economic growth and financial stability. By obtaining information about future property market trends, more effective and suitable policy can be created and implemented to avoid property bubbles. Due to significant fluctuations in the modern property market cycle and major property price hikes, it is of interest to forecast the property market cycle for a whole economy. A directional accuracy test results are also presented on indicator construction analysis to determine the accuracy of PCI in forecasting the property market condition. Directional accuracy test results show that the constructed PCI can predict Malaysia’s major property cycle turning points with up to 62.1% accuracy. Although the directional accuracy rate for the nationally owned MHPI recorded best up till 62.6%, a directional accuracy of less than 50.0% is tracked at lag 6. Moreover, binomial test results call for a rejection of the null hypothesis at the 10% significance level for both PCI and MHPI, indicating that the constructed PCI performs better than the wild guess. Based on the empirical analysis, the movement of PCI is consistent in advance of PSU, suggesting that the PCI has a significant amount of signaling attributes against the PSU. To further examine the amount of signaling attributes, the BB dating algorithm was used and the findings suggested that the constructed PCI yields a medium lead time for the Malaysian property market. Selection of financial, macroeconomic and property-related variables as the component series used in this book is also justified.