Author : Na Li
Publisher : Open Dissertation Press
ISBN 13 : 9781374670716
Total Pages : pages
Book Rating : 4.6/5 (77 download)
Book Synopsis The Informational Content of Indirect Real Estate Options by : Na Li
Download or read book The Informational Content of Indirect Real Estate Options written by Na Li and published by Open Dissertation Press. This book was released on 2017-01-27 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation, "The Informational Content of Indirect Real Estate Options: Evidence From Hong Kong" by Na, Li, 李娜, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Abstract of Thesis Titled The Informational Content of Indirect Real Estate Options: Evidence from Hong Kong Submitted by LI Na For the degree of Doctor of Philosophy At The University of Hong Kong in December 2006 There has been ample research on the relationship between the implied volatility of financial options and the realized volatility of the underlying stock. Empirical results on whether or not implied volatility contains information on future realized volatility have been mixed. This study contributes to this area of research by analyzing the informational content of derivative warrants (financial options) of property companies (indirect real estate) in Hong Kong. Previous studies suggested that there is a strong link between the prices of indirect real estate and those of direct real estate. However, there has been no research on the link between the options of indirect real estate and direct real estate. Using a sample of listed companies with a relatively long history of warrants listed on the Hong Kong Stock Exchange, I found that there was no obvious relationship between the implied volatility and the realized volatility of the underlying stock. This is consistent with the results from previous studies. However, with regard to direct real estate, the informational content of implied volatility is different for the two broad categories of indirect real estate, namely investment companies and development companies. Investment companies hold properties for investment purposes. Their major source of revenue is rental income. I found that the implied volatility of the warrant of investment companies contained future information on the volatility of direct real estate. This result is expected, since the financial market is more liquid, and therefore, changes in the economic and political environment (such as interest rate movements and changes in fiscal and economic policies in Hong Kong and Mainland China) that are likely to affect the volatility of rental income will first be reflected in the warrant market. The results are, however, different for development companies. I found that the implied volatility of development companies contains information about the historical volatility of direct real estate. That is, the warrants of property development companies are priced based on historical volatility in the direct real estate market, which is a less liquid market. This apparently counterintuitive result can be explained by property development risk and the uncertainties that developers have to face than pricing presale housing units. The property developer has to bear the development risk in addition to fluctuations in property prices. The sources of development risks come mainly from the uncertainty in obtaining approvals from various government departments. Furthermore, in many cases, there is also uncertainty involved in negotiations with different stakeholders and pressure groups. Development risk may also vary according to the nature and timing of a development project. In essence, development risks are unique, and therefore, historical events have little predictive power. On the other hand, when developers sell their units in the presale market, they often face the problem of setting the right presale price that optimizes total profit. In the price searching process,
