Inside information of real estate developers

Information profoundly influences market trading. Real estate businesses are always prone to news about change. However, little work has been done on the relationship between inside information and performance of real estate equities. This paper investigates the likelihood of informed trading in equities issued by real estate developers. The paper adopts the framework of probability of informed trading (PIN), using high-frequency data from Hong Kong. Compared with Tay, Ting, Tse, and Warachka (2009)'s logistic model, this study provides a new and better approach, with Pareto distribution, to model time-varying probabilities of news. Importantly, it tackles the floating-point (FP) problem arising from large loads of financial data in numerical computation, by giving a better solution. The findings suggest that the likelihood of informed trading in equities happens among real estate developers. Particularly, the equities of mainland-based developers with lower market values have a higher chance of informed trading than those issued by HK-based developers of high market values. Somehow, a diversified business is less likely to be associated with informed trading. Furthermore, the liquidity of equities has an effect of dilution on informed trading. While this study focuses on real estate equities data, its proposed approach can be applied to the detection of likelihood of informed trading in other sectors.