A Study of Speculative Bubbles in Financial and Real Estate Markets using Hilbert-Huang Transform

Abstract

The recent bull markets around the world have led many academics and practitioners to predict if there exist asset price bubbles. To judge whether there is an asset price bubble, economist usually use a model of the fundamental value to check the existence of bubbles. Since the fundamental value is related to the future expectation and uncertainty of the market, economists sometimes define bubbles differently. Due to the difficulties associated with the assessment of the fundamental value, one can hardly detect bubbles using a standard model. Therefore, our main question in this study is “What is the difference between bubbles and regular fluctuations (market fundamental value) of stock markets and real estate markets?” Using the Augmented Dickey-Fuller (ADF) unit root test, we find that the stock market indexes are non-stationary. Furthermore, many empirical results suggest that the economic behavior, like investors’ attitudes toward risk and expected return, are nonlinear. The Hilbert-Huang Transform (HHT) which is developed by Huang et al. (1998) is a new method that can better study both nonlinear and nonstationary data. Using HHT, this paper seeks to answer whether there is a significant difference between market fundamentals and speculative bubbles and how to identify the signals that can detect the formation and crash of economic bubbles. A valid signal for detecting bubbles can help investors or government monitor the health condition and anomalies of real estate and financial markets and prevent major economic losses.