Bubbles and Behavioral Finance

Hong Kong housing is commonly known as one of the most unaffordable housing in the world. The housing bubble is formed due to low interest rates, a limited amount of housing supply and speculation. Even though the Hong Kong government launched countercyclical housing policies to stabilize the market, the inflating housing bubble was unstoppable. The situation continued until the emergence of COVID-19, which brought a huge negative shock to the market. This paper revisits the housing bubble by using the right-tailed ADF test and provides useful policy recommendations at the end.

The purpose of this paper is to study bubbles solutions to the Cagan hyperinflation models under rational expectations. Both the price and exchange rate bubbles are considered. Specifications of the Cagan model under rational expectations will be briefly described, in which the price and exchange rate series are expressed in first-order linear difference equations. The particular and the homogenous solutions to the Cagan model can then be derived. The particular or fundamental solution characterizes a unique dynamic movement of an underlying fundamental process. Several representations of the fundamental solution will be explored. The homogenous or bubble solution is non-unique in a rational expectations framework. Some examples of bubble solution with different dynamic properties are specified. Also, examples of bursting bubble specifications will be illustrated. It is concluded that the problems of multiple solutions make indirect tests more attractive than direct tests for bubble detection. In addition, the general solution, which is just the sum of particular and homogenous solutions, will be discussed. Hence, the bubble paths are characterized as any deviations of the general solution from the fundamental solution when the model is specified correctly.

The purpose of this paper is to test for the presence of price and exchange rate bubbles in Cagan's model using data from the interwar European hyperinflations of Germany, Hungary, and Poland. Markov-switching cointegration test would be adopted for the empirical analysis. Then, the regime-shifting behaviour of time series variables is assumed to depend on unobservable states generated by a first-order Markov chain. The probability law that governs the Markov-switching regimes is advantageous in that it is more flexible and allows the data to determine the specific form of nonlinearities that are consistent with the sample information. Inferences about the probabilities of the unobservable states at each point in time can also be made.

We extend Hon’s (2012) paper to identify and analyse the important factors that capture the behaviour of small investors in the Hong Kong stock market, especially during the financial crisis. Exploratory factor analysis is employed to analyze the data, we find that the reference group is the most important factor and monitoring investments is the second important factor.

In the literature, the relationship between stock price and economic variables was examined in different countries. The findings confirmed the existence of fundamental variables in the Hong Kong stock market. This paper focuses on the case of Hong Kong and extends this issue to the Hang Seng sub-indexes, which include the Commerce and Industry Sub-index, the Finance Sub-index, the Properties Sub-index and the Utilities Sub-index, by applying the Vector Error Correction Model based on the sample from January 2004 to August 2014. Applying Johansen’s (1991) method, cointegration is found between each of the sub-indexes and different sets of economic variables, including price level, money supply, effective exchange rate, long-term interest rate, China stock market and industry-related variables. The results show that the long-run coefficients of some economic variables vary in size and sign in the cointegrating vectors in different sub-index models. Granger causality results conclude that all four sub-indexes are long-run Granger-caused by the economic variables with different speeds of adjustment. The paper also finds that industry-specific variables, relative to the macroeconomic fundamentals, are playing modest roles in determining the long-run equilibrium of the stock indexes. In addition, impulse responses and variance decomposition analysis are performed to show the relative strength of the causal chain between the sub-indexes and economic variables. This paper could draw implications for investors in their decision-making process about how the stock performance in various sectors is affected by different economic fundamentals.