Detection of the Bubble Crash in Financial and Real Estate Markets-Noise Trading and Energy Perspectives
Date Issued
2010
Date
2010
Author(s)
Liu, Chang-Fu
Abstract
This paper proposes the hypotheses about noise traders’ irrational behavior before collapsing from noise trading and energy perspective and employs the HHT, which is a time frequency method, to observe whether there is a significant difference between regular fluctuations of markets and crashes in high frequency volatility in the stock and real estate markets. Furthermore, the paper presents two indicators, which are HFV and PRH to detect the financial crash and use these two indicators to analyze the historical data.
We observe that the value of indicators increasing tremendously before collapsing from two indicators’ graphs and use the ROC (Receiver operating characteristic) curve to verify our indicators’ discrimination and the AUC (Area under curve) value, which equals 0.9436. The result shows that the indicators have an excellent discrimination between detecting collapse and non-collapse.
Finally, we apply the indicators in different indexes and offer the typeⅠ、typeⅡ errors under different thresholds to investors who have different risk preferences so that investors can choose a proper detection mechanism and exit the market in time before collapsing. With the detection mechanism, the government can make precautions for the economic, social, and political problems that collapse brings.
Subjects
Noise trading
Volatility
Crash
Type
thesis
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