Asset bubbles are one of the most dangerous phenomena in an economy. They can go unnoticed for long periods of time and then burst, causing massive economic damage. The two most infamous examples of recent asset bubbles are the 2000 Dot Com bubble and the 2007 housing bubble. Both of these bubbles resulted in recessions and severe economic damage. The 2007 Subprime Mortgage Crisis, a direct result of the housing bubble bursting, was the greatest economic crisis since the Great Depression. Given how dangerous asset bubbles can be, it is a wonder that they have not received greater attention. Being able to predict and avoid asset bubbles would be a great service to the world economy, yet it is incredibly difficult to do so. This thesis aims to change that.
This thesis will define what asset bubbles are and will review the existing literature on them. A model will then be created to predict economic trouble in the form of recessions. This model will include financial and economic indicators chosen for their predictive power. These indicators are federal debt, private debt, the Federal Funds rate, The CBOE Volatility Index, and the yield curve. Once this predictive model is created, an in-depth review of the chosen indicators will look for unusual behavior leading up to the 2000 and 2007 bubbles. With this two-step systematic model, this thesis hopes to provide a method of predicting the likelihood of an asset bubble. Of course, predicting and addressing an asset bubble are two different things. This thesis will also discuss the ramification of successfully predicting an asset bubble, and how regulators and the market should handle this information. The results are encouraging in that there were concerning signs of economic trouble prior to both the 2000 and 2007 bubbles' existences. These signs can be used in diagnoses of future potential bubbles.