Explaining Asset Price Movements: An Unobserved Components Approach

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This interesting and important project concerns the analysis of the movements of prices of long-term assets. Many economists and other financial analysts have tried to explain the movements of prices in the stock market. To do this they have introduced the concept of an efficient market, that is a market where the supply and demand forces are not inhibited in any way and which equilibrates very quickly. However, it is clear that the stock market often seems to fluctuate without any obvious external stimulus, and explaining price movements is often very difficult even after they are observed. Prediction is yet more difficult. Stock prices share some important characteristics with other macroeconomic variables such as the long-term bond yield, the exchange rate, and the level of private consumption expenditure. These variables play a key role in macroeconomic theory and policy, and they are greatly affected by the market participants's expectations about the future. Thus explaining their behavior is important. However, they display movements which are not driven by events elsewhere in the economy. The major goal of this project is to explain why long-term asset prices move as they do. The project consists of two main sections: 1) the development of a framework in which asset price levels, as well as expected asset returns can be explained, and 2) derivation of measures of the economic importance of the possible determinants of asset prices. Technically, Professor Campbell uses an analytical framework known as unobservable components, in which the unobservable state of the entire system evolves according to a transition equation, and the observed data are considered to be discrete realizations of the underlying continuous transition process. An important aspect of this research is that Professor Campbell compares the results of the unobserved components analysis with those of other standard techniques, such as Vector Autoregression analysis and general equilibrium models. He also extends the framework to include continuous time models.