| My dissertation aims to explain two features of Asset Pricing: the "high tech bubble" and the return comovement anomaly.;In Chapter One, I show that a generalized version of the standard neoclassical investment model can explain the relatively high equity prices in the late 1990s and early 2000s in the US corporate nonfinancial and NASDAQ sectors along with the relatively low prices before and after this period. Stock returns predicted by the model are as volatile as the observed stock returns in both sectors. Three key model assumptions are multiple capital goods, investment-specific technological change and non-quadratic adjustment costs. During the "bubble" period, investment in equipment is relatively high---consistent with high expected cash flows and high prices. Investment rates subsequently fall---consistent with lower expected cash flows and lower prices. On average, managers' forecasts are correct. Increases in the growth rate of equipment investment coincide with decreases in measured productivity growth. This is consistent with the unobserved diversion of labor from producing output towards accumulating human capital or other intangible assets.;In Chapter Two, I examine the role of information in explaining excess comovement in asset returns. Many studies have documented stock return comovement above and beyond that predicted by standard asset pricing models. Furthermore, when stocks are added to an index, their betas with respect to that index tend to increase. I find that much of this excess comovement can be explained by correlated information. If individual analysts earnings forecast errors are correlated across stocks, the stock return correlations should be higher than fundamental correlations. I develop a measure of correlated analyst coverage to test this hypothesis and find: (1) Stocks with similar analysts tend to exhibit more excess comovement, (2) On average, when a stock enters the S&P 500 index, the same analysts that cover other S&P 500 stocks begin to cover the new stock, and (3) Changes in excess comovement are larger for stocks with larger increases in correlated analyst coverage around this event. This measure does not seem to be proxying for correlations in risk or unexpected earnings. |
