Two essays on the predictability of asset prices:"Benchmarking problems and long horizon abnormal returns"and,"Low R square in the cross section of expected returns"

This dissertation consists of two essays on predictability of asset prices. "Benchmarkingproblems and long horizon abnormal returns" and, "Low R-square in the cross section ofexpected returns". Long run abnormal returns following Initial Public Offerings (IPOs),Seasoned Equity Offers (SEO) and other firm level events are well documented in the financeliterature. These findings are difficult to reconcile in an efficient markets world. I examine theseriousness of potential benchmarking errors on the measurement of abnormal returns. I findthat the simpler, more parsimonious models perform better in practice and finds that excessperformance is not predictable regardless of the APM. Thus, the long run underperformancefollowing SEOs found in the literature is consistent with market efficiency because excessperformance itself is not predictable.In the other essay, "Low R-square in the cross section of expected returns", I examine the“low R-square” phenomenon observed in the literature. CAPM predicts exact linear relationshipbetween return and betas (SML). This means that estimated time series betas for firms should berelated with firms’ future returns. However, the estimated betas have almost no relationship withfuture returns. The cross-sectional R2 are surprising low (3% average) while time series R2 arehigher (around 30 % average). He develops a simple asset pricing model that explains thisphenomenon. Even in a perfect world where there are no errors in the benchmark measurementor estimation of the price of market risk the difference in R-squares can be quite large due to thedifference in variance between the “market” and average returns. I document that marketvariance exceeds the variance of average returns, with few exceptions, for the last 74 years.