Essays on Empirical Asset Pricing

This dissertation includes three essays of empirical asset pricing. In the first essay, The Value/Growth Anomaly and Hard to Value Firms, I show that combining quality signals (firm fundamentals) and hard to value measures increases the return spread between value and growth portfolios. A portfolio that is long high quality value firms that are hard to value and short low quality growth firms that are hard to value yields a 4-factor alpha of up to 1.41% per month. Second, ex-ante observed quality signals are better at predicting high performance and low performance growth stocks as compared to value stocks. This growth stock mispricing can be explained by extreme quality measures, and enhanced by focusing on hard to value growth firms.;In the second essay, Using Maximum Drawdowns to Capture Tail Risk, I, along with my co-author Wesley R. Gray, propose the use of maximum drawdown, the maximum peak to trough loss across a time series of compounded returns, as a simple method to capture an element of risk unnoticed by linear factor models: tail risk. Unlike other tail-risk metrics, maximum drawdown is intuitive and easy-to-calculate. We look at maximum drawdowns to assess tail risks associated with market neutral strategies identified in the academic literature. Our evidence suggests that academic anomalies are not anomalous: all strategies endure large drawdowns at some point in the time series. Many of these losses would trigger margin calls and investor withdrawals, forcing an investor to liquidate.;In the third essay, Analyzing Valuation Measures: A Performance Horse Race over the Past 40 Years, I, along with my co-author Wesley R. Gray, show that EBITDA/TEV has historically been the best performing valuation metric and outperforms many investor favorites such as price-to-earnings, free-cash-flow to total enterprise value, and book-to-market. We also explore the investment potential of long-term valuation ratios, which replaces one-year earnings with an average of long-term earnings. In contrast to prior empirical work, we find that long-term ratios add little investment value over standard one-year valuation metrics.