Essays On Asset Pricing: Predictability, Information, And Liquidity

This dissertation is a collection of essays on Asset Pricing: Predictability, Information, and Liquidity. The ?rst chapter, ?Predictability of Equity Returns over Di?erent Time Horizons: A Nonparametric Approach? aims to test an important hypothesis in ?nan, cial economics: whether equity returns are predictable over various horizons? We ?rst propose a nonparametric test to examine the predictability of equity returns, which can be interpreted as a signal-to-noise ratio test. Our empirical results show that the short rate, dividend yields and earnings yields have good predictability power for both short and long horizons, which is di?erent from both the conventional wisdom and Ang and Bekaert (2007). Also, using our nonparametric test, a comprehensive in-sample and out-of-sample analysis documents that the predictor variables (dividend yields, earnings yields, dividend payout ratio, short rate, in? ation, book-to-market ratio, investment to capital ratio, corporate issuing activity, and consumption, wealth, and income ratio) have predictability power on equity returns but this cannot be well captured by linear prediction models. In addition, we use the nonparametric test to compare the conventional long-horizon prediction regression models on predictor variables with the historical mean model, where there has exists a debate about which model has better forecasting power for equity returns (Campbell and Thompson (2007) and Goyal and Welch (2007)). We ?nd that the prevailing prediction model has a better forecasting power than the historical mean model because the former has a lower neglected signal-to-noise ratio. Finally, we ?nd that our nonparametric predictive models have lower RMSE than the historical mean model at both short-horizon and long-horizon. Using our nonparametric methods, both combined and individual forecast outperform the historical average. The second chapter, ?An Intraday Analysis of Related Investment Vehicles Traded in the NYSE and AMEX? undertakes an intraday analysis of related , investment vehicles traded in the NYSE and AMEX. I investigate how the trading behaviors of three related investment vehicles (American Depository Receipt, Exchange-traded Fund, and Closed-end Fund) di?er across countries using highfrequency intraday data. I ?nd that ADRs trade at transaction prices that are on average worse than ETFs and CEFs. The trading of ADRs, ETFs, and CEFs follows positive feedback strategies. The buy and sell trades of the three securities are driven by the net order imbalances and past returns of three securities themselves. The correlated trading behaviors of the three securities can be explained by momentum traders with a common information set. The third chapter, ?Endogenous Information Acquisition, Cost of Capital, and Comovement of Equity Returns? investigates endogenous information acquisition, , cost of capital, and comovement of equity returns. The traditional asset pricing model cannot provide a good explanation for the comovement of asset returns. This chapter introduces endogenous costly information acquisition that generates comovement of asset returns in a rational expectations framework. The private information signals observed by many investors contain information not only about the value of the asset itself, but also the value of many other assets. This common source of information causes excessive covariance in their returns. If informed investors acquire more private information, or more investors are informed, the comovement of asset returns will increase. On the other hand, if informed investors aggressively obtain abundant private information, the comovement will decrease. We also ?nd that both greater precision in private information and higher cost of information will increase a company? cost of capital.