This dissertation consists of two essays in asset allocation. In the first essay, I measure the value of active money management. I explore this issue by comprehensively examining the parametric rule proposed by Brandt, Santa-Clara and Valkanov (2009) (the BSV rule) out-of-sample for portfolio selection among 3516 stocks in CRSP and comparing this rule to the mean-variance (MV) rule and the naïve 1/N rule recently advocated by DeMiguel, Garlappi and Uppal (2009). The BSV rule outperforms both the MV and 1/N rules and the outperformance is robust to investment horizons and stock market states. The BSV rule is effective for investors with different preferences or investment opportunities. The effectiveness of the BSV rule is robust to data screening criteria, estimation periods, portfolio performance evaluation models, the business cycle, and stock market states. In the second essay, I explore the question of whether macroeconomic state variables are able to predict cross-sectional stock returns from the perspective of asset allocation. I find that conditioning on macroeconomic state variables leads to optimal portfolios with a Carhart alpha that is 125 basis points per month higher than unconditional optimal portfolios out-of-sample. Unfortunately, conditioning on macroeconomic states is subject to an "overfitting" problem and can lead investors to experience unexpected huge losses. My results suggest that macroeconomic state variables mare able to predict cross-sectional stock returns but risk-averse investors need to combine other funds (e.g. market portfolio) to take advantage of this predictability.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/293404 |
| Date | January 2013 |
| Creators | Zhang, Huacheng |
| Contributors | Lamoureux, Christopher, Cederburg, Scott, Hirano, Keisuke, Sias, Richard, Lamoureux, Christopher |
| Publisher | The University of Arizona. |
| Source Sets | University of Arizona |
| Language | English |
| Detected Language | English |
| Type | text, Electronic Dissertation |
| Rights | Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. |
Page generated in 0.0021 seconds