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Essays on Asset Pricing in Production Economies

Chen, Andrew Y
http://rave.ohiolink.edu/etdc/view?acc_num=osu1398770166

Abstract Details

2014, Doctor of Philosophy, Ohio State University, Business Administration.
This dissertation examines the modeling of asset prices in production economies. Chapter 1 presents a model which endogenizes a key mechanism of many theories of aggregate asset prices. In order to generate time-varying risk premia, many theories assume time-varying volatility. Chapter 1 shows that this channel can be endogenized with precautionary saving motives. Precautionary motives prescribe that, in bad times, next period's consumption should be very sensitive to economic news. High sensitivity in bad times results in time-varying consumption volatility, even in the presence of homoskedastic shocks. This channel is made visible by modeling production, and is amplified with external habit preferences. An estimated model featuring this channel quantitatively accounts for excess return and dividend predictability regressions. It also matches the first two moments of excess equity returns, the risk-free rate, and the second moments of consumption, output, and investment. Chapter 2 shows that the model of Chapter 1 not only addresses aggregate asset prices, but can also be extended to address key facts about the cross section of stock returns. This result is important because a solution to the equity premium puzzle should be informative about risk in general. I add idiosyncratic productivity to the model from Chapter 1. I find that the model's expected returns are log-linear in book-to-market equity, consistent with the data. Moreover, the slope of the relationship is similar. In both the model and the data, a 20% higher book-to-market implies a 100 b.p. increase in expected returns. The result is robust. It requires neither operating leverage nor asymmetric adjustment costs. Rather, value firms are low productivity firms, and mean reversion causes them to have high cash flow growth. This prediction is inconsistent with conventional wisdom, but consistent with recent empirical evidence. I present additional empirical evidence showing that value firms have high cash flow growth according to a number of definitions of cash flow. High cash flow growth means that value firms' cash flows are distributed toward the future, and, as a result, their prices are more exposed to discount rate shocks that drive the external habit model. The value premium is compensation for this high exposure. Chapter 3 examines general restrictions on production technologies implied by asset prices. It shows that representative firm models which are consistent with asset price data require either large capital adjustment costs, or volatile investment-specific technology shocks. These restrictions hold regardless of preferences, beliefs, operating leverage, or the completeness of asset markets. The restrictions summarize the sense in which asset prices are anomalous with respect to the theory of optimal investment.
Lu Zhang (Advisor)
Xiaoji Lin (Committee Member)
René Stulz (Committee Member)
Julia Thomas (Committee Member)
176 p.
Finance
Asset Pricing, Macroeconomics, Equity Premium Puzzle, Volatility Puzzle, Value Premium

Recommended Citations

Citations

  • Chen, A. Y. (2014). Essays on Asset Pricing in Production Economies [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1398770166

    APA Style (7th edition)

  • Chen, Andrew. Essays on Asset Pricing in Production Economies. 2014. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1398770166.

    MLA Style (8th edition)

  • Chen, Andrew. "Essays on Asset Pricing in Production Economies." Doctoral dissertation, Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1398770166

    Chicago Manual of Style (17th edition)

osu1398770166
1,043
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This open access ETD is published by The Ohio State University and OhioLINK.