Yihong Xia

Stock price volatility and equity premium

Abstract A dynamic general equilibrium model of stock prices is developed which yields a stock price volatility and equity premium that are close to the historical values. Non-observability of the expected dividend growth rate introduces an element of learning which increases the volatility of stock price. Calibration to the U.S. dividend and consumption processes yield interest rate and stock price processes that conform closely to the styled facts for the U.S. capital market.

Risk and valuation under an intertemporal capital asset pricing model

We analyze the risk characteristics and valuation of assets in an economy in which the investment opportunity set is described by the real interest rate and the maximum Sharpe ratio. We show that, holding constant the beta of the underlying cash flow, the beta of a security is a function of the cash flow maturity. For parameter values estimated from U.S. data, the security beta always increases with the maturity of the underlying cash flow, while discount rates for risky cash flows can be increasing, decreasing, or nonmonotone functions of that maturity.

Persistence, Predictability, and Portfolio Planning

We use a model of stock price behavior in which the expected rate of return on stocks follows an Ornstein- Uhlenbeck process to show that levels of return predictability that cause large variation in valuation ratios and offer significant benefits to dynamic portfolio strategies are hard to detect or measure by standard regression techniques, and that the R 2 from standard short run predictive regressions carry little information about either long run predictability or the value of dynamic portfolio strategies. We propose a new approach to portfolio planning that uses forward-looking estimates of long run expected rates of return from dividend discount models. We show how such long run expected rates of return can be used to estimate the instantaneous expected rate of return under the assumption that the latter follows an Ornstein-Uhlenbeck process. Simulation results using four different estimates of long run rates of return on U.S. common stocks suggest that this approach may be valuable for long horizon investors.