UCLA

This thesis uses high-frequency data to characterize the volatility of asset prices within a trading day. The estimation procedure applies the generalized method of moments (GMM) to the Heston (1993) model of stochastic volatility. I apply the estimation to SPY in chapter 1 and to other 8 assets in chapter 2. I compare estimation results and discuss the implications and applicability of the model. In Chapter 3 I examine the path behavior of realized volatility and provide evidence that it is important to allow jumps in the Heston model.