This paper examines the market efficiency of the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) Futures after the announcement of Quantitative Easing (QE) policy. Order imbalance is used to explore the relationship between return and order imbalance. We find that under the unconditional OLS model, lagged order imbalances almost have no significantly positive predictive power for current return. Nonetheless, on the trading day after the announcement of QE 1 policy, one-minute interval data show that the lagged order imbalance has predictive power for current return. Under the conditional OLS model, the reversed relation between current return and lagged order imbalance is not universal; on the other hand, after the announcement of QE 2 policy, the reversed relation between current return and lagged order imbalance is more common. Moreover, under volatility-GARCH (1, 1), one-minute interval data shows significantly positive relation between order imbalance and volatility.

In this paper, we explore the valuation performance of Heston and Nandi GARCH (HN GARCH) model on the pricing of options of financial stocks listed for AMEX during pre and post financial crisis periods. We find that the GARCH pricing model presents better performance than the traditional Black-Scholes model for the out-of-sample option pricing, no matter what the moneyness and the time-to-maturity. Specifically, the models show the effects of liquidity is not significant. Intuitionally, smaller liquidity tends to exhibit more pricing errors, especially for longer mature options. Unfortunately, we cannot get the expected outcomes, which is that the period of post financial crisis tend to have larger pricing errors. In sum, except more computational convenience, the HN GARCH model offers another vision of the relationship between liquidity and its effect on pricing errors.