This thesis consists of four empirical essays on option-implied information and asset pricing in the US market.The first essay examines the predictive ability of option-implied volatility measures proposed by previous studies by using firm-level option and stock data. This essay documents significant non-zero returns on long-short portfolios formed on call-put implied volatility spread, and implied volatility skew. Cross-sectional regressions show that the call-put implied volatility spread is the most important factor in predicting one-month ahead stock returns. For two-month and three-month ahead stock returns, “out-minus-at” of calls has stronger predictive ability.The second essay constructs pricing factors by using at-the-money option-implied volatilities and their first differences, and tests whether these pricing factors have significant risk premiums. However, results about significant risk premiums are limited.The third essay focuses on the relationship between an asset’s return and its sensitivity to aggregate volatility risk. First, to separate different market conditions, this study focuses on how VIX spot, VIX futures, and their basis perform different roles in asset pricing. Secondly, this essay decomposes the VIX index into two parts: volatility calculated from out-of-the-money call options and volatility calculated from out-of-the-money put options. The analysis shows that out-of-the-money put options capture more useful information in predicting future stock returns.The fourth essay concentrates on systematic standard deviation (i.e., beta) and skewness (i.e., gamma) by incorporating option-implied information. Portfolio level analysis shows that option-implied gamma performs better than historical gamma in explaining portfolio returns at longer horizons (five-month or longer). In addition, firm size plays an important role in explaining returns on constituents of the S&P500 index. Finally, cross-sectional regression results confirm the existence of risk premiums on option-implied components for systematic standard deviation and systematic skewness calculation.