This paper proposes a new structural option pricing model, which is estimated using the method of simulated moments (MSM) based on the joint data of stocks and options. The estimated model explains well the observed unconditional and conditional vola...
This paper proposes a new structural option pricing model, which is estimated using the method of simulated moments (MSM) based on the joint data of stocks and options. The estimated model explains well the observed unconditional and conditional volatility smirks in option pricing. The driving forces are a slow moving external habit and i.i.d. consumption jumps which induce jumps in stock prices. Habit formation generates excess return volatility, which is tightly linked to the price levels of ATM (at-the-money) options quoted in terms of Black-Scholes implied volatility (B/S-vol), while jumps generate the observed variations in B/S-vol across varying degrees of moneyness. The model also has predictions about the term structure of option pricing, historical smirk premia backed out of historical consumption, and a wide variety of stock pricing features which are all verified by the data. The model's asset pricing implications are robust to more realistic assumptions about the dividend process.