Risk Premia and Lévy Jumps: Theory and Evidence
提出一类新的时变Lévy模型，能捕捉杠杆效应和跳跃风险，用交易量代理不可观测的时变过程，通过期权定价分析发现无限活动跳跃过程具有显著风险溢价且优于有限活动过程。
Abstract We develop a novel class of time-changed Lévy models, which are tractable and readily applicable, capture the leverage effect, and exhibit pure jump processes with finite or infinite activity. Our models feature four nested processes reflecting market, volatility and jump risks, and observation error of time changes. To operationalize the models, we use volume-based proxies of the unobservable time changes. To estimate risk premia, we derive the change of measure analytically. An extensive time series and option pricing analysis of sixteen time-changed Lévy models shows that infinite activity processes carry significant jump risk premia, and largely outperform many finite activity processes.