Event Modeling

Events, such as earnings announcements, significantly affect options prices, resulting in complex W-shaped implied volatility curves and steep ATM vol and curvature term structures on the short end. The Event Modeling framework allows one to decompose the “dirty” volatility surface implied directly from the market into a “clean” or “de-evented” volatility surface, with a much smoother parameter term structure, and the event jump distribution.

This distribution is modeled as either discrete or Merton jumps at the time of the announcement (two jumps, at least, are needed, one up, one down). With this module, one can calibrate the event jump distribution from a given dirty vol surface or convert between the clean and dirty surfaces using specified event jump parameters.

Use Event Modeling to answer questions Like:

• What does the market imply about the jump sizes, widths, and probabilities for this event?
• Do different expiries price in the same event distribution?