Event Modeling

Events, such as earnings announcements, significantly affect options prices, resulting in complex W-shaped implied volatility curves and discontinuous ATM vol and curvature term structures. Event Modeling decomposes the “dirty” volatility surface implied from the market into a “clean” or de-evented volatility surface with positive curvature and a smooth parameter term structure and the event jump distribution.

This distribution is modeled as either discrete or Merton jumps at the time of the announcement. With this module, you 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 size, width, and probability for this announcement?
• Do different expiries price the same event distribution?
• How would the dirty implied vol curve look under particular event jump parameters?