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An $alpha$-Stable Limit Theorem Under Sublinear Expectation

  • Event Date: November 17, 2015
  • Event End Date: November 17, 2015
  • Event Start Time: 11:45 AM
  • Event End Time: 12:45 PM
  • Event Location: Hill 705
  • Event Type: Mathematical Finance and Probability Seminars
  • Extra Info: Alexander Munk, U Michigan
Speaker: Alexander Munk, U Michigan
Location: Hill 705
Slides: ( TBA )

ABSTRACT
For $alpha in left( 1 , 2 ight)$, we present a generalized central limit theorem for $alpha$-stable random variables under sublinear expectation. The foundation of our proof is an interior regularity estimate for partial integro-differential equations (PIDEs). A classical generalized central limit theorem is recovered as a special case, provided a mild but natural additional condition holds. Our approach contrasts with previous arguments for the result in the linear setting which have typically relied upon tools that are nonexistent in the sublinear framework, e.g., characteristic functions.