Registered Data

[00572] Model uncertainty for statistical arbitrage

  • Session Time & Room : 2E (Aug.22, 17:40-19:20) @F412
  • Type : Contributed Talk
  • Abstract : We consider an optimal stopping problem that addresses \textit{model uncertainty}, which affects the model assumptions, e.g., the parameters embedded in the probability distribution. The result presented in this talk shows the explicit form of the boundary indicating the optimal stopping time, assuming the portfolio value as an Ornstein-Uhlenbeck process. Applying our method might make statistical arbitrage more robust because the trading code for statistical arbitrage often depends on incorrect estimation.
  • Classification : 60G40, 60G10, 91G80
  • Format : Talk at Waseda University
  • Author(s) :
    • Daisuke Yoshikawa (Kansai University)