[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.
