Dynamic portfolio optimization with ambiguity aversion
Yunbi An
11月8日（星期二），10:00
A1039
This paper investigates portfolio selection in the presence of transaction costs and ambiguity about return predictability. We derive the optimal dynamic trading rule in closed form using the robust optimization method, and characterize its properties and the unique mechanism through which ambiguity aversion impacts the optimal robust strategy. In addition to the two trading principles documented in Gârleanu and Pedersen (2013), our model further implies that the robust strategy is to aim for a low expected loss. Ambiguity-averse investors trade toward an aim portfolio that gives less weight to highly volatile return-predicting factors, and loads less on the securities that have large and costly positions in the existing portfolio. Using data on various commodity futures, we show that the robust strategy outperforms the corresponding non-robust strategy in out-of-sample tests.
