Abstract
We study positional portfolio management strategies in which the manager maximizes an expected utility function written on the cross-sectional rank (position) of the portfolio return. The objective function reflects the manager's goal to be well-ranked among competitors. To implement positional allocation strategies, we specify a nonlinear unobservable factor model for the asset returns which disentangles the dynamics of the cross-sectional distribution and the dynamics of the ranks of the individual assets. Using a large dataset of stocks returns we find that positional strategies outperform standard momentum, reversal and mean-variance allocation strategies, as well as equally weighted portfolio for criteria based on position.
| Original language | English |
|---|---|
| Pages (from-to) | 650-706 |
| Number of pages | 57 |
| Journal | Journal of Financial Econometrics |
| Volume | 19 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 1 Jan 2021 |
| Externally published | Yes |
Keywords
- Big data
- Equally weighted portfolio
- Factor model
- Fund tournament
- Momentum
- Positional good
- Positional risk aversion
- Rank
- Reversal
- Robust portfolio management