Factor Timing
Valentin Haddad
University of California, Los Angeles and NBER
Serhiy Kozak
University of Maryland
Shrihari Santosh
University of Colorado Boulder

The optimal factor timing portfolio is equivalent to the stochastic discount
factor. We propose and implement a method to characterize both empirically.
Our approach imposes restrictions on the dynamics of expected returns, leading
to an economically plausible SDF. Market-neutral equity factors are strongly
and robustly predictable. Exploiting this predictability leads to substantial
improvement in portfolio performance relative to static factor investing. The
variance of the corresponding SDF is larger, is more variable over time, and
exhibits dierent cyclical behavior than estimates ignoring this fact. These
results pose new challenges for theories that aim to match the cross-section of
stock returns.