TY - JOUR
T1 - Data-generating process uncertainty
T2 - What difference does it make in portfolio decisions?
AU - Tu, Jun
AU - Zhou, Guofu
PY - 2004/5
Y1 - 2004/5
N2 - As the usual normality assumption is firmly rejected by the data, investors encounter a data-generating process (DGP) uncertainty in making investment decisions. In this paper, we propose a novel way to incorporate uncertainty about the DGP into portfolio analysis. We find that accounting for fat tails leads to nontrivial changes in both parameter estimates and optimal portfolio weights, but the certainty-equivalent losses associated with ignoring fat tails are small. This suggests that the normality assumption works well in evaluating portfolio performance for a mean-variance investor.
AB - As the usual normality assumption is firmly rejected by the data, investors encounter a data-generating process (DGP) uncertainty in making investment decisions. In this paper, we propose a novel way to incorporate uncertainty about the DGP into portfolio analysis. We find that accounting for fat tails leads to nontrivial changes in both parameter estimates and optimal portfolio weights, but the certainty-equivalent losses associated with ignoring fat tails are small. This suggests that the normality assumption works well in evaluating portfolio performance for a mean-variance investor.
KW - Asset pricing tests: Investments
KW - Bayesian analysis
KW - Data generating process
KW - t distribution
UR - https://www.scopus.com/pages/publications/1842659070
U2 - 10.1016/j.jfineco.2003.05.003
DO - 10.1016/j.jfineco.2003.05.003
M3 - Article
AN - SCOPUS:1842659070
SN - 0304-405X
VL - 72
SP - 385
EP - 421
JO - Journal of Financial Economics
JF - Journal of Financial Economics
IS - 2
ER -