  We relax a number of assumptions in Alexeev and Tapon (2012) in order to
account for non-normally distributed, skewed, multi-regime, and leptokurtic
asset return distributions. We calibrate a Markov-modulated Levy process model
to equity market data to demonstrate the merits of our approach, and show that
the calibrated models do a good job of matching the empirical moments. Finally,
we argue that much of the related literature on portfolio diversification
relies on assumptions that are in tension with certain observable regularities
and which, if ignored, may lead to underestimation of risk.
