The authors examined five alternative equity indices (AEIs) in the United States using
industries instead of individual stocks as building blocks to form portfolios and compared their …

METHODS Three popular AI models, recursive partitioning, neural networks, and genetic
algorithms, are initially trained during an in-sample period from January 1975 through …

This article discusses the necessity of managing the futures contract roll and argues that
most commodity index providers set futures rollover rules in an inefficient manner. Generally, …

Binary modeling may be used in order to constrain the num-ber of stocks in an optimal portfolio.
Such modeling allows an exact resolution of the number problem raised by Jansen and …

Although various income statement–based measures predict the cross section of stock
returns, direct method cash flow measures have even stronger predictive power. We transform …

… at that same point, the analysis performed by Mouakhar and Roberge is akin to studying the
failure … a high degree of uncertainty: five of Mouakhar and Roberge’s strategies have annual …

Under the paradigm of factor investing, we create a global factor allocation strategy using
country indexes and portfolio construction methodologies that are robust to estimation error. …

Stock return momentum and reversal have been known for well over a decade. This work
documents two new momentum effects that are even stronger than effects documented to date: …

Commodities entice investors for two main reasons: inflation protection, and portfolio diversification
(low correlations with other asset classes). Given these important benefits, and rising …

Dynamic portfolio analysis looks at the portfolio as a moving object to capture the essentials
of a long-short investment management strategy. To see the forest rather than the trees …