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This study examines the impact of uncertainty on the asset allocation algorithm. The analysis concludes that ranges, rather than specific investment targets, should be the preferred method of mean-variance optimization. Ranges are not only statistically robust, but also circumvent many of the practical problems associated with owning an illiquid asset, such as valuation issues and lumpiness. Second, the study also examines the role of multi-family housing in a real estate portfolio in the presence of uncertainty. This study uses the Emerging Markets Data Base from the International Finance Corporation to examine emerging market real estate as an asset class using data on companies classified as real estate firms by SIC codes.