Abstract
We introduce a simple and intuitive composite model for forecasting correlations for use in portfolio optimization. Each element of the composite model is based on a realized volatility model. To test our model, we consider an investor seeking to diversify an equity portfolio by including commodities. In a high-frequency setting, we demonstrate that significant economic gains can be achieved by basing portfolio decisions on our modeling framework. The gains depend on the quality of the chosen volatility model, and for our preferred model, they are economically significant despite the realistic constraints on short selling and portfolio turnover.
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