The purpose of this paper is to present results on inverse optimization in the case of portfolios that have been optimized under constraints. Inverse optimization yields implied views that represent investors? expectations on market performance. While literature mainly considers the unconstrained case, we will focus on views that can be derived from constrained portfolios. The implied views are derived in the form of spreads representing the loss of explanatory power with an increasing number of constraints. Applying the Black Litterman model allows the incorporation of the derived views as an additional source of information within the further asset allocation process.
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The purpose of this paper is to present results on inverse optimization in the case of portfolios that have been optimized under constraints. Inverse optimization yields implied views that represent investors? expectations on market performance. While literature mainly considers the unconstrained case, we will focus on views that can be derived from constrained portfolios. The implied views are derived in the form of spreads representing the loss of explanatory power with an increasing number of...
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