Computing efficient frontiers using estimated parameters

By Mark Broadie. 1993

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Citations in the corpus

Incorporating estimation errors into portfolio selection: Robust portfolio construction (2006, background): “As defined by Broadie (1993), the terms ‘true frontier’, ‘estimated frontier’, and ‘actual frontier’ are used to refer to the efficient frontiers computed using the true expected returns (unobservable), estimated expected returns and true expected returns of the portfolios on the estimated frontier,”
Multi-asset portfolio optimization and out-of-sample performance: an evaluation of Black–Litterman, mean-variance, and naïve diversification approaches (2017, unknown): “…when applied in an asset management setting, estimation errors in input parameters (Jobson and Korkie 1981a; Michaud 1989), corner solutions (Broadie 1993), and high transaction costs, resulting from extreme portfolio reallocations (Best and Grauer 1991), often result in a poor…”
Robust Portfolio Selection Problems (2003, methodology): “Several techniques have been suggested to reduce the sensitivity of the Markowitz-optimal portfolios to input uncertainty: Chopra (1993) and Frost and Savarino (1988) propose constraining portfolio weights, Chopra et al. (1993) proposes using a James-Stein estimator (see Huber 1981 for details on St”
Size Matters: Optimal Calibration of Shrinkage Estimators for Portfolio Selection (2011, background): “As a result, mean-variance portfolios computed from sample estimators perform poorly out of sample; see, for instance, Jobson and Korkie (1981); Best and Grauer (1991); Broadie (1993); Britten-Jones (1999); DeMiguel, Garlappi, and Uppal (2009).”
Stability analysis of portfolio management with conditional value-at-risk (2007, background): “Most notably, Kallberg and Ziemba (1984), Broadie (1993) and Chopra and Ziemba (1993) examined the relative effects of estimation errors in the mean, variance and covariance of asset returns on mean-variance efficient portfolios.”
A Generalized Approach to Portfolio Optimization: Improving Performance by Constraining Portfolio Norms (2009, background): “This general framework relies on solving the traditional minimum-variance problem (based on the sample covariance matrix) but subject to the additional constraint that the norm of the portfolio-weight vector be smaller than a given threshold.”
Markowitz Revisited: Mean-Variance Models in Financial Portfolio Analysis (2001, unknown): “, by Best and Grauer [16], Jobson [93], Broadie [25], Chopra and Ziemba [30], Best and Ding [15], and MacLean and Weldon [133].”