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The Univariate Collapsing Method for Portfolio Optimization

Department of Banking and Finance, University of Zurich, Zurich 8032, Switzerland
Swiss Finance Institute, Zurich 8006, Switzerland
Academic Editor: In Choi
Econometrics 2017, 5(2), 18;
Received: 9 October 2016 / Revised: 4 February 2017 / Accepted: 17 February 2017 / Published: 5 May 2017
The univariate collapsing method (UCM) for portfolio optimization is based on obtaining the predictive mean and a risk measure such as variance or expected shortfall of the univariate pseudo-return series generated from a given set of portfolio weights and multivariate set of assets under interest and, via simulation or optimization, repeating this process until the desired portfolio weight vector is obtained. The UCM is well-known conceptually, straightforward to implement, and possesses several advantages over use of multivariate models, but, among other things, has been criticized for being too slow. As such, it does not play prominently in asset allocation and receives little attention in the academic literature. This paper proposes use of fast model estimation methods combined with new heuristics for sampling, based on easily-determined characteristics of the data, to accelerate and optimize the simulation search. An extensive empirical analysis confirms the viability of the method. View Full-Text
Keywords: asset allocation; backtest-overfitting; non-ellipticity asset allocation; backtest-overfitting; non-ellipticity
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MDPI and ACS Style

Paolella, M.S. The Univariate Collapsing Method for Portfolio Optimization. Econometrics 2017, 5, 18.

AMA Style

Paolella MS. The Univariate Collapsing Method for Portfolio Optimization. Econometrics. 2017; 5(2):18.

Chicago/Turabian Style

Paolella, Marc S. 2017. "The Univariate Collapsing Method for Portfolio Optimization" Econometrics 5, no. 2: 18.

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