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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01ww72bd94x
Title: Volatility Targeting Portfolios: A Multi-Period Framework
Authors: Perricone, Jacob
Advisors: Sircar, Ronnie
Department: Operations Research and Financial Engineering
Class Year: 2016
Abstract: Numerous empirical as well as theoretical studies have demonstrated the superior performance of dynamic asset allocation strategies that target a constant volatility level through time. These volatility targeting strategies mitigate portfolio risk by adjusting the portfolio’s exposure based on updated volatility forecasts. However, most dynamic allocation strategies use a myopic optimization scheme; namely, they repeatedly solve a sequence of single period optimization problems. This paper will investigate the use of a multi-period decision model in the construction of volatility targeting portfolios. Counter to the predominant stochastic programming approach, which is hindered by its computational intractability, this thesis uses an optimization scheme that can be solved by readily available convex quadratic programming solvers. Exploring two different recourse policies, this paper finds that the multi-period approach outperforms the myopic scheme when measured on a risk-return basis.
Extent: 150 pages
URI: http://arks.princeton.edu/ark:/88435/dsp01ww72bd94x
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Operations Research and Financial Engineering, 2000-2016

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