Need to Meet Investment Goals? Track Synthetic Indexes with the SDDP Method

Lorenzo Reus () and Rodolfo Prado ()
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Lorenzo Reus: Universidad Adolfo Ibañez
Rodolfo Prado: Universidad Adolfo Ibañez

Computational Economics, 2022, vol. 60, issue 1, No 3, 47-69

Abstract: Abstract This work presents a novel application of the Stochastic Dual Dynamic Problem (SDDP) to large-scale asset allocation. We construct a model that delivers allocation policies based on how the portfolio performs with respect to user-defined (synthetic) indexes, and implement it in a SDDP open-source package. Based on US economic cycles and ETF data, we generate Markovian regime-dependent returns to solve an instance of multiple assets and 28 time periods. Results show our solution outperforms its benchmark, in both profitability and tracking error.

Keywords: Dynamic asset allocation; Index tracking; SDDP; Julia; ALM; ETF (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10614-021-10133-6

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