Importance sampling in stochastic optimization: an application to intertemporal portfolio choice
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Publication:2183315
DOI10.1016/j.ejor.2019.01.013zbMath1441.90104OpenAlexW2909881945WikidataQ128596919 ScholiaQ128596919MaRDI QIDQ2183315
Publication date: 26 May 2020
Published in: European Journal of Operational Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ejor.2019.01.013
stochastic programmingMonte Carlo simulationportfolio optimizationscenario generationvariance reduction techniques
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The value and cost of more stages in stochastic programing: a statistical analysis on a set of portfolio choice problems ⋮ Adaptive step size rules for stochastic optimization in large-scale learning
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Cites Work
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