Publication: Estimation of the ex ante Distribution of Returns for a Portfolio of U.S. Treasury Securities via Deep Learning
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Date
2019-03
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Published
2019-03
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Abstract
This paper presents different deep neural network architectures designed to forecast the distribution of returns on a portfolio of U.S. Treasury securities. A long short-term memory model and a convolutional neural network are tested as the main building blocks of each architecture. The models are then augmented by cross-sectional data and the portfolio's empirical distribution. The paper also presents the fit and generalization potential of each approach.
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“Foresti, Andrea. 2019. Estimation of the ex ante Distribution of Returns for a Portfolio of U.S. Treasury Securities via Deep Learning. Policy Research Working Paper;No. 8790. © World Bank. http://hdl.handle.net/10986/31449 License: CC BY 3.0 IGO.”
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