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Estimation of the ex ante Distribution of Returns for a Portfolio of U.S. Treasury Securities via Deep Learning

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  • Foresti,Andrea

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 Series 8790, The World Bank.
    • Handle: RePEc:wbk:wbrwps:8790
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