Estimation of the ex ante Distribution of Returns for a Portfolio of U.S. Treasury Securities via Deep Learning
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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| Format: | Working Paper biblioteca |
| Language: | English |
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World Bank, Washington, DC
2019-03
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| Subjects: | MACHINE LEARNING, NEURAL NETWORKS, CONVOLUTION, LSTM, MARKET RISK, SECURITIES PORTFOLIO, |
| Online Access: | http://documents.worldbank.org/curated/en/433791553192242300/Estimation-of-the-ex-ante-Distribution-of-Returns-for-a-Portfolio-of-U-S-Treasury-Securities-via-Deep-Learning https://hdl.handle.net/10986/31449 |
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dig-okr-10986314492024-10-17T09:29:11Z Estimation of the ex ante Distribution of Returns for a Portfolio of U.S. Treasury Securities via Deep Learning Foresti, Andrea MACHINE LEARNING NEURAL NETWORKS CONVOLUTION LSTM MARKET RISK SECURITIES PORTFOLIO 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. 2019-03-27T14:54:07Z 2019-03-27T14:54:07Z 2019-03 Working Paper Document de travail Documento de trabajo http://documents.worldbank.org/curated/en/433791553192242300/Estimation-of-the-ex-ante-Distribution-of-Returns-for-a-Portfolio-of-U-S-Treasury-Securities-via-Deep-Learning https://hdl.handle.net/10986/31449 English Policy Research Working Paper;No. 8790 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank application/pdf text/plain World Bank, Washington, DC |
| institution |
Banco Mundial |
| collection |
DSpace |
| country |
Estados Unidos |
| countrycode |
US |
| component |
Bibliográfico |
| access |
En linea |
| databasecode |
dig-okr |
| tag |
biblioteca |
| region |
America del Norte |
| libraryname |
Biblioteca del Banco Mundial |
| language |
English |
| topic |
MACHINE LEARNING NEURAL NETWORKS CONVOLUTION LSTM MARKET RISK SECURITIES PORTFOLIO MACHINE LEARNING NEURAL NETWORKS CONVOLUTION LSTM MARKET RISK SECURITIES PORTFOLIO |
| spellingShingle |
MACHINE LEARNING NEURAL NETWORKS CONVOLUTION LSTM MARKET RISK SECURITIES PORTFOLIO MACHINE LEARNING NEURAL NETWORKS CONVOLUTION LSTM MARKET RISK SECURITIES PORTFOLIO Foresti, Andrea Estimation of the ex ante Distribution of Returns for a Portfolio of U.S. Treasury Securities via Deep Learning |
| description |
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. |
| format |
Working Paper |
| topic_facet |
MACHINE LEARNING NEURAL NETWORKS CONVOLUTION LSTM MARKET RISK SECURITIES PORTFOLIO |
| author |
Foresti, Andrea |
| author_facet |
Foresti, Andrea |
| author_sort |
Foresti, Andrea |
| title |
Estimation of the ex ante Distribution of Returns for a Portfolio of U.S. Treasury Securities via Deep Learning |
| title_short |
Estimation of the ex ante Distribution of Returns for a Portfolio of U.S. Treasury Securities via Deep Learning |
| title_full |
Estimation of the ex ante Distribution of Returns for a Portfolio of U.S. Treasury Securities via Deep Learning |
| title_fullStr |
Estimation of the ex ante Distribution of Returns for a Portfolio of U.S. Treasury Securities via Deep Learning |
| title_full_unstemmed |
Estimation of the ex ante Distribution of Returns for a Portfolio of U.S. Treasury Securities via Deep Learning |
| title_sort |
estimation of the ex ante distribution of returns for a portfolio of u.s. treasury securities via deep learning |
| publisher |
World Bank, Washington, DC |
| publishDate |
2019-03 |
| url |
http://documents.worldbank.org/curated/en/433791553192242300/Estimation-of-the-ex-ante-Distribution-of-Returns-for-a-Portfolio-of-U-S-Treasury-Securities-via-Deep-Learning https://hdl.handle.net/10986/31449 |
| work_keys_str_mv |
AT forestiandrea estimationoftheexantedistributionofreturnsforaportfolioofustreasurysecuritiesviadeeplearning |
| _version_ |
1813417162273980416 |