Fusing Economic Indicators for Portfolio Optimization - A Simulation-Based Approach
Portfolio optimization and quantitative risk management have been extensively studied since the 1990s, and attracted even more attention after the financial crisis in 2008. Such a disastrous event required portfolio managers to better manage the risk and return trade-off when building their clients' portfolios. With that said, the advancement of machine-learning algorithms and computing resources helps portfolio managers explore rich information by incorporating the macro-economy conditions into their investment strategies and optimizing their portfolio performance in a timely manner. In this paper, we present a simulation-based approach by fusing eleven macroeconomic factors using Neural Networks (NN) to build an Economic Factor-based Predictive Model (EFPM). Then, we combine it with Copula-GARCH simulation model and the Mean-Conditional Value at Risk (Mean-CVaR) framework to derive an optimal portfolio comprised of six index funds. Empirical test on the achieved portfolio is conducted on an out-of-sample dataset utilizing a rolling-horizon approach. Finally, we compare its performance against the three benchmark portfolios over a twelve-year period (01/2007 - 12/2018). The results indicate that the proposed EFPM-based asset allocation strategy outperforms the three alternatives on many common metrics, including annualized return, 99% VaR, and Sharpe ratio
Year of publication: |
2020
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Authors: | Yu, Jiayang |
Publisher: |
[2020]: [S.l.] : SSRN |
Subject: | Portfolio-Management | Portfolio selection | Wirtschaftsindikator | Economic indicator | Theorie | Theory | Simulation |
Saved in:
freely available
Extent: | 1 Online-Ressource (8 p) |
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Series: | |
Type of publication: | Book / Working Paper |
Language: | English |
Notes: | Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments 2019 erstellt |
Other identifiers: | 10.2139/ssrn.3632467 [DOI] |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10012830505
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