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Title: Robust portfolio optimization with covariates
Authors: Heng, Darren Kai Hong
Keywords: Science::Mathematics::Applied mathematics::Optimization
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Heng, D. K. H. (2022). Robust portfolio optimization with covariates. Final Year Project (FYP), Nanyang Technological University, Singapore.
Abstract: In this project, we propose ARIMA regression as a methodology for the inclusion of covariate information into a robust CVaR minimization portfolio as a method to improve the performance of the portfolio optimization model. This methodology is compared with a robust CVaR minimization portfolio and an equal weights portfolio and is found to have poor performance in terms of Sharpe ratio and certainty-equivalent return but exhibits better performance when it comes to maximum drawdown. This suggests that while the methodology is flawed, it still holds promise in certain niche applications.
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SPMS Student Reports (FYP/IA/PA/PI)

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