Portfolio models with return forecasting and transaction costs

By Jing-Rung Yu, Wan-Jiun Paul Chiou, Wen-Yi Lee, Shunfu Lin. 2020

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Abstract In this paper, we advance portfolio models by incorporating return projection and further analyze their realized performance. To ensure practicality, the transaction costs and the optimization of short-selling weights are taken into account in portfolio rebalancing. Using the daily returns of international ETFs over a period of 14 years, the empirical results show that including return forecasting improves the realized performance due to more efficient asset allocation but not a reduction in trading costs. The models that are based on trade-off between return and volatility, such as the mean-variance and Omega models, show higher increases in performance than those mainly focus on controlling loss, such as the linearized value-at-risk, the conditional value-at-risk, and the downside risk. The superiority of forecasting risky portfolios over the equally-weighted diversification varies intertemporarily across various portfolio models. The benefit of inclusion of prediction is larger when the market is less volatile.

Subfields: Finance, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/db465a6cda0b282b3dc4ccb55da4d690896c210c