Yong Zhang, Jiahao Li, Xingyu Yang, and Hong Lin. "Aggregating exponential gradient expert advice for online portfolio selection under transaction costs" Journal of the Operational Research Society, 2023, 74(8): 1940-1953.

As an application of machine learning techniques in the field of portfolio management, online portfolio selection (OLPS) aims at optimising the allocation of wealth in an uncertain environment. When making investment decisions, the transaction cost is such an important factor that investor should not ignore. Thus, this paper extends an existing online portfolio selection strategy Continuous Aggregating Exponential Gradient (CAEG) (Yang et al., 2022) in the presence of transaction costs. The proportional transaction costs model is constructed when the transaction costs are incorporated into the decision-making process, and we call this new strategy CAEGc. Theoretical guarantee proves that the mean of the logarithmic cumulative wealth of CAEGc has an asymptotic upper bound with that of its benchmark. The numerical examples demonstrate the impact of transaction costs on the proposed CAEGc strategy on the one hand, and on the other hand, verify that CAEGc outperforms other related OLPS strategies and is comparable to its benchmark strategy.

There is always risk of loss in trading. All trading strategies are used at your own risk

• Yong Zhang
• Jiahao Li (contact: [email protected])
• Xingyu Yang
• Hong Lin

• School of Management, Guangdong University of Technology

This project would not have been finished without using the codes from the following open source projects:

• Online Portfolio Selection toolbox

We welcome contributions from the community, including but not limited to:

• Bug fixing
• A more detailed discussion of transaction costs

Please consider citing our work if you find our code/paper is useful to your work.

@article{zhang2023aggregating,
	title     = {Aggregating exponential gradient expert advice for online portfolio selection under transaction costs},
	author    = {Zhang, Yong and Li, Jiahao and Yang, Xingyu and Lin, Hong},
	journal   = {Journal of the Operational Research Society},
	volume    = {74},
	number    = {8},
	pages     = {1940--1953},
	year      = {2023},
	publisher = {Taylor \& Francis}
}

@article{yang2022aggregating,
    title     = {Aggregating exponential gradient expert advice for online portfolio selection},
    author    = {Yang, Xingyu and He, Jin'an and Zhang, Yong},
    journal   = {Journal of the Operational Research Society},
    volume    = {73},
    number    = {3},
    pages     = {587--597},
    year      = {2022},
    publisher = {Taylor \& Francis}
}