Semi-Universal Portfolios with Transaction Costs
Authors: Dingjiang Huang, Yan Zhu, Bin Li, Shuigeng Zhou, Steven C.H. Hoi
IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Empirical simulation on real historical markets show that SUP can overcome the drawback of existing UP based transaction cost aware algorithms and achieve significantly better performance. |
| Researcher Affiliation | Academia | 1Department of Mathematics, East China University of Science and Technology, Shanghai 200237, China 2School of Computer Science, Fudan University, Shanghai 200433, China 3Shanghai Key Lab of Intelligent Information Processing, Fudan University, Shanghai 200433, China 4Economics and Management School, Wuhan University, Wuhan 430072, China 5School of Information Systems, Singapore Management University, 80 Stamford Road 178902, Singapore |
| Pseudocode | Yes | Algorithm 1 Online factor graph implementation for SUP. Algorithm 2 Random walk implementation for m > 2. |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described, such as a specific repository link or an explicit code release statement. |
| Open Datasets | Yes | The first one is the well-known NYSE(O) dataset, which consists of 36 stocks in New York Stock Exchange for a 22-year period [Cover, 1991]. The second is SP500, which is the Stan-1All datasets and their compositions can be downloaded from http://olps.stevenhoi.org/. |
| Dataset Splits | No | The paper uses two datasets, NYSE(O) and SP500, and describes selecting '50 pairs of stocks' for investment. However, it does not provide specific data split information (e.g., exact percentages, sample counts, or a detailed splitting methodology) for training, validation, and testing. |
| Hardware Specification | No | The paper does not provide specific hardware details (such as exact GPU/CPU models, processor types, or memory amounts) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details, such as library or solver names with version numbers, that would be needed to replicate the experiments. |
| Experiment Setup | Yes | Here, we set q=100 in SUP-q, η=20 and α=0.1 in OLU. |