Transaction-Cost-Conscious Pairs Trading via Approximate Dynamic Programming
Abstract/Contents
- Abstract
- In this paper, we develop an algorithm that optimizes logarithmic utility in pairs trading. We assume price processes for two assets, with transaction cost linear with respect to the rate of change in portfolio weights. We then solve the optimization problem via a linear programming approach to approximate dynamic programming. Our simulation results show that when asset price volatility and transaction cost are sufficiently high, our ADP strategy offers significant benefits over the chosen baseline strategy. Our baseline strategy is an optimized version of a pairs trading heuristic studied in the literature.
Description
| Type of resource | text |
|---|---|
| Date created | 2006-06-01 |
Creators/Contributors
| Author | Yan, Xiang |
|---|---|
| Advisor | Van Roy, Benjamin |
| Department | Stanford University. Department of Computer Science. |
Subjects
| Subject | Algorithms |
|---|---|
| Subject | Dynamic programming |
| Subject | Investment analysis |
| Genre | Thesis |
Bibliographic information
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- Use and reproduction
- User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
Preferred citation
- Preferred Citation
- Yan, Xiang (2006). Transaction-Cost-Conscious Pairs Trading via Approximate Dynamic Programming. Stanford Digital Repository. Available at: http://purl.stanford.edu/tm700dc0091
Collection
Undergraduate Theses, School of Engineering
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