An Empirical Analysis of Return on Investment Maximization in Sponsored Search Auctions
Abstract/Contents
- Abstract
In this thesis I empirically investigate whether bidders are maximizing their return on investment (ROI) across multiple keywords in sponsored search auctions. I classify bidders based on the minimum perturbations that must be applied to their bids in order for various conditions to be satisfied.
I show that a large fraction of bidders in the Yahoo Webscope first price data set may be following ROI-based strategies.
Description
| Type of resource | text |
|---|---|
| Date created | 2008-05 |
Creators/Contributors
| Author | Auerbach, Jason |
|---|---|
| Advisor | Roughgarden, Tim |
| Advisor | Sundararajan, Mukund |
| Department | Stanford University. Department of Computer Science. |
Subjects
| Subject | Internet auctions |
|---|---|
| Subject | Electronic commerce > Management |
| Subject | Auctions > Mathematical models |
| Genre | Thesis |
Bibliographic information
Access conditions
- 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
- Auerbach, Jason (2008). An Empirical Analysis of Return on Investment Maximization in Sponsored Search Auctions. Stanford Digital Repository. Available at http://purl.stanford.edu/sv915zg2311
Collection
Undergraduate Theses, School of Engineering
View other items in this collection in SearchWorksContact information
- Contact
- engreference@stanford.edu
Also listed in
Loading usage metrics...