Adaptive Trading Technologies |
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| Course Overview | |||||
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Automated or semi-automated trading technologies are slowly finding their way into a number of different environments (for example, stock exchange, eBay, and energy trading). They enable users (whether individuals or organizations) to rapidly evaluate a significantly larger number of options than any human decision maker could. Potential benefits include faster response to changing market conditions and higher profits. With annual supply chain transactions worth trillions of dollars worldwide, supply chain trading technologies are attracting the attention of a growing number of researchers and enterprises. “Adaptive Trading Technologies” (17-814) is a hands-on, research-oriented course that will introduce students to adaptive trading technologies, focusing on supply chain scenarios. The course will expose students to fundamental research challenges and key adaptive trading technologies. The course format will combine discussion of research papers with the design and evaluation of supply chain trading technologies in the context of the upcoming 2007 supply chain trading competition. This is an annual tournament that requires looking at the dynamic market interactions that take place when multiple organizations concurrently compete in overlapping customer and supplier markets. Since its launch in 2003, the Competition has grown to include an international community of 150 researchers from universities and companies in over 15 countries. The best technologies developed as part of the course are expected to form the basis for CMU’s entry in the 2007 tournament, which will take place in the summer of 2007. |
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| Format | |||||
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Discussion of research papers along with design, implementation and evaluation of supply chain trading technologies |
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| Target Audience & Prerequisites | |||||
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This course is intended for students interested in gaining hands-on understanding of automated trading technologies. The course is primarily intended for graduate students, though it is open to particularly strong seniors and juniors in computer science. Minimally, students are expected to have taken 15-211 (Fundamental Algorithms and Data Structures) and 15-251 (Great Theoretical Ideas in Computer Science - I) or equivalent courses. They are also expected to be proficient in Java and have had courses in probability theory and statistics. Prior exposure to advanced search techniques, learning techniques and/or game theory is a plus but is not required. |
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| Number of Units | |||||
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This is a 12-unit course |
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| Meeting Times | |||||
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To be announced. |
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| Grading | |||||
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Based on class participation, student presentations and course projects. |
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| Textbooks | |||||
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Some Useful References can be found here |
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| Course Webpage | |||||
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The course website has been moved to the university blackboard system |
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