Reference number : GC-2017-Q2-04271, amendment number : , agreement type : G, recipient legal name : Mazumdar, Ravi (University of Waterloo), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Collaborative Research and Development Grants - Project, program name french : Subventions de recherche et développement coopérative - projet, program purpose english : Algorithmic trading is an essential part of today's economy. This proposal in on the design and implementation of algorithmic trading in the context of ad auctions in the wireless mobile context. This work is being done in collaboration with our industrial partner Addictive Mobility, Toronto that provides cutting edge solutions for providing ad space to advertisers in the context of mobile wireless systems by trading on ad auction exchanges._x000D_
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The proposed research is to develop advanced algorithms that help improve the yield and maximize the profitability for algorithmic trading in the ad auction context. The key issues are bidding strategies that must operate at very fast time scales of around 100 milliseconds. The research will consist of three main components: 1) Development of models and techniques for ad space bidding given strict time constraints._x000D_
2) Development of algorithmic trading strategies, and 3) Implementation of strategies. We will work closely with our industrial partner in the 2nd and 3rd thrusts._x000D_
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The research will involve many components: 1) Building models of random interactions using ideas from random exchange theory, 2) Understanding the role of budget and time constraints both in terms of execution time as well as campaign time horizon, 3) Understanding the role of information in the context of actions, 4) Develop techniques and algorithms for price discovery, and 5) Development of real-time bidding algorithms that can operate on the information history within the constraints of the auction durations._x000D_
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The techniques will involve Markov models, mean field theory, stochastic decision theory, learning, and the development of algorithms., program purpose french : Algorithmic trading is an essential part of today's economy. This proposal in on the design and implementation of algorithmic trading in the context of ad auctions in the wireless mobile context. This work is being done in collaboration with our industrial partner Addictive Mobility, Toronto that provides cutting edge solutions for providing ad space to advertisers in the context of mobile wireless systems by trading on ad auction exchanges._x000D_
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The proposed research is to develop advanced algorithms that help improve the yield and maximize the profitability for algorithmic trading in the ad auction context. The key issues are bidding strategies that must operate at very fast time scales of around 100 milliseconds. The research will consist of three main components: 1) Development of models and techniques for ad space bidding given strict time constraints._x000D_
2) Development of algorithmic trading strategies, and 3) Implementation of strategies. We will work closely with our industrial partner in the 2nd and 3rd thrusts._x000D_
_x000D_
The research will involve many components: 1) Building models of random interactions using ideas from random exchange theory, 2) Understanding the role of budget and time constraints both in terms of execution time as well as campaign time horizon, 3) Understanding the role of information in the context of actions, 4) Develop techniques and algorithms for price discovery, and 5) Development of real-time bidding algorithms that can operate on the information history within the constraints of the auction durations._x000D_
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The techniques will involve Markov models, mean field theory, stochastic decision theory, learning, and the development of algorithms., agreement title english : Efficient algorithms for online ad markets with time constraints, agreement title french : Efficient algorithms for online ad markets with time constraints, agreement number : CRDPJ, agreement value : 150000.0, agreement start date : 2017-09-20, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2020-2021)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2020-2021)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada