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Periodic Double Auctions (PDAs) are commonly used in the real world for trading, e.g. in stock markets to determine stock opening prices, and energy markets to trade energy in order to balance net demand in smart grids, involving trillions…

Computer Science and Game Theory · Computer Science 2019-11-26 Susobhan Ghosh , Sujit Gujar , Praveen Paruchuri , Easwar Subramanian , Sanjay P. Bhat

In real time electricity markets, the objective of generation companies while bidding is to maximize their profit. The strategies for learning optimal bidding have been formulated through game theoretical approaches and stochastic…

Artificial Intelligence · Computer Science 2021-01-08 Jahnvi Patel , Devika Jay , Balaraman Ravindran , K. Shanti Swarup

Contextual dynamic pricing aims to set personalized prices based on sequential interactions with customers. At each time period, a customer who is interested in purchasing a product comes to the platform. The customer's valuation for the…

Machine Learning · Statistics 2023-03-07 Yiyun Luo , Will Wei Sun , and Yufeng Liu

We study discrete-time predictable forward processes when trading times do not coincide with performance evaluation times in a binomial tree model for the financial market. The key step in the construction of these processes is to solve a…

Mathematical Finance · Quantitative Finance 2023-12-05 Gechun Liang , Moris S. Strub , Yuwei Wang

We propose a dynamic model of a prediction market in which agents predict the values of a sequence of random vectors. The main result shows that if there are agents who make correct (or asymptotically correct) next-period forecasts, then…

Probability · Mathematics 2024-02-27 Nina Badulina , Dmitry Shatilovich , Mikhail Zhitlukhin

Algorithmic trading in modern financial markets is widely acknowledged to exhibit strategic, game-theoretic behaviors whose complexity can be difficult to model. A recent series of papers (Chriss, 2024b,c,a, 2025) has made progress in the…

Computer Science and Game Theory · Computer Science 2025-06-10 Michael Kearns , Mirah Shi

Recent literature on online learning has focused on developing adaptive algorithms that take advantage of a regularity of the sequence of observations, yet retain worst-case performance guarantees. A complementary direction is to develop…

Machine Learning · Computer Science 2015-01-27 Ali Jadbabaie , Alexander Rakhlin , Shahin Shahrampour , Karthik Sridharan

This paper addresses the portfolio selection problem for nonlinear law-dependent preferences in continuous time, which inherently exhibit time inconsistency. Employing the method of stochastic maximum principle, we establish verification…

Mathematical Finance · Quantitative Finance 2023-11-15 Zongxia Liang , Jianming Xia , Fengyi Yuan

We provide a natural learning process in which a financial trader without a risk receives a gain in case when Stock Market is inefficient. In this process, the trader rationally choose his gambles using a prediction made by a randomized…

Machine Learning · Computer Science 2011-05-24 Vladimir Trunov , Vladimir V'yugin

Statistical properties of order-driven double-auction markets with Bid-Ask spread are investigated through the dynamical quantities such as response function. We first attempt to utilize the so-called {\it Madhavan-Richardson-Roomans model}…

Trading and Market Microstructure · Quantitative Finance 2011-04-01 Takero Ibuki , Jun-ichi Inoue

Follow-The-Regularized-Leader (FTRL) is known as an effective and versatile approach in online learning, where appropriate choice of the learning rate is crucial for smaller regret. To this end, we formulate the problem of adjusting FTRL's…

Machine Learning · Computer Science 2024-03-12 Shinji Ito , Taira Tsuchiya , Junya Honda

In this paper, we study the contextual dynamic pricing problem where the market value of a product is linear in its observed features plus some market noise. Products are sold one at a time, and only a binary response indicating success or…

Machine Learning · Computer Science 2022-05-05 Jianqing Fan , Yongyi Guo , Mengxin Yu

In the optional prisoner's dilemma (OPD), players can choose to cooperate and defect as usual, but can also abstain as a third possible strategy. This strategy models the players' participation in the game and is a relevant aspect in many…

Computer Science and Game Theory · Computer Science 2021-06-15 Leonardo Stella , Dario Bauso

We study the problem of computing a competitive equilibrium with approximately optimal bundles in Fisher markets with separable piecewise-linear concave (SPLC) utility functions, meaning that every buyer receives a $(1-\delta)$-optimal…

Computer Science and Game Theory · Computer Science 2026-05-01 Argyrios Deligkas , John Fearnley , Alexandros Hollender , Themistoklis Melissourgos

Pricing decisions stand out as one of the most critical tasks a company faces, particularly in today's digital economy. As with other business decision-making problems, pricing unfolds in a highly competitive and uncertain environment.…

Computer Science and Game Theory · Computer Science 2024-09-04 Daniel García Rasines , Roi Naveiro , David Ríos Insua , Simón Rodríguez Santana

Traditional pricing paradigms, once dominated by static models and rule-based heuristics, are increasingly being replaced by dynamic, data-driven approaches powered by machine learning algorithms. Despite their growing sophistication, most…

Machine Learning · Computer Science 2025-12-01 Marco Mussi , Marcello Restelli

Market equilibria of matching markets offer an intuitive and fair solution for matching problems without money with agents who have preferences over the items. Such a matching market can be viewed as a variation of Fisher market, albeit…

Computer Science and Game Theory · Computer Science 2017-04-03 Saeed Alaei , Pooya Jalaly , Eva Tardos

In this work, we study a generalized Fisher market model that incorporates social influence. In this extended model, a buyer's utility depends not only on their own resource allocation but also on the allocations received by their…

Computer Science and Game Theory · Computer Science 2025-01-14 Mandar Datar

We report on new stability conditions for evolutionary dynamics in the context of population games. We adhere to the prevailing framework consisting of many agents, grouped into populations, that interact noncooperatively by selecting…

Populations and Evolution · Quantitative Biology 2021-07-08 Semih Kara , Nuno C. Martins

We study a general class of repeated auctions, such as the ones found in electricity markets, as multi-agent games between the bidders. In such a repeated setting, bidders can adapt their strategies online based on the data observed in the…

Computer Science and Game Theory · Computer Science 2021-07-14 Orcun Karaca , Pier Giuseppe Sessa , Anna Leidi , Maryam Kamgarpour