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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

As a fundraising method, Initial Coin Offering (ICO) has raised billions of dollars for thousands of startups in the past two years. Existing ICO mechanisms place more emphasis on the short-term benefits of maximal fundraising while…

Computer Science and Game Theory · Computer Science 2020-02-27 Mingyu Guo , Zhenghui Wang , Yuko Sakurai

We study a demand response problem from utility (also referred to as operator)'s perspective with realistic settings, in which the utility faces uncertainty and limited communication. Specifically, the utility does not know the cost…

Optimization and Control · Mathematics 2017-08-11 Pan Li , Hao Wang , Baosen Zhang

The smart grid vision entails advanced information technology and data analytics to enhance the efficiency, sustainability, and economics of the power grid infrastructure. Aligned to this end, modern statistical learning tools are leveraged…

Machine Learning · Statistics 2015-06-17 Vassilis Kekatos , Yu Zhang , Georgios B. Giannakis

We consider a scenario where a retailer can set different prices for different consumers in a smart grid. The retailer's objective is to maximize the revenue, minimize the operating cost, and maximize the consumer's welfare. The retailer…

Optimization and Control · Mathematics 2021-11-09 Diptangshu Sen , Kushaagra Goyal , Varun Ramamohan , Arnob Ghosh

We study a general online combinatorial auction problem in algorithmic mechanism design. A provider allocates multiple types of capacity-limited resources to customers that arrive in a sequential and arbitrary manner. Each customer has a…

Computer Science and Game Theory · Computer Science 2023-10-10 Xiaoqi Tan , Alberto Leon-Garcia , Yuan Wu , Danny H. K. Tsang

With a novel search algorithm or assortment planning or assortment optimization algorithm that takes into account a Bayesian approach to information updating and two-stage assortment optimization techniques, the current research provides a…

Theoretical Economics · Economics 2023-07-19 Dipankar Das

This paper studies the application of machine learning in extracting the market implied features from historical risk neutral corporate bond yields. We consider the example of a hypothetical illiquid fixed income market. After choosing a…

Mathematical Finance · Quantitative Finance 2018-06-06 Greg Kirczenow , Ali Fathi , Matt Davison

Demand response (DR) has been demonstrated to be an effective method for reducing peak load and mitigating uncertainties on both the supply and demand sides of the electricity market. One critical question for DR research is how to…

Machine Learning · Computer Science 2023-06-27 Jun Song , Chaoyue Zhao

Dynamic pricing models often posit that a $\textbf{stream}$ of customer interactions occur sequentially, where customers' valuations are drawn independently. However, this model is not entirely reflective of the real world, as it overlooks…

Machine Learning · Computer Science 2024-06-10 Titing Cui , Su Jia , Thomas Lavastida

Motivated by the problem of market power in electricity markets, we introduced in previous works a mechanism for simplified markets of two agents with linear cost. In standard procurement auctions, the market power resulting from the…

Theoretical Economics · Economics 2019-07-25 Benjamin Heymann , Alejandro Jofré

Retailers have significant potential to improve recommendations through strategic bundling and pricing. By taking into account different types of customers and their purchasing decisions, retailers can better accommodate customer…

Optimization and Control · Mathematics 2024-09-06 Maxime Bouscary , Mazen Danaf , Saurabh Amin

The paper develops a decentralized resource allocation mechanism for allocating divisible goods with capacity constraints to non-price-taking agents with general concave utilities. The proposed mechanism is always budget balanced,…

Optimization and Control · Mathematics 2012-02-10 Ali Kakhbod

We study liquidity provision in the presence of exogenous competition. We consider a `reference market maker' who monitors her inventory and the aggregated inventory of the competing market makers. We assume that the competing market makers…

Mathematical Finance · Quantitative Finance 2024-07-25 Robert Boyce , Martin Herdegen , Leandro Sánchez-Betancourt

The autonomous systems need to decide how to react to the changes at runtime efficiently. The ability to rigorously analyze the environment and the system together is theoretically possible by the model-driven approaches; however, the model…

Software Engineering · Computer Science 2021-10-28 Melika Dastranj , Mehran Alidoost Nia , Mehdi Kargahi

Discounted algorithms often encounter evaluation errors due to their reliance on short-term estimations, which can impede their efficacy in addressing simple, short-term tasks and impose undesired temporal discounts (\(\gamma\)).…

Machine Learning · Computer Science 2024-09-02 Nitsan Soffair , Gilad Katz

Within decentralized organizations, the local demand for recommender systems to support business processes grows. The diversity in data sources and infrastructure challenges central engineering teams. Achieving a high delivery velocity…

Software Engineering · Computer Science 2021-09-21 Maurits van der Goes

We study the dynamic pricing problem faced by a monopolistic retailer who sells a storable product to forward-looking consumers. In this framework, the two major pricing policies (or mechanisms) studied in the literature are the…

Computer Science and Game Theory · Computer Science 2018-06-06 Gerardo Berbeglia , Gautam Rayaprolu , Adrian Vetta

This paper discusses the revenue management (RM) problem to maximize revenue by pricing items or services. One challenge in this problem is that the demand distribution is unknown and varies over time in real applications such as airline…

Machine Learning · Computer Science 2024-05-09 Kazuma Shimizu , Junya Honda , Shinji Ito , Shinji Nakadai

A novel high-frequency market-making approach in discrete time is proposed that admits closed-form solutions. By taking advantage of demand functions that are linear in the quoted bid and ask spreads with random coefficients, we model the…

Trading and Market Microstructure · Quantitative Finance 2024-05-21 Jonathan Chávez-Casillas , José E. Figueroa-López , Chuyi Yu , Yi Zhang