Balanced Trade Reduction for Dual-Role Exchange Markets

Authors: Dengji Zhao, Sarvapali Ramchurn, Enrico Gerding, Nicholas Jennings

AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical We consider dual-role exchange markets, where traders can offer to both buy and sell the same commodity in the exchange but, if they transact, they can only be either a buyer or a seller, which is determined by the market mechanism. To design desirable mechanisms for such exchanges, we show that existing solutions may not be incentive compatible, and more importantly, cause the market maker to suffer a significant deficit. Hence, to combat this problem, following Mc Afee s trade reduction approach, we propose a new trade reduction mechanism, called balanced trade reduction, that is incentive compatible and also provides flexible trade-offs between efficiency and deficit.
Researcher Affiliation Academia Dengji Zhao, Sarvapali D. Ramchurn, Enrico H. Gerding and Nicholas R. Jennings Electronics and Computer Science University of Southampton Southampton, SO17 1BJ, UK
Pseudocode Yes Mc Afee s trade reduction MMc Afee; Balanced payment setting x(vb,vs); Balanced trade reduction Mbtr; k-balanced trade reduction Mbtr,k
Open Source Code No The paper does not provide concrete access to source code for the methodology described.
Open Datasets No The paper is theoretical and does not involve training on a dataset, therefore no dataset access information is provided.
Dataset Splits No The paper is theoretical and does not involve experimental validation, therefore no dataset split information for validation is provided.
Hardware Specification No The paper is theoretical and does not describe any experiments that would require specific hardware, therefore no hardware specifications are provided.
Software Dependencies No The paper is theoretical and does not describe experiments that would require specific software dependencies with version numbers.
Experiment Setup No The paper is theoretical and does not describe any experimental setup details such as hyperparameters or training configurations.