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Niuniu Zhang

Niuniu Zhang is a PhD student in Decisions, Operations, and Technology Management at the UCLA Anderson School of Management. His research examines the strategic behavior of economic agents in digital platforms, spanning topics such as generative AI’s impact on the gig economy, algorithmic collusion, social preferences in large language models, and blockchain. Before joining UCLA, he was a research assistant at the University of Pennsylvania’s Crypto and Society Lab.
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Preventing Algorithmic Collusion by Adding Noise to Market Data

Niuniu Zhang
In new research, Niuniu Zhang discusses how regulators can add “noise” to market data to preclude tacit collusion through algorithmic pricing software without hampering legitimate market practices.

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The publication of the Stigler Center at The University of Chicago Booth School of Business

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