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The Nasdaq Exchange Embraces AI: Market Manipulation Mitigation Built for the Future

· Nasdaq,Stock Market,Stock Trading,Trading

The Nasdaq Exchange Embraces AI: Market Manipulation Mitigation Built for the Future

Nasdaq Inc is home of the Nasdaq Stock Market, the world’s largest stock exchange by volume traded. The Nasdaq exchange operates autonomously; the exchange offers cost-efficient listing and trading processes, yet lacks important fraud safeguards without human traders’ oversight. Recognizing the need to promote ethical utilization of the exchange, Nasdaq is increasingly looking toward technological innovation to facilitate market security and efficacy.

The technology-facing exchange has recently implemented artificial intelligence (AI) based monitoring systems for market fraud and manipulation. The AI system leverages data-driven machine-learning technology to identify nefarious exchange manipulation. Nasdaq’s proprietary algorithm detects irregular trading patterns and protocols to alert exchange officials, who subsequently may investigate and remove fraudulent equity orders.

Nasdaq’s AI monitoring system leverages deep learning mechanisms, autonomous algorithm training processes, which distinguish illicit market manipulation from the billions of lawful trades supported by the Nasdaq exchange daily. Nasdaq officials affirm that the AI system positively identifies both irregular and illicit exchange activity, providing a potential future of autonomous volatility detection and correction. Nasdaq operates additional derivatives and fixed-income exchanges and clearing houses in addition to international equity and securities exchanges.

Nasdaq’s AI tool deployment represents a significant acceptance and adoption of financial machine-learning algorithms. Yet significant headwinds remain to widespread AI algorithm adoption by stock exchanges. While deep learning algorithms benefit from large scale training from billions of historical trade data points in the equity market, relatively illiquid markets lack similar data collection practices and data set size. Furthermore, the ethical challenge of autonomation disruption remains present: algorithmic security mechanisms may displace current human market manipulation divisions.

Despite these potential challenges to AI exchange surveillance implementation, Nasdaq’s investment in the space reveals the innovative nature of further financial AI development. Furthermore, Nasdaq officials emphasize that human analysts remain critical to the continued efficacy of market manipulation prevention. Thus, complementary AI systems can augment our ability to identify and attenuate equity market fraud; and if Nasdaq’s AI implementation is any indication, this may simply be the beginning of AI algorithms in financial system security.

Written by Aaron Rennert, Edited by James Mueller & Alexander Fleiss