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AI in Finance: Progress Limited for Consistent Profitability

By PulseAugur Editorial · [1 sources] ·

A new research paper reviews the current state of artificial intelligence in equity and crypto markets, examining its progress from data analysis to automated investing. While AI has shown advancements in prediction, text processing, and portfolio design, the evidence for consistent profitability is limited. Challenges such as temporal contamination, implementation costs, and market mechanics hinder the translation of AI capabilities into net alpha, particularly in the complex crypto landscape. The paper concludes that no general AI architecture has yet demonstrated persistent, cross-regime, capacity-aware net alpha in public markets. AI

IMPACT Examines the practical limitations of current AI in generating consistent profits in financial markets.

RANK_REASON The item is a research paper published on arXiv discussing AI applications in financial markets. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI in Finance: Progress Limited for Consistent Profitability

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41 / 100
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The item is a research paper published on arXiv discussing AI applications in financial markets. [lever_c_demoted from research: ic=1 ai=1.0]
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Linsen Zhu, Mengqing Cai ·

    Artificial Intelligence in Equity and Crypto Markets: Progress, Profitability Evidence, and the Limits of Automated Investing

    arXiv:2609.04917v1 Announce Type: new Abstract: Artificial intelligence (AI) now supports investment workflows from data and prediction through research, portfolios, execution, and tool use. Technical capability, however, is not evidence of investment profitability. This critical…

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