Paper Citation Record · LEDGER

Can Large Language Models Beat Wall Street? Unveiling the Potential of AI in Stock Selection

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2401.03737.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2401.03737 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:53:05.313051Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-23T01:12:20.618846Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation f166556c-626c-4afc-a3d6-a4d1a288d92f · inbound

Bridging Language Models and Financial Analysis cites this paper.

Bridging Language Models and Financial Analysis Can Large Language Models Beat Wall Street? Unveiling the Potential of AI in Stock Selection

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-23T01:12:20.622069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bfb309e2-c95f-48a1-9792-374b0d5e9ad9 · inbound

LLM-Powered AI Agent Systems and Their Applications in Industry cites this paper.

LLM-Powered AI Agent Systems and Their Applications in Industry Can Large Language Models Beat Wall Street? Unveiling the Potential of AI in Stock Selection

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-22T14:06:38.097862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ec595322-a751-4158-aec8-8d0f92ba5986 · inbound

Integrating Large Language Models in Financial Investments and Market Analysis: A Survey cites this paper.

Integrating Large Language Models in Financial Investments and Market Analysis: A Survey Can Large Language Models Beat Wall Street? Unveiling the Potential of AI in Stock Selection

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T21:53:05.313051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae7d5c1c-77d2-448c-8f20-f506bb39f811 · inbound

Predicting Business Angel Early-Stage Decision Making Using AI cites this paper.

Predicting Business Angel Early-Stage Decision Making Using AI Can Large Language Models Beat Wall Street? Unveiling the Potential of AI in Stock Selection

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-06T20:09:36.092897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 929682b6-841d-4c7a-b33e-4ff99a1dcfda · inbound

Agentar-Fin-R1: Enhancing Financial Intelligence through Domain Expertise, Training Efficiency, and Advanced Reasoning cites this paper.

Agentar-Fin-R1: Enhancing Financial Intelligence through Domain Expertise, Training Efficiency, and Advanced Reasoning Can Large Language Models Beat Wall Street? Unveiling the Potential of AI in Stock Selection

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T15:07:37.370817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a13eeb9e-7364-4ba8-bdca-8d2c084bf1ed · inbound

ContestTrade: A Multi-Agent Trading System Based on Internal Contest Mechanism cites this paper.

ContestTrade: A Multi-Agent Trading System Based on Internal Contest Mechanism Can Large Language Models Beat Wall Street? Unveiling the Potential of AI in Stock Selection

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T10:12:19.773924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.