Paper Citation Record · LEDGER

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500

As of 8 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2507.09739.

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

pith.paper-citation-record.v1
2507.09739 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:54:17.290286Z

measured 27 of 27 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

27 of 27 outbound references displayed

verified exact5
verified fuzzy8
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c8a96d12-b592-4669-b69a-18e3fd447dbe · outbound

This paper cites an unresolved cited work.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-06T17:54:18.557165Z

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 afa7e7cf-b3d0-4f20-8c27-558a3c3ee1f5 · outbound

This paper cites an unresolved cited work.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-06T17:54:18.536348Z

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 fede16cb-f595-462d-a0e6-66ec17481902 · outbound

This paper cites an unresolved cited work.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-06T17:54:18.515446Z

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 52875b06-3611-42e6-8586-54d9c22135f7 · outbound

This paper cites A comparative study of the MACD-base trading strategies: evidence from the US stock market.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 A comparative study of the MACD-base trading strategies: evidence from the US stock market

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T17:54:16.766316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4076a1ae-0cb3-42c6-b580-d6b3fe3fdae1 · outbound

This paper cites Financial sentiment analysis: Techniques and applications.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Financial sentiment analysis: Techniques and applications

Reference 5

Resolution: verified exact; doi, observed 2026-08-06T17:54:17.551121Z

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 3841a177-38bb-4b8d-9da8-fcf35e1bf043 · outbound

This paper cites Engelberg and C.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Engelberg and C

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.493577Z

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 5f7db60f-62c6-430a-9533-5682184e09a2 · outbound

This paper cites Using financial news sentiment for stock price direction prediction.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Using financial news sentiment for stock price direction prediction

Reference 7

Resolution: verified exact; doi, observed 2026-08-06T17:54:17.522599Z

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 039af28f-13ea-42e4-85c2-1373ece4555a · outbound

This paper cites Twitter sentiment and stock market movements: The predictive power of social media.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Twitter sentiment and stock market movements: The predictive power of social media

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.468047Z

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 f3c14d38-91bf-475f-887c-00e4a2bdf763 · outbound

This paper cites Informational role of social media: Evidence from twitter sentiment.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Informational role of social media: Evidence from twitter sentiment

Reference 9

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T17:54:17.989168Z

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 4ea69ead-28b7-4ad2-9a50-9aedb7a31588 · outbound

This paper cites Revised short screening version of the profile of mood states (poms-16): Validity and reliability.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Revised short screening version of the profile of mood states (poms-16): Validity and reliability

Reference 10

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T17:54:17.849896Z

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 fb22b146-9e5d-4719-8c81-67c46c7c0a1f · outbound

This paper cites News Sentiment as Leading Indicators for Recessions.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 News Sentiment as Leading Indicators for Recessions

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:54:17.725550Z

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 15bb4dc9-d75e-4155-9888-d2dea556c1cc · outbound

This paper cites Hyndman and George Athanasopoulos.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Hyndman and George Athanasopoulos

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.424543Z

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 0a07079c-d1ef-4549-af85-02ba9004bd42 · outbound

This paper cites an unresolved cited work.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-06T17:54:18.382094Z

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 1ef01622-512a-4585-9379-8ba34a742937 · outbound

This paper cites Sentiment trading with large language models.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Sentiment trading with large language models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T17:54:17.166917Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95281c94-91ea-4408-96e4-c20eb2832d4a · outbound

This paper cites Finvader: VADER sentiment classifier updated with financial lexicons.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Finvader: VADER sentiment classifier updated with financial lexicons

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.353096Z

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 4af2c818-c7ba-422c-94d3-ddeba2e92014 · outbound

This paper cites Loughran and B.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Loughran and B

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.316190Z

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 a5d5498c-aa51-4729-90a0-aa39e73bb11a · outbound

This paper cites Design and evaluation of SentiEcon : A fine-grained economic/financial sentiment lexicon from a corpus of business news.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Design and evaluation of SentiEcon : A fine-grained economic/financial sentiment lexicon from a corpus of business news

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.282463Z

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 71e2ab73-329d-4388-a2f2-a278f5d5b297 · outbound

This paper cites Language models are unsupervised multitask learners.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Language models are unsupervised multitask learners

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.245066Z

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 ba91a043-a6a5-4f70-810b-bfd85fdf1dd9 · outbound

This paper cites an unresolved cited work.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-06T17:54:18.200386Z

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 709a472a-e234-400e-a5ea-4a46c4069187 · outbound

This paper cites Shumway and David S.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Shumway and David S

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T17:54:17.225446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cdd42f3f-6389-42d5-9cad-26604bb2e2a4 · outbound

This paper cites Forecasting at scale.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Forecasting at scale

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T17:54:17.234220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccb2f5b0-21d0-4b84-a7c8-569461e6b054 · outbound

This paper cites an unresolved cited work.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-06T17:54:18.137114Z

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 17f16cd7-26da-482e-82a6-33a276803a35 · outbound

This paper cites Bitcoin price change and trend prediction through twitter sentiment and data volume.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Bitcoin price change and trend prediction through twitter sentiment and data volume

Reference 23

Resolution: verified exact; doi, observed 2026-08-06T17:54:17.437734Z

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 28908d94-4665-4aec-8c6c-43602e1a99b8 · outbound

This paper cites Wang and J.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Wang and J

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:54:18.105763Z

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 ffe5e739-d044-4b8e-a9e7-dd0897d7bb38 · outbound

This paper cites Efficient market hypothesis in contemporary applications: A systematic review on theoretical models, experimental validation, and practical application.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Efficient market hypothesis in contemporary applications: A systematic review on theoretical models, experimental validation, and practical application

Reference 25

Resolution: verified exact; doi, observed 2026-08-06T17:54:17.374654Z

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 3d68a238-94bd-44a0-9f63-df380ee48b9d · outbound

This paper cites an unresolved cited work.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 Unresolved cited work

Reference 26

Resolution: unresolved; raw_fallback, observed 2026-08-06T17:54:18.070216Z

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 6facb2b6-a10c-4ba7-a16c-50648d151a22 · outbound

This paper cites FinBERT: A Pretrained Language Model for Financial Communications.

Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500 FinBERT: A Pretrained Language Model for Financial Communications

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T17:54:17.290286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.