Paper Citation Record · LEDGER

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images

As of 16 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2501.12239.

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

pith.paper-citation-record.v1
2501.12239 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:23:48.306957Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

24 of 24 outbound references displayed

verified exact6
verified fuzzy8
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 717f112f-7347-450c-9a23-371ff986c5ad · outbound

This paper cites We selected stocks(AAPL), exchange(EUR_USD), and crypto(Bitcoin) as our trading instruments of interest to get data for our train model and perform p redictions.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images We selected stocks(AAPL), exchange(EUR_USD), and crypto(Bitcoin) as our trading instruments of interest to get data for our train model and perform p redictions

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:23:49.012748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 96eb4c70-d791-4cb9-91e2-28f28b30425d · outbound

This paper cites These patterns are then labeled as either strong or weak, providing a vital ground truth for the model's learning process.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images These patterns are then labeled as either strong or weak, providing a vital ground truth for the model's learning process

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:23:48.999773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d5dc0ce3-5e04-48bd-af08-86f7759548a5 · outbound

This paper cites Real-Time Flying Object Detection with YOLOv8.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images Real-Time Flying Object Detection with YOLOv8

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T17:23:48.232656Z

Source-reported events for the cited work

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Observation 2821b41b-a630-414a-8eca-890f3ce213a8 · outbound

This paper cites an unresolved cited work.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-10T17:23:49.025256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9cedf973-9048-48bc-b287-a91f44d121e7 · outbound

This paper cites Deep Candlestick Predictor,.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images Deep Candlestick Predictor,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:23:48.985195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7cc165c8-5a7c-4056-892f-1e50b96706cd · outbound

This paper cites Non-Pattern.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images Non-Pattern

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:23:48.972584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e1ab6411-dc90-45b5-a715-85c372d8bf1d · outbound

This paper cites An Introduction to Convolutional Neural Networks.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images An Introduction to Convolutional Neural Networks

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T17:23:48.223116Z

Source-reported events for the cited work

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Observation a58fe6a6-2a1d-4622-9d59-75c855608fde · outbound

This paper cites Deep Feature Fusion via Two -Stream Convolutional Neural Network for Hyperspectral Image Classification,.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images Deep Feature Fusion via Two -Stream Convolutional Neural Network for Hyperspectral Image Classification,

Reference 8

Resolution: metadata mismatch; raw_fallback, observed 2026-08-10T17:23:48.906754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c4ea32c0-cb34-44f7-ab7b-61812ddafc03 · outbound

This paper cites Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T17:23:48.238050Z

Source-reported events for the cited work

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Observation b682990f-d33e-400e-9810-e1cabe4a3a4f · outbound

This paper cites Dynamic Deep Convolutional Candlestick Learner.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images Dynamic Deep Convolutional Candlestick Learner

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-10T17:23:48.441309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 341b6f87-824a-4e06-a12f-66ec74a56cd9 · outbound

This paper cites Deep Candlestick Predictor: A Framework toward Forecasting the Price Movement from Candlestick Charts,.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images Deep Candlestick Predictor: A Framework toward Forecasting the Price Movement from Candlestick Charts,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T17:23:48.252882Z

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Observation 39f3ef19-5374-4c1a-a35c-e6c0d71704c6 · outbound

This paper cites DPP: Deep predictor for price movement from candlestick charts,.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images DPP: Deep predictor for price movement from candlestick charts,

Reference 13

Resolution: verified exact; doi, observed 2026-08-10T17:23:48.421333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9b4c938d-8190-4678-a4c0-13c265e811c0 · outbound

This paper cites Predicting the price movement from candlestick charts: a CNN -based approach,.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images Predicting the price movement from candlestick charts: a CNN -based approach,

Reference 14

Resolution: metadata mismatch; raw_fallback, observed 2026-08-10T17:23:48.729450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b8c3e7b6-15da-4f5d-883c-d2502c5f6eec · outbound

This paper cites Predicting Short Trend of Stocks by Using Convolutional Neural Network and Candlestick Patterns,.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images Predicting Short Trend of Stocks by Using Convolutional Neural Network and Candlestick Patterns,

Reference 15

Resolution: metadata mismatch; raw_fallback, observed 2026-08-10T17:23:48.649644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1dcdb4f3-8805-4ca7-bbac-3d73e535769d · outbound

This paper cites Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data,.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data,

Reference 16

Resolution: verified exact; doi, observed 2026-08-10T17:23:48.407628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation bef03d20-cfc1-4337-a15b-06ffa7dbd396 · outbound

This paper cites Using Deep Learning Neural Networks and Candlestick Chart Representation to Predict Stock Market (Feb.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images Using Deep Learning Neural Networks and Candlestick Chart Representation to Predict Stock Market (Feb

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:23:48.958560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 94d8d02f-2a15-4ece-bb05-4ee11fdda124 · outbound

This paper cites Deep Learning for Price Movement Prediction Using Convolutional Neural Network and Long Short -Term Memory,.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images Deep Learning for Price Movement Prediction Using Convolutional Neural Network and Long Short -Term Memory,

Reference 18

Resolution: verified exact; doi, observed 2026-08-10T17:23:48.350071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c6601424-22b3-46c6-8c13-8e82580a99e3 · outbound

This paper cites Stock Price Movement Prediction from Financial News with Deep Learning and Knowledge Graph Embedding,.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images Stock Price Movement Prediction from Financial News with Deep Learning and Knowledge Graph Embedding,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:23:48.945674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation dbb4dde7-2a50-4768-8d53-a968e7484dce · outbound

This paper cites Stock Price Prediction Using CNN and LSTM - Based Deep Learning Models,.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images Stock Price Prediction Using CNN and LSTM - Based Deep Learning Models,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:23:48.932726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 677fff49-25d4-4572-8704-f84571c23c50 · outbound

This paper cites A Stock Price Prediction Model Based on Investor Sentiment and Optimized Deep Learning,.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images A Stock Price Prediction Model Based on Investor Sentiment and Optimized Deep Learning,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T17:23:48.292490Z

Source-reported events for the cited work

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Observation 5edd0c61-cd57-428c-bef6-f6936b774048 · outbound

This paper cites Stock Chart Pattern recognition with Deep Learning.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images Stock Chart Pattern recognition with Deep Learning

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-10T17:23:48.381579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1ed5baac-d0b8-424e-a6e7-c2ac79894a3f · outbound

This paper cites A Stock Closing Price Prediction Model Based on CNN -BiSLSTM,.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images A Stock Closing Price Prediction Model Based on CNN -BiSLSTM,

Reference 23

Resolution: verified exact; doi, observed 2026-08-10T17:23:48.363831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 64a4d894-93b8-4ae3-a2bf-3dc5718c2989 · outbound

This paper cites Please ensure that all template text is removed from your conference paper prior to submission to the conference.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images Please ensure that all template text is removed from your conference paper prior to submission to the conference

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:23:48.919224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 56376c62-6501-4194-a186-ee3b2a19c9d7 · outbound

This paper cites Using Deep Learning Neural Networks and Candlestick Chart Representation to Predict Stock Market.

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images Using Deep Learning Neural Networks and Candlestick Chart Representation to Predict Stock Market

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-10T17:23:48.279940Z

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Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.