Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:30:19.339196Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2506.06356.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:30:19.339196Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
21 of 21 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 3e1a107d-56e3-475a-9aea-2bcc99a572dc · outbound
Deep Learning Enhanced Multi-Day Turnover Quantitative Trading Algorithm for Chinese A-Share Market Common risk factors in the ret urns on stocks and bonds,
Reference 1
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 cd784ea5-b83d-4cbf-85e3-1cb317f508c4 · outbound
Deep Learning Enhanced Multi-Day Turnover Quantitative Trading Algorithm for Chinese A-Share Market On persistence in mutual fund performanc e,
Reference 2
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 f86c7a16-9d75-4287-a4c1-ea7693354eec · outbound
Deep Learning Enhanced Multi-Day Turnover Quantitative Trading Algorithm for Chinese A-Share Market Consumer credit-r isk models via machine-learning algorithms,
Reference 3
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 479ff026-0ddc-4782-b822-4da963f4209d · outbound
Deep Learning Enhanced Multi-Day Turnover Quantitative Trading Algorithm for Chinese A-Share Market Deep learning with long short- term memory networks for financial market predictions,
Reference 4
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 feef5607-eee0-41a3-9fc0-00a9bbe971e5 · outbound
Deep Learning Enhanced Multi-Day Turnover Quantitative Trading Algorithm for Chinese A-Share Market Financia l time series forecasting with deep learning: A systematic litera ture review: 2005–2019,
Reference 5
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 fb9001dd-f427-4e7f-bd13-90ac83a0b48d · outbound
Deep Learning Enhanced Multi-Day Turnover Quantitative Trading Algorithm for Chinese A-Share Market Informer: Beyond efficient transformer f or long se- quence time-series forecasting,
Reference 6
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 95f44e2e-4cec-4c93-99c2-50b11c55b292 · outbound
Deep Learning Enhanced Multi-Day Turnover Quantitative Trading Algorithm for Chinese A-Share Market and the cross-sectio n of expected returns,
Reference 7
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 b1e1f1c9-8c69-440b-b6ab-e5e4d4900798 · outbound
Deep Learning Enhanced Multi-Day Turnover Quantitative Trading Algorithm for Chinese A-Share Market The real value of China’s stock market,
Reference 8
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 2cd56270-5581-4403-bf16-3f411daa814a · outbound
Deep Learning Enhanced Multi-Day Turnover Quantitative Trading Algorithm for Chinese A-Share Market Machine learning f or stock selection and portfolio optimization in Chinese A-sh are market,
Reference 9
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 be94a1fe-ecd5-4581-92ed-0f241d45bd0d · outbound
Deep Learning Enhanced Multi-Day Turnover Quantitative Trading Algorithm for Chinese A-Share Market Dynamic conditional correlation: A simpl e class of multivariate generalized autoregressive conditional het eroskedasticity models,
Reference 10
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 ae309848-0a59-4a20-89e6-20e837925540 · outbound
Deep Learning Enhanced Multi-Day Turnover Quantitative Trading Algorithm for Chinese A-Share Market Financial time se ries prediction using hybrids of chaos theory, multi-layer perceptron and m ulti-objective evolutionary algorithms,
Reference 11
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 755e93c6-fdfe-4d0a-adce-4dbe34c0d308 · outbound
Deep Learning Enhanced Multi-Day Turnover Quantitative Trading Algorithm for Chinese A-Share Market A new interpretation of information rat e,
Reference 12
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 c0f24e43-3adb-4b39-a4ad-199fbbb72691 · outbound
Deep Learning Enhanced Multi-Day Turnover Quantitative Trading Algorithm for Chinese A-Share Market The Kelly criterion in blackjack sports be tting, and the stock market,
Reference 13
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 a4fbda0a-99fc-4de6-9b2a-cbb09a3c145b · outbound
Deep Learning Enhanced Multi-Day Turnover Quantitative Trading Algorithm for Chinese A-Share Market Optimal execution of portfol io transactions,
Reference 14
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 ca8a53be-40cc-4ad0-b12a-130e8cddf89a · outbound
Deep Learning Enhanced Multi-Day Turnover Quantitative Trading Algorithm for Chinese A-Share Market Cartea, S
Reference 15
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 02d198cd-ff95-4370-b9fa-ec02c5f7b1ca · outbound
Deep Learning Enhanced Multi-Day Turnover Quantitative Trading Algorithm for Chinese A-Share Market A refinement to the Sharpe ratio and inf ormation ratio,
Reference 16
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 8b19a040-41c1-44b4-ab35-e80c2a3c71c3 · outbound
Deep Learning Enhanced Multi-Day Turnover Quantitative Trading Algorithm for Chinese A-Share Market Risks and portfolio decision s involving hedge funds,
Reference 17
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 ee2d152c-a583-432b-82c7-9bdbddc6e67c · outbound
Deep Learning Enhanced Multi-Day Turnover Quantitative Trading Algorithm for Chinese A-Share Market Big data and AI s trategies: Machine learning and alternative data approach to investin g,
Reference 18
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 18dcfdd9-2678-47fe-9959-fe99614c54b1 · outbound
Deep Learning Enhanced Multi-Day Turnover Quantitative Trading Algorithm for Chinese A-Share Market Twitter mood predicts th e stock market,
Reference 19
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 6070c3c5-65aa-405a-b39e-73569bf748a1 · outbound
Deep Learning Enhanced Multi-Day Turnover Quantitative Trading Algorithm for Chinese A-Share Market Forecastin g the equity risk premium: the role of technical indicators,
Reference 20
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 1fc3b37e-3447-4a0a-8a46-b372f4c1bb18 · outbound
Deep Learning Enhanced Multi-Day Turnover Quantitative Trading Algorithm for Chinese A-Share Market Empirical asset pricing via machine learning,
Reference 21
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.
No inbound Pith citation observations are available.