Paper Citation Record · LEDGER

End-to-End Parametric Portfolio Policies for Cross-Asset Futures Timing: When Do AI Models Beat Simple Rules?

As of 18 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2607.00475.

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

pith.paper-citation-record.v1
2607.00475 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-02T02:12:42.753066Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

17 of 17 outbound references displayed

verified exact2
verified fuzzy14
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ade1a289-e01d-49ca-87c5-84d9dbfce1b2 · outbound

This paper cites Deep reinforce- ment learning for trading,.

End-to-End Parametric Portfolio Policies for Cross-Asset Futures Timing: When Do AI Models Beat Simple Rules? Deep reinforce- ment learning for trading,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T09:12:10.685977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d0b72aae-0b0e-4652-b640-f5c9a40be038 · outbound

This paper cites Enhancing time series momentum strategies using deep neural networks,.

End-to-End Parametric Portfolio Policies for Cross-Asset Futures Timing: When Do AI Models Beat Simple Rules? Enhancing time series momentum strategies using deep neural networks,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T09:12:10.684184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 284d8763-d22e-41a8-b66a-b91c199a5923 · outbound

This paper cites Deep learning for portfolio optimization,.

End-to-End Parametric Portfolio Policies for Cross-Asset Futures Timing: When Do AI Models Beat Simple Rules? Deep learning for portfolio optimization,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T09:12:10.687758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cec94ac5-d1ca-442a-8a45-d749c085c7a1 · outbound

This paper cites Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture.

End-to-End Parametric Portfolio Policies for Cross-Asset Futures Timing: When Do AI Models Beat Simple Rules? Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-02T02:16:25.700402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3d7b6b37-84f2-4720-bb6b-fcde7f945bcd · outbound

This paper cites Para- metric portfolio policies: Exploiting characteristics in the cross-section of equity returns,.

End-to-End Parametric Portfolio Policies for Cross-Asset Futures Timing: When Do AI Models Beat Simple Rules? Para- metric portfolio policies: Exploiting characteristics in the cross-section of equity returns,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T09:12:10.689712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a4af9726-4fa6-49a5-9a91-35663b7f746f · outbound

This paper cites Optimal versus naive diversification: How inefficient is the1/Nportfolio strategy?.

End-to-End Parametric Portfolio Policies for Cross-Asset Futures Timing: When Do AI Models Beat Simple Rules? Optimal versus naive diversification: How inefficient is the1/Nportfolio strategy?

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T09:12:10.704129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 71ecc5c7-5f72-41e2-b863-2a3a5027c9c5 · outbound

This paper cites A Universal End-to-End Approach to Portfolio Optimization via Deep Learning.

End-to-End Parametric Portfolio Policies for Cross-Asset Futures Timing: When Do AI Models Beat Simple Rules? A Universal End-to-End Approach to Portfolio Optimization via Deep Learning

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-07-02T02:16:25.696341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f446f3ee-a5cc-494c-8e0a-9e90ce71fc1c · outbound

This paper cites an unresolved cited work.

End-to-End Parametric Portfolio Policies for Cross-Asset Futures Timing: When Do AI Models Beat Simple Rules? Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-07-06T09:12:10.702374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d05f6d38-1fc2-4e98-87e8-16251b89da48 · outbound

This paper cites Portfolio transformer for attention-based asset allocation,.

End-to-End Parametric Portfolio Policies for Cross-Asset Futures Timing: When Do AI Models Beat Simple Rules? Portfolio transformer for attention-based asset allocation,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T09:12:10.695228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4f35c54b-a0ad-429d-9f9d-cf13f0468601 · outbound

This paper cites Deep parametric portfolio policies,.

End-to-End Parametric Portfolio Policies for Cross-Asset Futures Timing: When Do AI Models Beat Simple Rules? Deep parametric portfolio policies,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T09:12:10.696914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6333e8e2-1490-4b59-b892-ef0b116e72d7 · outbound

This paper cites Machine learning and the implementable efficient frontier,.

End-to-End Parametric Portfolio Policies for Cross-Asset Futures Timing: When Do AI Models Beat Simple Rules? Machine learning and the implementable efficient frontier,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T09:12:10.693476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ebbb1dc2-3389-4ccc-87c6-b1e5feed9ff7 · outbound

This paper cites Portfolio selection,.

End-to-End Parametric Portfolio Policies for Cross-Asset Futures Timing: When Do AI Models Beat Simple Rules? Portfolio selection,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T09:12:10.691661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b6d74cef-ad50-4bd4-ab35-83a3a601077d · outbound

This paper cites Efficient capital markets: A review of theory and empirical work,.

End-to-End Parametric Portfolio Policies for Cross-Asset Futures Timing: When Do AI Models Beat Simple Rules? Efficient capital markets: A review of theory and empirical work,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T09:12:10.677448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a58db342-3f9e-4bbc-ac88-8365d314769a · outbound

This paper cites Reinforcement learning for trading,.

End-to-End Parametric Portfolio Policies for Cross-Asset Futures Timing: When Do AI Models Beat Simple Rules? Reinforcement learning for trading,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T09:12:10.700553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0c5e3b36-1dde-490c-9b87-ebd8d76f7872 · outbound

This paper cites Smart ‘predict, then optimize’,.

End-to-End Parametric Portfolio Policies for Cross-Asset Futures Timing: When Do AI Models Beat Simple Rules? Smart ‘predict, then optimize’,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T09:12:10.680080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 57568230-03ef-42ed-95ac-224d352cc302 · outbound

This paper cites Task-based end- to-end model learning in stochastic optimization,.

End-to-End Parametric Portfolio Policies for Cross-Asset Futures Timing: When Do AI Models Beat Simple Rules? Task-based end- to-end model learning in stochastic optimization,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T09:12:10.698678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b9259acc-6364-4ec5-9d9f-48e6301bd1bd · outbound

This paper cites From predictive to prescrip- tive analytics,.

End-to-End Parametric Portfolio Policies for Cross-Asset Futures Timing: When Do AI Models Beat Simple Rules? From predictive to prescrip- tive analytics,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T09:12:10.688972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

No inbound Pith citation observations are available.