Paper Citation Record · LEDGER

Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach

As of 17 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2505.03760.

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

pith.paper-citation-record.v1
2505.03760 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:48:12.750838Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

20 of 20 outbound references displayed

verified exact0
verified fuzzy11
unresolved8
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b8237938-98d3-4103-bf46-c8c1c50e5778 · outbound

This paper cites Continuous control with stacked deep dynamic recurrent reinforcement learning for portfolio optimization.

Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach Continuous control with stacked deep dynamic recurrent reinforcement learning for portfolio optimization

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:48:12.971365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 177ca98b-7018-4533-9cba-200b008bbc8f · outbound

This paper cites Recurrent ensemble random vector functional link neural network for financial time series forecasting.

Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach Recurrent ensemble random vector functional link neural network for financial time series forecasting

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:48:12.959865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 72ceb123-8181-4563-8070-39dde056ade3 · outbound

This paper cites Generalized autoregressive conditional heteroskedasticity.

Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach Generalized autoregressive conditional heteroskedasticity

Reference 3

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Source-reported events for the cited work

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Observation 6e0b278f-9b3f-47de-9a0e-4987003723f4 · outbound

This paper cites Multi-period portfolio optimization using a deep reinforcement learning hyper-heuristic approach.

Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach Multi-period portfolio optimization using a deep reinforcement learning hyper-heuristic approach

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:48:12.942119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 71ed08bf-70c0-421b-a1a2-82a6ebf0fa73 · outbound

This paper cites Deep reinforcement learning for stock portfolio optimization by connecting with modern portfolio theory.

Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach Deep reinforcement learning for stock portfolio optimization by connecting with modern portfolio theory

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:48:12.930624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d1345d86-5ec4-4c40-b2dc-17736002fabc · outbound

This paper cites A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem.

Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T11:48:12.698344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d3d8d8c-bac0-45d6-9cfd-66d03c906a4c · outbound

This paper cites FinRL: A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance.

Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach FinRL: A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T11:48:12.702583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 21777317-0746-4a8f-a7a7-fa6f807d7501 · outbound

This paper cites Foundations of portfolio theory.

Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach Foundations of portfolio theory

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:48:12.919181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3ee23d12-1380-4517-92d9-c5efbaec80a5 · outbound

This paper cites Performance functions and reinforcement learning for trading systems and portfolios.

Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach Performance functions and reinforcement learning for trading systems and portfolios

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:48:12.908271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 85e4b85d-4461-44ac-9dad-75678189be0c · outbound

This paper cites Dynamic reinforced ensemble using bayesian optimization for stock trading.

Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach Dynamic reinforced ensemble using bayesian optimization for stock trading

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:48:12.897357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f98a0b32-8362-4244-b51a-63da73e9b78b · outbound

This paper cites Forecasting volatility in the financial markets.

Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach Forecasting volatility in the financial markets

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:48:12.886148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 90c13752-7802-4846-a466-9baeb88e251f · outbound

This paper cites Proximal Policy Optimization Algorithms.

Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach Proximal Policy Optimization Algorithms

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T11:48:12.720335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3301f440-2ed3-4ff1-8cd8-02173d113d12 · outbound

This paper cites Reinforcement learning: An introduction.

Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach Reinforcement learning: An introduction

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T11:48:12.724179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20f4bbdd-d803-45c5-9ef9-f03363dab92d · outbound

This paper cites Portfolio formation with preselection using deep learning from long-term financial data.

Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach Portfolio formation with preselection using deep learning from long-term financial data

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:48:12.867185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f68b0c37-1184-48d7-a429-93a16d0d64cd · outbound

This paper cites Deeptrader: a deep reinforcement learning approach for risk-return balanced portfolio management with market conditions embedding.

Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach Deeptrader: a deep reinforcement learning approach for risk-return balanced portfolio management with market conditions embedding

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:48:12.855715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 48d43671-2c2b-4c7f-bc78-a8d67f605742 · outbound

This paper cites A multiobjective multiperiod portfolio selection approach with different investor attitudes under an uncertain environment.

Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach A multiobjective multiperiod portfolio selection approach with different investor attitudes under an uncertain environment

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:48:12.844449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0eb23869-e125-4266-94e0-31c3e035b4f5 · outbound

This paper cites write newline.

Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach write newline

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-16T11:48:12.738371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a10b1f11-7457-4387-a095-acfa6e35bdbb · outbound

This paper cites @esa (Ref.

Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach @esa (Ref

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-16T11:48:12.742829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1683c76e-5bdd-4320-8c13-60e01e0c907a · outbound

This paper cites an unresolved cited work.

Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach Unresolved cited work

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T11:48:12.746597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a42650bc-78aa-44a6-b525-806a60382f07 · outbound

This paper cites The dynamic and stochastic nature of the financial markets offers the flexibility to model it as a Markov Decision Process (MDP).

Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach The dynamic and stochastic nature of the financial markets offers the flexibility to model it as a Markov Decision Process (MDP)

Reference 20

Resolution: malformed identifier; raw_fallback, observed 2026-08-16T11:48:12.813990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

No inbound Pith citation observations are available.