RRepoGEO

REPOGEO REPORT · LITE

wassname/rl-portfolio-management

Default branch master · commit e73339ff · scanned 6/4/2026, 10:03:14 AM

GitHub: 562 stars · 179 forks

AI VISIBILITY SCORE
28 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface wassname/rl-portfolio-management, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the README's opening paragraph to clarify current value

    Why:

    CURRENT
    Attempting to replicate "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem" by Jiang et. al. 2017 [1].
    
    **Note2 (20190525):** vermouth1992 improved this environment during their final project, I reccomend you start with their repo. Also check out the sagemaker tutorial which is based on vermouth1992's work.
    
    Note1 (2018): the paper's authors have put the official code for the paper up and it works well
    
    tl;dr I managed to get 8% growth on training data, but it disapeared on test data. So I couldn't replicate it. However, RL papers can be very difficult to replicate due to bugs, framework differences, and hyperparameter sensistivity
    COPY-PASTE FIX
    This repository offers a robust OpenAI Gym environment for financial portfolio management, serving as a valuable foundation for deep reinforcement learning research in finance. While originally part of an attempt to replicate the Jiang et al. 2017 paper, and acknowledging the replication challenges, the environment itself is well-tested and useful for new experiments or understanding replication complexities. For successful replications or production-ready solutions, please refer to vermouth1992's repository or the official paper code.
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://arxiv.org/abs/1706.10059
  • lowtopics#3
    Refine repository topics to reflect its specific value

    Why:

    CURRENT
    cryptocurrency, deep-reinforcement-learning, deeprl, openai-gym, openai-gym-environments, portfolio-management
    COPY-PASTE FIX
    cryptocurrency, deep-reinforcement-learning, deeprl, openai-gym, openai-gym-environments, portfolio-management, rl-replication-study, financial-gym-environment, learning-resource

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface wassname/rl-portfolio-management
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
FinRL
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. FinRL · recommended 2×
  2. Stable Baselines3 · recommended 1×
  3. Gymnasium · recommended 1×
  4. Ray RLlib · recommended 1×
  5. TensorFlow Agents · recommended 1×
  • CATEGORY QUERY
    How can I apply deep reinforcement learning to optimize a financial portfolio?
    you: not recommended
    AI recommended (in order):
    1. Stable Baselines3
    2. Gymnasium
    3. Ray RLlib
    4. FinRL
    5. TensorFlow Agents
    6. PyTorch
    7. Keras-RL2

    AI recommended 7 alternatives but never named wassname/rl-portfolio-management. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for an OpenAI Gym environment to simulate cryptocurrency portfolio trading.
    you: not recommended
    AI recommended (in order):
    1. Gym-TradingEnv
    2. FinRL
    3. OpenAI Gym
    4. QuantConnect
    5. Backtrader

    AI recommended 5 alternatives but never named wassname/rl-portfolio-management. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of wassname/rl-portfolio-management?
    pass
    AI did not name wassname/rl-portfolio-management — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts wassname/rl-portfolio-management in production, what risks or prerequisites should they evaluate first?
    pass
    AI named wassname/rl-portfolio-management explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo wassname/rl-portfolio-management solve, and who is the primary audience?
    pass
    AI named wassname/rl-portfolio-management explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of wassname/rl-portfolio-management. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/wassname/rl-portfolio-management.svg)](https://repogeo.com/en/r/wassname/rl-portfolio-management)
HTML
<a href="https://repogeo.com/en/r/wassname/rl-portfolio-management"><img src="https://repogeo.com/badge/wassname/rl-portfolio-management.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

wassname/rl-portfolio-management — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite