RRepoGEO

REPOGEO REPORT · LITE

georgezouq/awesome-ai-in-finance

Default branch main · commit b646b26e · scanned 5/18/2026, 7:27:36 PM

GitHub: 5,938 stars · 686 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
27 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
1 / 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 georgezouq/awesome-ai-in-finance, 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 clearly state it's an awesome list of resources

    Why:

    CURRENT
    There are millions of trades made in the global financial market every day. Data grows very quickly and people are hard to understand. With the power of the latest artificial intelligence research, people analyze & trade automatically and intelligently. This list contains the research, tools and code that people use to beat the market.
    COPY-PASTE FIX
    This is a curated list of awesome resources for applying Artificial Intelligence, particularly Large Language Models (LLMs) and deep learning, to financial markets. It gathers cutting-edge research, practical tools, and code that empower intelligent analysis and automated trading strategies, helping to navigate the vast and complex financial data landscape.
  • mediumreadme#2
    Add a sentence to the README clarifying the target audience and scope

    Why:

    COPY-PASTE FIX
    This repository serves as a comprehensive guide for researchers, quantitative analysts, developers, and enthusiasts seeking to explore and implement advanced AI techniques in finance, from portfolio management to high-frequency trading.
  • lowtopics#3
    Add 'llm' and 'large-language-models' to the repository topics

    Why:

    CURRENT
    analysis, awesome, awesome-list, cryptocurrency, deep-learning, financial, neural-network, quant, quantitative-finance, reinforcement-learning, stock-market, technology-analysis
    COPY-PASTE FIX
    analysis, awesome, awesome-list, cryptocurrency, deep-learning, financial, llm, large-language-models, neural-network, quant, quantitative-finance, reinforcement-learning, stock-market, technology-analysis

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 georgezouq/awesome-ai-in-finance
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face Transformers
Recommended in 4 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Transformers · recommended 4×
  2. OpenAI API · recommended 4×
  3. Anthropic Claude · recommended 2×
  4. QuantConnect/Lean · recommended 1×
  5. quantopian/zipline · recommended 1×
  • CATEGORY QUERY
    What AI tools are available for developing quantitative trading strategies in finance?
    you: not recommended
    AI recommended (in order):
    1. QuantConnect (Lean Engine) (QuantConnect/Lean)
    2. Zipline (quantopian/zipline)
    3. Backtrader (mementum/backtrader)
    4. MetaTrader 5 (MQL5)
    5. Keras (keras-team/keras)
    6. TensorFlow (tensorflow/tensorflow)
    7. PyTorch (pytorch/pytorch)
    8. Scikit-learn (scikit-learn/scikit-learn)
    9. Optuna (optuna/optuna)

    AI recommended 9 alternatives but never named georgezouq/awesome-ai-in-finance. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can large language models be applied to financial market analysis and predictions?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. OpenAI API
    3. Google Cloud Natural Language API
    4. AssemblyAI
    5. Deepgram
    6. OpenAI API
    7. OpenAI API
    8. Anthropic Claude
    9. Hugging Face Transformers
    10. Elastic Stack
    11. Hugging Face Transformers
    12. Google Cloud Vertex AI
    13. Python
    14. NLTK
    15. spaCy
    16. scikit-learn
    17. Hugging Face Transformers
    18. Keras
    19. TensorFlow
    20. PyTorch
    21. OpenAI API
    22. Anthropic Claude
    23. Haystack

    AI recommended 23 alternatives but never named georgezouq/awesome-ai-in-finance. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 georgezouq/awesome-ai-in-finance?
    pass
    AI did not name georgezouq/awesome-ai-in-finance — 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 georgezouq/awesome-ai-in-finance in production, what risks or prerequisites should they evaluate first?
    pass
    AI named georgezouq/awesome-ai-in-finance 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 georgezouq/awesome-ai-in-finance solve, and who is the primary audience?
    pass
    AI did not name georgezouq/awesome-ai-in-finance — 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?

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite