RRepoGEO

REPOGEO REPORT · LITE

QuantaAlpha/QuantaAlpha

Default branch main · commit be808736 · scanned 6/2/2026, 12:08:20 PM

GitHub: 1,014 stars · 215 forks

AI VISIBILITY SCORE
35 /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
3 / 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 QuantaAlpha/QuantaAlpha, 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
  • highlicense#1
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with your chosen open-source license (e.g., MIT, Apache-2.0, GPL-3.0). If unsure, consult legal advice or choose a permissive license like MIT.
  • highreadme#2
    Strengthen README's opening to emphasize LLM-driven quantitative finance factor discovery

    Why:

    CURRENT
    🧬 Achieving superior quantitative alpha through trajectory-based self-evolution with diversified planning initialization, trajectory-level evolution, and structured hypothesis-code constraint
    COPY-PASTE FIX
    QuantaAlpha is an innovative **LLM-driven framework for quantitative finance factor discovery**, transforming how quants and researchers identify superior alpha factors. It combines large language model intelligence with evolutionary strategies to automatically mine, evolve, and validate factors through self-evolving trajectories.
  • mediumtopics#3
    Expand repository topics to include specific quantitative finance and AI terms

    Why:

    CURRENT
    code, codeagent, factor-mining, quantaalpha, self-evolving
    COPY-PASTE FIX
    quantitative-finance, llm, artificial-intelligence, algorithmic-trading, factor-mining, evolutionary-algorithms, machine-learning-finance, alpha-factors, self-evolving, codeagent

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 QuantaAlpha/QuantaAlpha
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
quantopian/zipline
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. quantopian/zipline · recommended 2×
  2. QuantConnect/Lean · recommended 2×
  3. Bloomberg Terminal · recommended 1×
  4. Refinitiv Eikon / Workspace · recommended 1×
  5. FactSet · recommended 1×
  • CATEGORY QUERY
    How can I leverage large language models for discovering new quantitative alpha factors?
    you: not recommended
    AI recommended (in order):
    1. Bloomberg Terminal
    2. Refinitiv Eikon / Workspace
    3. FactSet
    4. Quandl (now Nasdaq Data Link)
    5. AlphaSense / S&P Global Market Intelligence
    6. OpenAI GPT-4 / GPT-3.5 Turbo
    7. Google Gemini (Pro / Ultra)
    8. Anthropic Claude 3 (Opus / Sonnet)
    9. Hugging Face Transformers (huggingface/transformers)
    10. Llama 3
    11. Mixtral
    12. Python
    13. Pandas (pandas-dev/pandas)
    14. NumPy (numpy/numpy)
    15. SciPy (scipy/scipy)
    16. Zipline (quantopian/zipline)
    17. QuantConnect (Lean Engine) (QuantConnect/Lean)
    18. Alpaca API
    19. Quantopian
    20. LangChain (langchain-ai/langchain)
    21. LlamaIndex (run-llama/llama_index)
    22. Pinecone
    23. Weaviate (weaviate/weaviate)
    24. Milvus (milvus-io/milvus)
    25. AWS SageMaker
    26. Google Cloud AI Platform
    27. Azure Machine Learning

    AI recommended 27 alternatives but never named QuantaAlpha/QuantaAlpha. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What frameworks help evolve and validate financial trading strategies using AI and self-learning?
    you: not recommended
    AI recommended (in order):
    1. QuantConnect (Lean Engine) (QuantConnect/Lean)
    2. Zipline (quantopian/zipline)
    3. Backtrader (mementum/backtrader)
    4. PyAlgoTrade (gbeced/pyalgotrade)
    5. Catalyst (by Enigma) (enigmampc/catalyst)
    6. TensorFlow/PyTorch
    7. OpenBB Terminal (OpenBB-finance/OpenBBTerminal)

    AI recommended 7 alternatives but never named QuantaAlpha/QuantaAlpha. 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 QuantaAlpha/QuantaAlpha?
    pass
    AI named QuantaAlpha/QuantaAlpha explicitly

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

  • If a team adopts QuantaAlpha/QuantaAlpha in production, what risks or prerequisites should they evaluate first?
    pass
    AI named QuantaAlpha/QuantaAlpha 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 QuantaAlpha/QuantaAlpha solve, and who is the primary audience?
    pass
    AI named QuantaAlpha/QuantaAlpha explicitly

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

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