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Research Books — AI & Finance

Governance-first · long-form · release-versioned · human-accountable

This repository hosts long-form research books, technical monographs, and curated collections of papers by Alejandro Reynoso on artificial intelligence, finance, quantitative reasoning, infrastructure, algorithmic trading, and adjacent institutional applications.

These works are written under a disciplined model of human–AI collaboration. AI tools may assist with drafting, editing, coding, formatting, or structural iteration, but all works remain under human direction, review, and final responsibility.

Repository purpose:

  • distribute stable, camera-ready PDF editions
  • maintain versioned releases for citation and archival use
  • document revisions through release notes
  • provide a transparent record of human-supervised AI collaboration

Camera-ready PDFs are distributed through GitHub Releases.
Optional archival mirrors such as Zenodo may be used later to mint DOIs for citation.


Table of Contents


What this repository contains

This repository is the release home for research-oriented books at the intersection of:

  • artificial intelligence
  • financial practice
  • quantitative and structural reasoning
  • quantum-inspired methods
  • multi-agent systems
  • institutional governance
  • algorithmic trading systems
  • AI infrastructure and deployment economics

The books vary in scope and style. Some are single-subject monographs. Others are collected essays or tightly connected paper bundles organized as short books.

Across all of them, the common principle is the same:

capability must remain subordinate to accountability

That means these books are not positioned as autonomous machine outputs. They are curated, reviewed, and finalized under human supervision, with AI used as a tool inside a controlled intellectual workflow.


Catalog

Each entry links to its stable PDF and corresponding GitHub Release tag.


Authorship and Human–AI Collaboration

These books may incorporate AI tools for tasks such as:

  • drafting
  • editing
  • restructuring
  • code generation
  • formatting
  • language polishing

However:

  • final responsibility for the ideas, arguments, claims, mathematics, code logic, and empirical interpretations remains with the human author
  • AI is treated as a tool within a supervised workflow, not as an autonomous author
  • where appropriate, AI assistance may be acknowledged in prefaces, notes, or supporting repository material

This repository should therefore be understood as a record of disciplined human-led research and writing, sometimes accelerated by AI, never delegated to it.


How to cite

Please cite the specific book and version you used.

If a DOI is later minted through Zenodo or another archival service, prefer the DOI. Otherwise, the relevant GitHub Release URL or stable release PDF URL is sufficient for academic referencing.

Examples from this repository:

Suggested BibTeX pattern:

@book{reynoso_bookkey_year,
  author    = {Alejandro Reynoso},
  title     = {Book Title},
  year      = {Year},
  version   = {release-tag},
  publisher = {GitHub},
  url       = {https://github.com/alexdibol/books/releases/tag/release-tag}
}

Suggested BibTeX for the new book:

@book{reynoso_agentic_unification_trading_strategies,
  author    = {Alejandro Reynoso},
  title     = {Agentic Unification of Research and Implementation of Trading Strategies},
  version   = {book-quanconnect_converters-v01},
  publisher = {GitHub},
  url       = {https://github.com/alexdibol/books/releases/tag/book-quanconnect_converters-v01},
  note      = {SHA-256: a56b84c27b66683326fc12933c9183881d9902704940618f2e6e1f6c5fcda869}
}

License

  • Text and PDFs: CC BY 4.0 (Creative Commons Attribution 4.0)

You are free to share and adapt the material, provided appropriate credit is given to the author.

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Long-form research books on AI & Quant Finance—human-led, DOI-ready release

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