Stock Research With AI : The Business-Quality & Valuation Scoring Protocol
Language: English
Published by Amazon Digital Services LLC - Kdp Sep 2026, 2026
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 27.65
Quantity: 2 available
Add to basketItem description from seller
Neuware - A systematic, evidence-first framework for equity research using generative AI. Twelve evidence-scored factors. One honest percentage. Comparing companies goes wrong in a familiar way. You study three of them, form an impression of each, and the impressions harden into a ranking before any rule for ranking has been stated. This book replaces the impression with twelve small decisions, each made against a threshold you write down before you read the evidence, and each tied to a quotable line in a primary document.Book Two of the Stock Research With AI series is a scoring protocol you run with an AI model that has live web search. Six factors describe the business (competitive intensity, growth tailwinds and headwinds, revenue concentration, market headroom, order book, growth runway). Six describe how it is priced (growth-adjusted PEG, P/E against its own history and against peers, price-to-book, dividend yield and capital return, and a quality-haircut PEG). A chain of nineteen prompts scores each factor, and every prompt chapter shows why each instruction is worded as it is, a worked specimen output and a mandatory verification block.What you will learn to doThe reference section includes a book of thirty-three rulings for edge cases, a worked case in which the protocol declines to score, templates, and the complete evidence file for the worked example, which scores four invented companies from invented documents.What this book is notIt contains no stock tips, no buy or sell calls, no model portfolio and no ranking of real companies. A score here is a position on a fixed scale, not a forecast, a fair-value estimate or a recommendation. The book is educational and is not investment advice. AI models can fabricate figures with complete confidence, so every number must be verified against a primary source, and the book builds that habit into every chapter.Book Two of Three in the VV Research AI Investing Series. It is designed to follow Book One, The Seven-Screen Prompt System, whose research files it draws on.Fix the rules of comparison in a lock sheet before you see the answer- Tie every score to an evidence line you can check against a filing or transcript- Catch the false uniformity that AI models produce when asked to score- Run a blind independent re-read and resolve disagreements by evidence- Test how much of the final percentage survives a change in weighting- Roll a scorecard forward and separate price-driven change from evidence-driven change.…
Seller Inventory # 9798176695885
- Title
- Stock Research With AI : The Business-Quality & Valuation Scoring Protocol
- Author
- Vv Research
- Publisher
- Amazon Digital Services LLC - Kdp Sep 2026
- Publication year
- 2026
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 13
- 9798176695885
- Item weight
- 259 grams
- Dimensions
- 229x152x10 mm
- Series
- Book 2 of 2: VV Research AI Investing Series
A systematic, evidence-first framework for equity research using generative AI.
Twelve evidence-scored factors. One honest percentage.
Comparing companies goes wrong in a familiar way. You study three of them, form an impression of each, and the impressions harden into a ranking before any rule for ranking has been stated. This book replaces the impression with twelve small decisions, each made against a threshold you write down before you read the evidence, and each tied to a quotable line in a primary document.
Book Two of the Stock Research With AI series is a scoring protocol you run with an AI model that has live web search. Six factors describe the business (competitive intensity, growth tailwinds and headwinds, revenue concentration, market headroom, order book, growth runway). Six describe how it is priced (growth-adjusted PEG, P/E against its own history and against peers, price-to-book, dividend yield and capital return, and a quality-haircut PEG). A chain of nineteen prompts scores each factor, and every prompt chapter shows why each instruction is worded as it is, a worked specimen output and a mandatory verification block.
What you will learn to do
The reference section includes a book of thirty-three rulings for edge cases, a worked case in which the protocol declines to score, templates, and the complete evidence file for the worked example, which scores four invented companies from invented documents.
What this book is not
It contains no stock tips, no buy or sell calls, no model portfolio and no ranking of real companies. A score here is a position on a fixed scale, not a forecast, a fair-value estimate or a recommendation. The book is educational and is not investment advice. AI models can fabricate figures with complete confidence, so every number must be verified against a primary source, and the book builds that habit into every chapter.
Book Two of Three in the VV Research AI Investing Series. It is designed to follow Book One, The Seven-Screen Prompt System, whose research files it draws on.
Fix the rules of comparison in a lock sheet before you see the answer- Tie every score to an evidence line you can check against a filing or transcript
- Catch the false uniformity that AI models produce when asked to score
- Run a blind independent re-read and resolve disagreements by evidence
- Test how much of the final percentage survives a change in weighting
- Roll a scorecard forward and separate price-driven change from evidence-driven change
"Synopsis" may belong to another edition of this title.
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