A short, annotated reading list. These are the original publications or official educational resources behind the essays. Inclusion is not an endorsement of every claim, and a historical paper should not be mistaken for a benchmark of today’s products.
Financial mechanics
SEC — How Fees and Expenses Affect Your Investment Portfolio
An official investor-education reference on fees. Read alongside the fee-compounding example; the numerical scenario in the essay is separate from the bulletin’s examples.
MSRB — Evaluating a Municipal Bond’s Interest Rate Risk
An introduction to duration and convexity in a municipal-bond context. The duration essay uses a generic zero-coupon example to isolate discounting.
SEC — How to Read a 10-K/10-Q
A map of the annual and quarterly filing. Useful before asking an assistant to summarize a document whose structure you have not yet inspected.
SEC — Beginners’ Guide to Financial Statements
An accessible introduction to financial statements. A starting reference for the evidence-first research workflow.
Research design and valuation
Bailey, Borwein, López de Prado & Zhu — The Probability of Backtest Overfitting (2015 revision)
A formal treatment of selection and backtest overfitting. Our backtest audit discusses additional practical issues, including timestamps and execution.
Aswath Damodaran, NYU Stern — An Introduction to Valuation
A foundation for connecting a business narrative with cash flows, growth, and risk. Read with Valuing AI Without Valuing the Story.
Aswath Damodaran, NYU Stern — The Fundamental Determinants of Growth
A reference on the relationship between growth, reinvestment, and returns on capital.
AI systems and evaluation
Lewis et al. — Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks (2020)
The original RAG paper. It provides the research context for retrieval, rather than a guarantee about any particular financial assistant.
Liu et al. — Lost in the Middle: How Language Models Use Long Contexts (2023)
A study of how evidence position affected the tested models. It motivates a test condition for your system; it does not establish a fixed limitation shared by all future models.
Chen et al. — FinQA: A Dataset of Numerical Reasoning over Financial Data (2021)
Financial question answering with annotated reasoning programs. Read with the separation of extraction and calculation.
NIST — Artificial Intelligence Risk Management Framework: Generative AI Profile (2024)
A broader voluntary risk-management reference, linked from the AI workflow economics essay.
Reading a source critically
Check the publication date, what was actually studied, and the difference between a result and a recommendation. For a financial figure, preserve its unit, reporting period, and definition. For an empirical AI result, preserve the model, task, and evaluation setting.
This list was assembled on October 26, 2026. It contains no live price feeds or automatically updated performance claims.