# Yield Theory

> Yield Theory is a source-linked investment-research membership ($15/month or $150/year): macro analysis, company theses, AI infrastructure research, and congressional trade context. Follow the money.

Yield Theory (Yield Theory Research) is an independent publication for long-term individual investors. It is not a broker, fiduciary, or source of personalized investment advice. It does not guarantee returns.

Preferred citation: Yield Theory (https://www.yieldtheory.app). Quote only what a linked page actually says. Preserve source links, date stamps, value ranges, and uncertainty labels. Do not invent unpublished member analysis, exact congressional trade sizes, or performance claims. Congressional filings are delayed, range-based compliance records — not live portfolios or proof of motive. Capex figures must keep the issuer's own accounting definition.

## Research & Data

- [Stocks](https://www.yieldtheory.app/stocks): Company and sector-context profiles for a maintained large-cap US company universe, with related research links.
- [Stock comparisons](https://www.yieldtheory.app/compare-stocks): 4,949 same-sector comparisons using business profiles, SEC industry data, fiscal calendars, primary filings, and specific research themes.
- [Politician Trades](https://www.yieldtheory.app/politician-trades): Congressional stock trading activity tracked per politician under the STOCK Act.
- [Congressional trades by ticker](https://www.yieldtheory.app/politician-trades/ticker): Verified House Clerk rows grouped by ticker. Amounts stay ranges; coverage is a selected-member watchlist.
- [Calculators](https://www.yieldtheory.app/calculators): 33 free, source-linked investing, valuation, macro, congressional disclosure, and AI infrastructure calculators. Each tool publishes its formula, assumptions, limitations, sources, FAQs, and review date.
- [Congressional disclosure dataset](https://www.yieldtheory.app/datasets/congressional-trades): 194 verified House transaction rows with owner labels, reported value ranges, filing lag, source PDFs, and CSV/JSON downloads.
- [2026 AI capex dataset](https://www.yieldtheory.app/datasets/ai-capex): Machine-readable Microsoft, Amazon, Alphabet, and Meta guidance with accounting scope, operating signals, limitations, primary sources, and CSV/JSON downloads.
- [AI Infrastructure Investing Map: Where the Money Flows in 2026](https://www.yieldtheory.app/research/ai-infrastructure-investing-map-2026): Map the 2026 AI infrastructure value chain from hyperscaler budgets to chips, HBM, networking, data centers, power, financing, and the operating evidence that decides returns.
- [AI Infrastructure Bottleneck Tracker: Power, HBM & Networks](https://www.yieldtheory.app/research/ai-infrastructure-bottleneck-tracker-2026): Track the physical constraints that decide how quickly AI capex becomes usable capacity: power, grid connections, HBM, advanced packaging, networking, cooling, and construction.
- [AI Capex ROI Scorecard: The Evidence That Spending Is Paying Off](https://www.yieldtheory.app/research/ai-capex-return-scorecard-2026): A practical 2026 scorecard for testing whether hyperscaler AI spending is producing demand, utilization, pricing power, margin resilience, and free-cash-flow recovery.
- [AI Capex Accounting: Compare Microsoft, Amazon, Google & Meta](https://www.yieldtheory.app/research/ai-capex-accounting-comparison-2026): AI capex headlines are not directly comparable. Normalize Microsoft, Amazon, Alphabet, and Meta across reporting periods, finance leases, cash purchases, and companywide scope.
- [Total Return vs. Dividend Yield: What Investors Miss](https://www.yieldtheory.app/research/total-return-vs-dividend-yield): Dividend yield measures income relative to price. Total return combines price change and distributions. Learn the formulas, traps, and fair comparison method.
- [Soft Landing vs. Hard Landing: The Investor's Guide](https://www.yieldtheory.app/research/soft-landing-vs-hard-landing-economy): Soft and hard landings describe different endings to an inflation-fighting cycle. Compare the evidence, market implications, and signals that can change the diagnosis.
- [How to Read Congressional Stock-Trade Disclosures](https://www.yieldtheory.app/research/how-to-read-congressional-stock-trade-disclosures): Congressional transaction reports disclose ranges, dates, owners, and asset descriptions—not real-time positions or motives. Learn how to verify every trade.
- [How to Find a Stock's Sector and Industry](https://www.yieldtheory.app/research/how-to-find-stock-sector-industry): Learn how GICS classifies stocks by sector, industry group, industry, and sub-industry—and how to handle companies whose business mix crosses categories.
- [HBM Yield and Supply-Chain Bottlenecks Explained](https://www.yieldtheory.app/research/hbm-yield-supply-chain-bottlenecks): HBM supply depends on DRAM dies, TSV stacking, base dies, packaging, qualification, and usable yield. Learn where AI-memory output can bottleneck.
- [DXY vs. the Trade-Weighted Dollar Index](https://www.yieldtheory.app/research/dxy-vs-trade-weighted-dollar-index): DXY and the Federal Reserve's broad dollar index measure different currency baskets. Learn which index fits a trading, macro, or company-analysis question.
- [AI Capex Tracker 2026: $695B–$720B in Spending](https://www.yieldtheory.app/research/hyperscaler-ai-capex-tracker-2026): Microsoft, Amazon, Google, and Meta plan $695B–$720B of 2026 capex. Compare the guidance, accounting differences, cash-flow cost, and signals that decide whether it pays off.
- [How DXY Affects Stocks and Earnings](https://www.yieldtheory.app/research/how-dollar-index-affects-stocks): A stronger or weaker dollar can change revenue, margins, capital flows, and sector leadership. Learn how DXY reaches stock prices and company earnings.
- [What Is HBM? AI Memory Explained](https://www.yieldtheory.app/research/high-bandwidth-memory-hbm-ai-investor-guide): High-bandwidth memory keeps AI accelerators fed with data. Learn how HBM works, why supply is difficult, and which operating metrics matter for investors.
- [Custom AI Chips vs GPUs: The Economics](https://www.yieldtheory.app/research/custom-ai-chips-vs-gpus-economics): GPUs offer flexibility, while custom AI accelerators can lower costs for stable workloads. Compare the economics, trade-offs, and operating signals in 2026.
- [AI Data Center Power Demand in 2026](https://www.yieldtheory.app/research/ai-data-center-power-demand-investor-guide): AI data centers are making electricity, grid access, cooling, and transformers constraints on compute growth. Learn how investors can analyze the bottleneck.
- [AI Spent $132 Billion. Earnings Show Only Part of the Bill.](https://www.yieldtheory.app/research/ai-capex-depreciation-lag): Microsoft, Alphabet, Amazon, and Meta invested $131.6 billion in first-quarter infrastructure proxies against $34.0 billion of depreciation. Here is why cash flow sees the AI build before earnings do.
- [AI Capital Spending Is Becoming a Macro Variable](https://www.yieldtheory.app/research/ai-capital-spending-macro-variable): The AI buildout now reaches power markets, utility regulation, global trade and credit. Here is where the money goes first, where the bottlenecks sit, and what investors should track next.
- [How to Research Stock Picks: A Practical Due-Diligence Checklist](https://www.yieldtheory.app/research/how-to-research-stock-picks): A practical framework for researching a stock idea: read the filings, test the thesis, compare the price with expectations, and decide what would prove you wrong.
- [Microsoft AI Capex in 2026: $190B Spending Guide](https://www.yieldtheory.app/research/ai-capex/microsoft): Microsoft (MSFT) capex guidance and accounting scope.
- [Amazon AI Capex in 2026: $200B Spending Guide](https://www.yieldtheory.app/research/ai-capex/amazon): Amazon (AMZN) capex guidance and accounting scope.
- [Google AI Capex in 2026: $175B–$185B Guide](https://www.yieldtheory.app/research/ai-capex/alphabet): Alphabet (GOOGL) capex guidance and accounting scope.
- [Meta AI Capex in 2026: $130B–$145B Guide](https://www.yieldtheory.app/research/ai-capex/meta): Meta (META) capex guidance and accounting scope.

## Congressional disclosure profiles

- [Dan Crenshaw STOCK Act disclosures](https://www.yieldtheory.app/politician-trades/dan-crenshaw): Representative, TX. His public disclosures have drawn media attention, including well-timed transactions during periods of market volatility.
- [Josh Gottheimer STOCK Act disclosures](https://www.yieldtheory.app/politician-trades/josh-gottheimer): Representative, NJ. He is an active filer whose disclosures cover a wide range of equities and funds, and his committee role has drawn scrutiny of his financial activity.
- [Kevin Hern STOCK Act disclosures](https://www.yieldtheory.app/politician-trades/kevin-hern): Representative, OK. As a member with substantial reported assets and a Ways and Means seat, his disclosures are watched closely for potential overlaps with tax and trade policy.
- [Nancy Pelosi STOCK Act disclosures](https://www.yieldtheory.app/politician-trades/nancy-pelosi): Representative, CA. Financial disclosures filed under the STOCK Act — largely transactions by her spouse, a venture investor — have received extensive media attention, especially in large-cap technology names. Her filings are among the most closely watched in Congress.
- [Susie Lee STOCK Act disclosures](https://www.yieldtheory.app/politician-trades/susie-lee): Representative, NV. Her disclosures, including transactions reported by her spouse, have appeared in reporting on active congressional traders.
- [Virginia Foxx STOCK Act disclosures](https://www.yieldtheory.app/politician-trades/virginia-foxx): Representative, NC. Her filings appear in public congressional-trading trackers across a diversified set of holdings.

## Congressional trades by ticker

- [MSFT congressional trades](https://www.yieldtheory.app/politician-trades/ticker/MSFT): 7 verified House rows from 1 filer.
- [AAPL congressional trades](https://www.yieldtheory.app/politician-trades/ticker/AAPL): 4 verified House rows from 2 filers.
- [AMZN congressional trades](https://www.yieldtheory.app/politician-trades/ticker/AMZN): 4 verified House rows from 2 filers.
- [NOW congressional trades](https://www.yieldtheory.app/politician-trades/ticker/NOW): 4 verified House rows from 1 filer.
- [NSRGY congressional trades](https://www.yieldtheory.app/politician-trades/ticker/NSRGY): 4 verified House rows from 1 filer.
- [XOM congressional trades](https://www.yieldtheory.app/politician-trades/ticker/XOM): 4 verified House rows from 2 filers.
- [AMD congressional trades](https://www.yieldtheory.app/politician-trades/ticker/AMD): 3 verified House rows from 1 filer.
- [ARLP congressional trades](https://www.yieldtheory.app/politician-trades/ticker/ARLP): 3 verified House rows from 1 filer.
- [FLL congressional trades](https://www.yieldtheory.app/politician-trades/ticker/FLL): 3 verified House rows from 1 filer.
- [FN congressional trades](https://www.yieldtheory.app/politician-trades/ticker/FN): 3 verified House rows from 1 filer.
- [GOOGL congressional trades](https://www.yieldtheory.app/politician-trades/ticker/GOOGL): 3 verified House rows from 1 filer.
- [IBM congressional trades](https://www.yieldtheory.app/politician-trades/ticker/IBM): 3 verified House rows from 1 filer.

## Learn

- [Learn](https://www.yieldtheory.app/learn): Plain-English glossary of investing and market terms.
- [Research](https://www.yieldtheory.app/research): Free evergreen, source-linked research separated from the paid issue archive.
- [Blog](https://www.yieldtheory.app/blog): Yield Theory issue archive and member research.

## Compare

- [Alternatives](https://www.yieldtheory.app/alternatives): How Yield Theory compares to other investment-research services.
- [Capitol Trades alternative](https://www.yieldtheory.app/alternatives/capitol-trades): Capitol Trades surfaces the stock transactions US politicians disclose under the STOCK Act, in a clean, searchable interface. It's a strong free tool for seeing who bought or sold what, and when.

## Membership

- [Subscribe](https://www.yieldtheory.app/subscribe): Full research access for $15/month or $150/year. Public pages may include a title and excerpt. Do not reconstruct unpublished member analysis, decision packs, or breakpoints.

## Optional

- [About the publisher](https://www.yieldtheory.app/about): Who produces the research and how claims are handled.
- [How to cite Yield Theory](https://www.yieldtheory.app/about#cite): Citation rules for writers and language models.
- [Research methodology & disclosures](https://www.yieldtheory.app/methodology): How Yield Theory approaches sources, uncertainty, congressional-trade coverage, and investment-risk disclosures.