Fundamental vs. technical vs. sentiment analysis — what each lens answers (what a business is worth, what the market is doing, what the crowd believes), where each is strong, and why you do not have to pick one. Combining all three reveals when the company, the price, and the narrative disagree — often the most useful signal. Educational research, never advice.
2026年8月6日
What insider buying and selling really tell you about a stock — how to read SEC Form 4, open-market purchases versus stock awards, why buying is often more informative than selling, cluster buying, transaction size relative to ownership, and when insider activity is misleading (10b5-1 plans, tax selling). Third-party facts to weigh, never a recommendation. Educational research, never advice.
2026年8月5日
Why do AI stock reports hallucinate — invented metrics, stale prices, misread filings, confused tickers, wrong earnings dates — and how do you catch it? A practical reliability framework for verifying any AI-generated research: source every claim, record the as-of date, prioritize official filings, separate facts from interpretation, and flag missing data. Educational research, never advice.
2026年8月4日
A section-by-section guide to reading a 10-K annual report — Business & segments, Risk Factors, MD&A, the financial statements, cash flow & debt, stock-based compensation, legal proceedings, and the warning signs investors overlook. Learn how to check a company's story against its own sworn SEC filing. Educational research, never advice.
2026年8月3日
A stock can drop 8% on an earnings "beat" — because the market grades results against expectations and guidance, not raw numbers. Here are 8 reasons stocks fall after good earnings: already priced in, weak guidance, shrinking margins, higher spending, the whisper number, poor cash flow, a missed key metric, and a worrying call tone. Educational research, never advice.
2026年8月2日
Can you trust AI stock analysis? A practical 10-check checklist for evaluating any AI-generated stock report — sourced claims, current data, SEC filings, facts vs. assumptions, both sides of the argument, disclosed uncertainty, explained valuation, reproducibility, missing-data flags, and a readable research trail. Educational research, never advice.
2026年8月1日
How to build the bull case and the bear case as two real, opposing arguments and stress-test a stock before investing — revenue and margin assumptions, valuation under bull/base/bear scenarios, competitive and regulatory risks, catalysts, thesis-breaking indicators, and how to weigh conflicting evidence. Educational research, never advice.
2026年7月31日
A screener filters the market down to a shortlist; a research platform does the homework on each name. Here's the real difference between an AI stock screener and an AI stock research platform — filtering vs. discovering vs. full fundamental, valuation, news, sentiment, technical, catalyst and risk research — and why serious investors need both, in order. Educational research, never advice.
2026年7月30日
A repeatable 12-step checklist for how to research a stock before buying — business model and moat, revenue, margins, cash flow, debt, valuation vs peers, earnings history, insiders, sentiment, and the bull/base/bear scenarios (plus the risks that would prove your thesis wrong). Educational research, never advice.
2026年7月29日
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