According to @QCompounding, the book Quality of Earnings emphasizes that traders should closely examine a company's financial statements and reported earnings to judge their true quality and reliability before making decisions; source: https://twitter.com/QCompounding/status/2006411094810570809. The stated takeaway is to prioritize validated earnings quality over headline figures as part of trading due diligence; source: https://twitter.com/QCompounding/status/2006411094810570809.

According to Edward Dowd, Nortel Networks’ share price topped in July 2000 after the company reported a quarter-over-quarter operating cash flow deceleration from 1.2 billion dollars to 800 million dollars, source: Edward Dowd on X, Nov 20, 2025, https://twitter.com/DowdEdward/status/1991337889821868073. He questions whether cash flow remains the decisive factor in today’s market, underscoring a trading takeaway to monitor operating cash flow momentum around earnings for potential risk signals in high-beta names, source: Edward Dowd on X, Nov 20, 2025, https://twitter.com/DowdEdward/status/1991337889821868073. For crypto-exposed equities, the post highlights applying the same cash-flow lens when evaluating listed miners and exchanges to gauge risk appetite across broader risk assets, source: Edward Dowd on X, Nov 20, 2025, https://twitter.com/DowdEdward/status/1991337889821868073.

According to @burrytracker, Michael Burry alleges that AI hyperscalers are inflating profits by extending server lifespans and masking approximately $176 billion in fake earnings (source: @burrytracker, Nov 10, 2025). The post characterizes the AI sector as a bubble and centers on earnings quality risks tied to depreciation and asset life assumptions, without naming specific companies (source: @burrytracker). For traders in AI-exposed equities and AI-themed crypto, the allegation highlights potential scrutiny of capex depreciation disclosures and sentiment around AI profitability narratives (source: @burrytracker).