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MIB Daily: AVGO -12.6% Exposes AI Hardware’s Pricing Trap — Dow ATH Hides Labor Stagflation Heading Into Friday’s NFP

By RecessionALERT on June 4, 2026 in Reflections

AVGO −12.6% after AI chip guidance ($16B Q3) missed by $1.2B; SOX −2.8%, MU −7.74%. UNH +5.7% on dual BofA/MS upgrades lifted Healthcare +3.06% to drive the Dow to an ATH at 51,562. Ceasefire news cut WTI $3 to $93. Jobless claims 225K (highest since February) confirmed labor softening; Challenger’s 97K May cuts — 40% AI-driven — are a record. IMF extended the US inflation timeline to end-2027 ahead of Warsh’s first FOMC; Friday NFP consensus: 85K.

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MIB: Strait Relief — Record Highs, Oil Collapse, $127B Tariff Refunds, and a Fed Forced to Recalibrate

By RecessionALERT on April 17, 2026 in Reflections

Iran declared the Strait of Hormuz “completely open,” sending WTI oil crashing 11.4% in the largest single-day drop since the war began. S&P 500 closed above 7,100 for the first time (+1.20%); Nasdaq’s winning streak hit 13 sessions — longest since 1992. Netflix (NFLX −9.72%) tanked on weak Q2 guidance and Reed Hastings’ board exit. Fed’s Waller: rate cuts viable if Hormuz stays open. A $127B IEEPA tariff refund portal launches Monday.

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IMPORTANT DISCLAIMERS: Although many of our models rely heavily on back-testing, optimisation and probability methods, please note that past performance is NO GUARANTEE for future returns. No system devised by man can predict the future, let alone the future of the markets and economies. What we have are sets of mathematical models that use historical data and varying theories to pinpoint places in time when the STATISTICAL LIKELYHOOD of calling the start and end to recessions is the greatest. In the midst of all the best mathematical models, you can have geo-political events, wars, terrorist attacks, natural disasters and even nuclear accidents that tip everything upside down. This is always a risk factor you need to factor in on any recession call no matter how confident you are in a signal. The SuperIndexes are created through mathematical and statistical optimisation techniques that best fit the historical NBER data. There is no guarantee that out-of-sample performance will match that of prior in-sample performance.