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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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MIB: AI Sentiment Reset, Gold at Record $5,200, and the $30B Warner Bros. Bidding War

By RecessionALERT on February 26, 2026 in Reflections

NVDA fell 5.5% despite record Q4 revenue ($68.1B, +73% YoY) — AI trade set to a new standard. Gold hit an all-time record above $5,200 as US-Iran nuclear talks in Geneva approach Trump’s March 6 strike deadline. WBD board calls Paramount Skydance’s $31/share bid “superior” to Netflix, starting a 4-day bidding war. Dell surges 9% after hours on a $22B AI server backlog. Fed Vice Chair Bowman signals broad bank deregulation. Nasdaq -1.2%, Russell +0.5% — sharpest rotation in months.

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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.