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MIB: Narrow Record — Intel Blowout and DOJ-Powell Resolution Lift S&P/Nasdaq as UMich Hits All-Time Low

By RecessionALERT on April 24, 2026 in Reflections

S&P 500 (+0.80%) and Nasdaq 100 (+1.95%) hit fresh records as Intel (+23.6%) blew out Q1 — best day since 1987 — dragging AMD (+13.9%) and NVDA (+4.3%, back above $5T). But the rally was narrow: Dow (-0.16%), Transports (-0.94%), NYSE Composite all red. DOJ dropped its Powell probe, clearing Warsh’s path; 10Y slipped to 4.31%. UMich sentiment crashed to a record-low 49.8 with 1-year inflation expectations spiking to 4.7%. Mega-cap tech earnings loom next week.

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MIB: $100 Oil, Five Straight Down Weeks, and a Consumer Sentiment Reading From the Abyss

By RecessionALERT on March 27, 2026 in Reflections

WTI crude above $100 for first time since 2022; Trump’s Iran deadline extension did nothing to calm markets. Dow enters correction; S&P posts 5th straight losing week — worst streak in 4 years. Macquarie warns 40% chance of $200 oil, $7/gallon gasoline if war lasts to June. Gold surges to $4,521/oz as VIX spikes 13% to 31. AZN +2.74% on Phase 3 COPD breakthrough. UMich crashes to 53.3 — bottom 1st percentile of all-time survey history.

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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.