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MIB: Stagflation Trap — Iran Sends Oil Past $101 While Google’s AI Crushes Semis and Meta Faces $Billions in Verdicts

By RecessionALERT on March 26, 2026 in Reflections

Iran denies US peace talks, pushing Brent crude past $101 and extending the Hormuz chokehold. Google’s TurboQuant crushed semiconductor stocks (LRCX -9.4%, AMAT -8.3%, AMD -7.5%, MU -7%). Meta shed 8% on a landmark social media addiction verdict. Nasdaq entered correction territory (-10%). OECD raised US inflation forecast to 4.2% for 2026, highest in G7. BlackRock downgraded US equities to neutral as stagflation fears mount.

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MIB: Q4 GDP Revised to 0.7%, Iran Vows Hormuz Shut, S&P Posts Third Weekly Loss, Adobe CEO Exits

By RecessionALERT on March 13, 2026 in Reflections

Iran’s new supreme leader vows Hormuz closure permanent; WTI near $100 for second straight day. Q4 GDP revised to +0.7% — stagflation trap confirmed. S&P 500 records third consecutive weekly loss, Nasdaq -0.68%. Adobe (ADBE) -7.5% as CEO Narayen exits after 18 years despite record Q1 beat. Trump’s Russia oil sanctions relief fails, allies furious. All eyes on FOMC March 17-18 — Powell’s stagflation signal is next week’s defining risk.

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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.