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MARKETS: Four Major Tops. One Recurring Pattern. Reef the Sails.

By RecessionALERT on June 1, 2026 in Research Papers

Every major market top of the modern era announced itself the same way: not with one alarm but with a cluster ringing at once. Stretched valuations, the narrowest single-name leadership of any modern top, professional cash below its own contrarian sell trigger, a quarter of the index already in private bear markets, and a credit structure as loose as 2007. Measured against 1999, 2007, and 2021, mid-2026 is the densest such reading since the dot-com peak. So reef the sails.

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ECONOMY: U.S 1Q2026 Report

By RecessionALERT on May 1, 2026 in Reflections

The Q1 2026 GDP advance estimate prints at 2.0% on three non-repeatable tailwinds — a federal payroll rebound, a tariff-driven inventory surge, and an AI capex pulse accounting for up to 79% of the print on a gross basis. Strip those out and the underlying pace is closer to the high-1s. Core PCE jumped 160 basis points in a single quarter to 4.3%. The Fed cannot cut into 4% inflation and cannot hike into a slowing consumer. The policy trap is set.

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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.