October | 2020 | RecessionAlert

Archive | October, 2020

A new, bigger U.S Coronavirus peak now likely

By RecessionALERT on October 20, 2020 in Reflections

For a while, it seemed we had tamed the coronavirus epidemic in the US. But new daily cases are on the 3rd surge since the epidemic hit US shores: The U.S lags most of Europe’s ‘ countries by about 4-6 weeks on the coronavirus curve. When we saw the infections picking up in Europe after lockdowns had been eased, we wondered if the US might be able to dodge a bullet, but sadly it appears a new wave of infections […]

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Coronavirus Recession likely ended in June

By RecessionALERT on October 12, 2020 in Reflections

In this exercise, we examine the current behavior of various of our US leading economic indexes to past history to determine a likely recession exit date. The charts we display below are automatically displayed (depending on your selections) in the monthly data file Analysis Tool that is published for PRO subscribers, and can be found in the new RECOVERY sheet in the Excel workbook. We start with our oldest and most widely followed index, the Weekly Leading SuperIndex: Let us […]

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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.