July | 2020 | RecessionAlert

Archive | July, 2020

Global V-shaped recovery stopped in its tracks

By RecessionALERT on July 21, 2020 in Reflections

The US State and G8 Mobility Charts have just been updated in the Covid menu. The U.S has seen a whopping increase in infections across a broad swathe of states since emerging from lockdown : As a result, US and state economic mobility has taken a huge hit. Although the US is only about 49% of the G8 GDP, there are enough G8 members also taking strain to stall the entire G8 group recovery. Since the G8 represent almost 49% […]

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Headwinds increasing for the stock market

By RecessionALERT on July 10, 2020 in Reflections

NOTE : All images and charts displayed below are regularly updated and available to subscribers from the CHARTS menu. The SP-500 has enjoyed an incredible 40% rally since the 23 March lows. This was mostly fueled by an unprecedented FED stimulus program, which is now coming to an end within the next few weeks: Unless more stimulus is unleashed (and a further $1.5-$2 trillion seems likely) the risks of a stock market selloff are high, especially given that the market […]

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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.