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ECRI WLI Growth Conundrum

By RecessionALERT on March 27, 2012 in Reflections

More recently, ECRI has switched from the use of smoothed 6-month growth rates (as calculated by their WLIg growth metric) to annual (52-week) growth numbers of its Weekly Leading Index (WLI) to prop up a recession scenario. The reason cited is “…a widespread seasonal adjustment problem that economists have known about for some time.” Another native Capetonian, Prieur du Plessis, who regularly tracks the WLI has posted an excellent analysis of the rationale behind this descision that highlights some interesting subtleties between the […]

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U.S economy almost back to par growth

By RecessionALERT on March 25, 2012 in Reflections

The U.S Coincident SuperIndex, which estimates U.S economic current growth, is within a whisker of returning to the growth rate normally averaged by the economy after 33 months into an expansion, as shown by the chart on the left. However, cumulative growth since the start of the expansion still remains sub-par (right chart) due to 22 months of sub-par growth. The recent 5 months of growth, coupled with almost reaching the par growth level are encouraging, but the sub-par cumulative expansion […]

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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.