January | 2012 | RecessionAlert

Archive | January, 2012

Further Improving the Use of the ECRI WLI (Part-II)

By RecessionALERT on January 20, 2012 in Research Papers

This article was co-authored with Georg Vrba and first appeared on the popular Advisor Perspectives web site on 17 January 2012 In our last article on using the ECRI WLI, we described how best to use the growth figure of the Economic Cycle Research Institute’s Weekly Leading Index (WLI) to predict recessions, but we also highlighted […]

Read full story · Comments are closed

Using the ECRI WLI to Flag Recessions (Part-I)

By RecessionALERT on January 10, 2012 in Research Papers

In September 2011, the Economic Cycle Research Institute proclaimed a new U.S recession would begin sometime in the coming year. ECRI based its prediction on a host of its own internal long-leading indexes, together with its widely followed weekly leading index (WLI). I do not wish to debate the merits of ECRI’s recession call here […]

Read full story · Comments are closed

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.