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8 / 9 tenuous relationship with long-term performance – see also quarterly inflation figures , monthly non-farm payroll numbers in the US and daily news of currency fluctuations to two decimal places . Such movements can be “ make or break ” for derivatives traders , but have little relevance for long-term investors until they begin to shape a multi-year trend .
So , how can investors separate “ the noise ” from what really matters ?
The wrong man Andrew Vaughan , manager of the
CFP SDL Free Spirit fund , says he is “ probably the wrong person to ask about ignoring the noise , because it ’ s just what we do ”. He follows the “ Business Perspective Investing ”
FAKE NEWS Matt Beesley , chief investment officer of Artemis , says that one of the biggest problems with basing an investment decision on a snapshot of macroeconomic data is that even official sources frequently get it wrong . Non-farm payroll data in the US can be particularly problematic . This often dictates near-term sentiment , with volumes in equity , bond and foreign exchange markets waning in advance of its publication , and “ the print ” driving market direction for that trading session .
However , Beesley notes it is one of the most heavily revised economic statistics . “ When the number is reported , it doesn ’ t fully capture all of the changes in data for the month because the month has only just ended ,” he says . “ But more than that , the scope of the data doesn ’ t include all the services sector nor underlying changes in small companies or self-employment . More broadly , the efficacy of the data point as a predictor of trends in employment is questionable given the seasonality of labour trends .”
Similar caveats apply to quarterly US GDP data , which is simply an advance estimate based on two months ’ data and sometimes no data at all – instead , the US Bureau of Economic Analysis ( BEA ) makes “ assumptions based on a variety of sources ”. It is a similar story in the UK . “ When GDP estimates are published it is typically with only about half the required data available to the Office for National Statistics ,” says Beesley . “ So again , not data series to be ignored , but data series that require a caveat .”
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