Being mean with a pitchfork: And blowing out Bollinger

Recent speakers at STA monthly meetings have given a couple of interesting talks on the Andrews pitchfork and its modified version, written up in this blog earlier.  I have certainly used the analysis for many years and find it useful, especially as a guide to the sort of magnitude of moves one can expect, and the retracements, often in stages, that one must deal with while remaining inside a trend.

Now look at my first chart and see if you can say for certain that I have drawn my pitchfork correctly.  (The chart is a monthly one of US dollars per pound starting when some exchange rates began to float in 1972).  The lines certainly capture most of the price action, in a depressing and relentless move to sterling weakness.  The central tine is, in fact, the mean regression over the history of the decline and fall.  After 2017’s rally, prices were capped this year by the mean.  The outer lines are therefore, standard deviations around this, in this case 1 standard deviation.  As an aside, one that I’m increasingly using is a 1.6 standard deviation – about half way between 1 and 2, and a Fibonacci number).

Chart 1

The difference is that unlike the pitchfork which is static, the mean changes as new data is used for the calculation.  The second chart shows the weekly candles of the moves since late 2016, again 1 standard deviation containing nearly all price action.

Chart 2

The third chart shows how the rake of the trend steepened in August 2017, reflected in the mean regression line.

 

Chart 3

Another study which has some similarities, with a central line and upper and lower lines plotted around it, are Bollinger Bands.  These too are dynamic, narrowing as daily ranges narrow, bursting apart when prices push outside the recent band.  What I think might be improved on is the fact that the widening of the outer band is symmetrical, perhaps not giving enough weight to the direction of the breakout.  One way or another, the fourth chart, a weekly one of cable with a conventional 20 period and 2 standard deviations around it, has worked exceptionally well over what has been a torrid time for cable.

Chart 4

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About Nicole Elliott

Nicole Elliott

A graduate of the London School of Economics and Political Science (BSc Social Psychology) Nicole Elliott has worked in banks in the City of London for the last 30 years. Whether in sales, trading or forecasting technical analysis has always been the bedrock of her thinking. Key expertise lies within all areas of treasury: foreign exchange, money markets, fixed income and commodities.

She has also added to the body of knowledge of the industry writing the first western book on Ichimoku Cloud Charts. Strong media links and a cult following are due to her prescient calls on the markets and often entertaining format.

Nicole can be contacted at trending@sta-uk.org

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