First, the range. Friday March 8, the range prices were 1.3133 high minus 1.2954 low = 179 pips, divide by 2 and my range is 89.1 pips, divide by 3 and my range is 59.2, multiply 179 by 2 = 358, True Range Average, 1.3043. Are we any smarter by this information, no.
How about measurement of a candlestick or sets of candles, no help either unless candles are measured for what they are and that is the Boxcar Average separated by either an average or Median Line to represent frequencies..Afterall , what allows the indicator Andrews Pitchfork 80 years later to be so effective is its use of this methodology. A double top or bottom sees price reversals because price frequencies in relation to its median price reached maximum extremes. Its seen in the candlestick pattern but few understand its actual methodology.
A range factors in mathematical terms many ways: Sine and cosine waves, percentiles, deciles, quartiles, interquartiles, frequencies, Standard Deviation. I measure my ranges by the Signal to Noise Ratio, the relationship between the mean and the standard deviation and an old old metric first used in electronics to measure actual radio sound to background noise.
A market price has two factors: a Signal or True market price and Noise measured by the variation of the True market price and seen in the variability of the Standard deviation. This questions asks how far is the market price from the True price and it changes on a daily basis as market prices trade. Signal and noise is found by first the signal or the mean of the market price and noise is the variation of the market price. An example from Friday.
Friday's True price signal mean was 1.3098 and the Standard Deviation was 0.0133, divide signal mean 1.3098 by Noise 0.0133 and we have a Signal to Noise Ratio of 98.4812, the higher the number the less is the range with good chances market prices will be stuck. As this number contracts, the more the range will increase.
A closer inspection of this relationship can be seen in the square root. 1.3098 = 1.1444, Noise = 9.923. Still high number so square root again, 1.06 vs 3.1. Now we can see the market price as a 1 to 3 basis in terms of the true price vs market noise. Afterall 1.3133 high to the 1.2954 low = 1.01% move and in line with normal market price movements.
If a range was measured by the Standard Deviation alone, we can see a 133 pip range but not enough to capture the actual range because the market moved by 179 pips for the day and because 133 pips is only the variability measure so any market range must be measured by the Interquartile range.
The Interquartile range is always the better measure because its not affected by outliers in my sets of Moving Averages. Plus if the Standard Deviation is larger than the Interquartile range then outliers are present in my averages so one indicator is a check on the other.
Now I take my SD 0.0133 X 1.34896 = my market range of 179 pips is established, 1.3133 minus 1.2954. The purpose here is to catch the top Amplitude of my Noise Ratio since my noise ratio is a high number. When price broke my mean 1.3098 the top amplitude of my signal number, well short without a look back since I know ranges are measured on a high low basis against my mean price. Noise is only the measure of the width.
Others can look at Signal to Noise in terms of Frequencies by high minus low divided by the noise number. My number is 1.8
I use the Signal to Noise ratio range against my probaility bands so then I can trade an actual trade comfortably and hit targets within ther context of my numbers.
I'm Brian Twomey authror of Inside the Currency Market