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To calculate hitorical volatility, the following formula applies:
sigma = sqrrt ( (252/n-1) * sum ((Mean R - R) squared) ) for n incidences of R
Mean R is the average daily return over the time period being measured. It is calculated as:
Mean R = i/n * ( sum natural log (F i+1/Fi) ) for n incidences of F
F is simply the daily closing price.
If you want to calculate the historical volatility I suggest you use a spreadsheet like Excel. Alternatively, most charting programs will do it for you automatically.
Just out of curiosity, what are you planning to do with your measurement? One thing you might consider is tracking a longer term hist vol (such as 100 days) and comparing it to a shorter term reading. Larry Conners has done this with a 6 day reading. The logic being that (as Natenberg points out in his book) hist vol tends to revert to its mean. Conners has tried to prove that when a short term hist vol reading is under half that of the long term figure, there is likely to be an explosion in volatility. However, when I have tried to reproduce his findings, I have had difficulty doing so and so am a bit of a skeptic.
Alternatively you might compare hist vol to implied vol. When these two figures get seriously out of line, you know that either the market is being hideously inefficient (as in the days following a crash or a large correction), or else the market is factoring in information that you might not have access to. Either way, there are big $$$$ to be won and lost at these times.
Good trading.
- Stuart
>>> P Gumprecht <ktata@xxxxxxxxxxxxx> 06/26 11:16 AM >>>
Does anyone know about Sheldon NatenBerg's and Lawrence
McMillan's formula on historical volatility?
Thanks,
Peter.
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