Total rookie question....

[kut2k2]

Quote from Sparohok:

I think the basic idea is that you can always get more information about volatility by looking at a shorter timescale. The more information you have the faster your estimate will converge, resulting in a more responsive estimator. However intraday data is difficult to work with, and less widely available than end of day data. Open-high-low-close bars provides some information about intra-period volatility and results in a slightly faster estimator than open-close bars.

You can find a lot of good stuff through scholar.google.com.

Martin

Thanks for another informative post, Martin.

Here's what I found on Rogers-and-Satchell:

It is designed to be 'drift-independent'. I'm not sure what the advantage of that is.

The n-day volatility_RS is

(volatility_RS)^2 =
(1/n)*SUM_from_i=1_to_i=n[ ln[Hi/Oi]*ln[Hi/Ci] + ln[Li/Oi]*ln[Li/Ci] ]

This is apparently designed to measure the deviation from the trendline between Oi and Ci for every day from i=1 to n. It is an all-intra-day (no interday) measure.

 

[kut2k2]

Quote from thenewguy:

Thanks for all the replies!

In regards to the HV, I've noticed two different approaches, in excel.

ln(today's close/yesterday's close) equals something marginally different than (today's close/yesterday's close - 1) in excel.

Does anyone know which is more accurate?

Thanks,

The New Guy

You want to use the log definition, because a key assumption of Black-Scholes is that price is lognormal, that is, price returns as measured by ln[CLOSEtoday/CLOSEyesterday] have a normalized Gaussian probability distribution.