| |
| | | Advertisement | | |
| |
July 10, 2007 12:26 IST
Although traders cannot predict the future, they must make intelligent guesses as to what the future holds.
A standard approach used in option evaluation is to look at the past. What has historically been the volatility of a certain commodity?
If for instance, the volatility of Treasury Bonds has been no higher than 25 per cent over the last 10 years, then a guess of 30 per cent is somewhat impractical. Based upon the past 10 years, 25 per cent or lower proves to be more realistic value for the volatility.
There are a number or ways to calculate the historical volatility. The first thing to determine is the time frame.
Do you want to study the last 10 days, six months, or five years? What length of time is required to obtain an accurate picture?
Generally, traders tend to start looking at volatility over a long time, at least 10 years.
This allows them to identify short-term deviations from normal activity. However, you must not overlook the short-term volatility either.
If a commodity has averaged 25 per cent volatility over the last year, but only 15 per cent over the past thirty days, you may want to adjust the volatility estimates to accommodate the most recent data. Rather than using a figure of 25 per cent, adjusting the figure to 20 per cent as the midpoint may prove more accurate.
Once you establish a time frame, you need to determine the price intervals.
Volatility can vary greatly based on the interval. For example, you may decide to monitor the volatility of the last 10 weeks measuring the price changes at the close of each day. This figure can be quite different from that of the price changes at the end of each week.
Prices can fluctuate wildly from day to day, but finish the week unchanged. When this happens, volatility for the daily price changes is higher than that of the weekly price changes.
You may think that there are an infinite number of ways to calculate the historical volatility.
However, as long as price changes are measured at regular intervals, the annualised volatilities resulting from these intervals are usually very similar.
| |