Volatility is critical to risk measurement. Generally, volatility refers to standard deviation, which is a dispersion measure. Greater dispersion implies greater risk, which implies higher odds of a price erosion or portfolio loss - this is key information for any investor. We often estimate future volatility by looking at historical volatility.
The volatility of CNX Nifty is shown above.
The volatility of CNX Nifty is shown above.
The volatility presented above is for 30 days. It is computed using the following method
a) Ln (Closing Index value/ Closing Index value of previous day) is computed for every day = X
b) Volatility = Standard Deviation of 30 days values of X multiplied by square root of 250 (it assumed that there are 250 trading days in a year)
Just before the crash of May ’04, the volatility had soared to levels of 55-60% and it came down to levels of 20% by July. The Nifty corrected from a peak of 1833 to 1504. During the summer of 2006, the volatility again rose to 50% and above and a sharp correction followed as the Nifty went down from an intermediate peak of 3754 to 2633. The smaller fall in August this year was also preceded by higher volatility. The volatility is seen to be rising again and is pushing the 30% mark.
a) Ln (Closing Index value/ Closing Index value of previous day) is computed for every day = X
b) Volatility = Standard Deviation of 30 days values of X multiplied by square root of 250 (it assumed that there are 250 trading days in a year)
Just before the crash of May ’04, the volatility had soared to levels of 55-60% and it came down to levels of 20% by July. The Nifty corrected from a peak of 1833 to 1504. During the summer of 2006, the volatility again rose to 50% and above and a sharp correction followed as the Nifty went down from an intermediate peak of 3754 to 2633. The smaller fall in August this year was also preceded by higher volatility. The volatility is seen to be rising again and is pushing the 30% mark.
