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A higher volatility stock, with the same expected return of 7% but with annual volatility of 20%, would indicate returns from approximately negative 33% to positive 47% most of the time (19 times out of 20, or 95%). These estimates assume a normal distribution; in reality stock price movements are found to be leptokurtotic (fat-tailed).
The realized volatility is the square root of the realized variance, or the square root of the RV multiplied by a suitable constant to bring the measure of volatility to an annualized scale. For instance, if the RV is computed as the sum of squared daily returns for some month, then an annualized realized volatility is given by 252 × R V ...
CBOE also calculates the Nasdaq-100 Volatility Index (VXNSM), CBOE DJIA Volatility Index (VXDSM) and the CBOE Russell 2000 Volatility Index (RVXSM). [6] There is even a VIX on VIX (VVIX) which is a volatility of volatility measure in that it represents the expected volatility of the 30-day forward price of the CBOE Volatility Index (the VIX). [10]
Calculating fair value: By comparing implied volatility with historical volatility, you can determine whether an option is fairly priced. If IV is significantly higher than HV, it may suggest that ...
Average true range (ATR) is a technical analysis volatility indicator originally developed by J. Welles Wilder, Jr. for commodities. [1] [2] The indicator does not provide an indication of price trend, simply the degree of price volatility. [3] The average true range is an N-period smoothed moving average (SMMA) of the true range values. Wilder ...
To calculate 'impact of prices' the formula is: Impact of prices = option delta × price move; so if the price moves $100 and the option's delta is 0.05% then the 'impact of prices' is $0.05. To generalize, then, for example to yield curves: Impact of prices = position sensitivity × move in the variable in question
Solving for volatility over a given set of durations and strike prices, one can construct an implied volatility surface. In this application of the Black–Scholes model, a coordinate transformation from the price domain to the volatility domain is obtained. Rather than quoting option prices in terms of dollars per unit (which are hard to ...
The volatilities in the market for 90 days are 18% and for 180 days 16.6%. In our notation we have , = 18% and , = 16.6% (treating a year as 360 days). We want to find the forward volatility for the period starting with day 91 and ending with day 180.