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The standard deviation is the square root of the variance. The standard deviation of the continuously compounded returns of a financial instrument is called volatility . The (yearly) volatility in a given asset price or rate over a term that starts from t 0 = 0 {\displaystyle t_{0}=0} corresponds to the spot volatility for that underlying, for ...
For any fund that evolves randomly with time, volatility is defined as the standard deviation of a sequence of random variables, each of which is the return of the fund over some corresponding sequence of (equally sized) times. Thus, "annualized" volatility σ annually is the standard deviation of an instrument's yearly logarithmic returns. [2]
For instance, an A-VIX value of 20% can be converted to a monthly figure, remembering that volatility scales at the square root of time, the formula is: 20% x √ 1/12 = 5.77% In the above example, index options over the S&P/ASX 200 are incorporating the potential for a one standard deviation return over the next month of +/- 5.77%.
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 ...
S&P 500 with 20-day, two-standard-deviation Bollinger Bands, %b and bandwidth. Bollinger Bands (/ ˈ b ɒ l ɪ n dʒ ər /) are a type of statistical chart characterizing the prices and volatility over time of a financial instrument or commodity, using a formulaic method propounded by John Bollinger in the 1980s.
Volatility is measured as the standard deviation of S&P500 one-day returns over a month's period. The blue lines indicate linear regressions, resulting in the correlation coefficients r shown. Note that VIX has virtually the same predictive power as past volatility, insofar as the shown correlation coefficients are nearly identical.
However the standard procedures used to compute volatility of stock prices, such as the standard deviation of logarithmic price ratios, are not invariant (to addition of a constant). Thus futures traders and analysts typically use one method (ATR) to calculate volatility, while stock traders and analysts typically use standard deviation of log ...
The MPT is a mean-variance theory, and it compares the expected (mean) return of a portfolio with the standard deviation of the same portfolio. The image shows expected return on the vertical axis, and the standard deviation on the horizontal axis (volatility). Volatility is described by standard deviation and it serves as a measure of risk. [7]