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to be a variance strike and L {\displaystyle L} be a notional amount converting the payoffs into a unit amount of money, say, e.g., USD or GBP, then payoffs at expiry for the call and put options written on R V d {\displaystyle RV_{d}} (or just variance call and put) are
Historical simulation in finance's value at risk (VaR) analysis is a procedure for predicting the value at risk by 'simulating' or constructing the cumulative distribution function (CDF) of assets returns over time assuming that future returns will be directly sampled from past returns.
the variance strike; the realized variance; the vega notional: Like other swaps, the payoff is determined based on a notional amount that is never exchanged. However, in the case of a variance swap, the notional amount is specified in terms of vega, to convert the payoff into dollar terms. The payoff of a variance swap is given as follows:
The formulas used above to convert returns or volatility measures from one time period to another assume a particular underlying model or process. These formulas are accurate extrapolations of a random walk, or Wiener process, whose steps have finite variance. However, more generally, for natural stochastic processes, the precise relationship ...
In contrast, modern portfolio theory is based on a different axiom, called variance aversion, [27] and may recommend to invest into Y on the basis that it has lower variance. Maccheroni et al. [ 28 ] described choice theory which is the closest possible to the modern portfolio theory, while satisfying monotonicity axiom.
Algorithms for calculating variance play a major role in computational statistics.A key difficulty in the design of good algorithms for this problem is that formulas for the variance may involve sums of squares, which can lead to numerical instability as well as to arithmetic overflow when dealing with large values.
If the set is a sample from the whole population, then the unbiased sample variance can be calculated as 1017.538 that is the sum of the squared deviations about the mean of the sample, divided by 11 instead of 12. A function VAR.S in Microsoft Excel gives the unbiased sample variance while VAR.P is for population variance.
Firstly, while the sample variance (using Bessel's correction) is an unbiased estimator of the population variance, its square root, the sample standard deviation, is a biased estimate of the population standard deviation; because the square root is a concave function, the bias is downward, by Jensen's inequality.