Estimates of the volatility for the ith day made at the end of the previous (i-1)th day, using an estimate of the volatility on the 0th day, according to the EWMA model with respect to changes in the market variable.
public double EwmaVolatilityEstimateInduction( doubleweightRatio, doublefirstDaysVolatilityEstimate, double[]endOfDay, double[]startOfDay );
Parameters
weightRatio
This constant between one and zero, is the ratio between the kth weight and the (k-1)th weight, for all k. The smaller the value used the more sensitive the model is to resent changes in the volatility.
firstDaysVolatilityEstimate
This is the estimate of the volatility on the 0th day.
endOfDay
This is an array of length i+1, where the first term is the closing value of the market variable (for example, the asset price) on the 0th day, the second element is the closing value of the market variable on the 1st day and so on.
startOfDay
This is an array of length i+1, where the first term is the opening value of the market variable (for example, the asset price) on the 0th day, the second element is the opening value of the market variable on the 1st day and so on.
Remarks
The
EWMA model is a special case of the ARCH model, where the weights assigned to the
historical volatility measure decreases by a constant factor.
Remarks:
Weight Ratio - J.P.Morgan's Riskmetrics groups found that across a range of market
variables, by taking weightRatio = 0.94, the forecasts of the volatility rate came
closest to the realized volatility.
Market Variable - the volatility can to measured with respect to any market variable.
The most common used market variable will be asset price in which case this method will
estimate the volatility of the price.