ما معنى Parkinson, Garman–Klass and Yang–Zhang estimators؟

With $H, L, O, C$ a day’s high, low, open and close, the Parkinson estimator of the daily variance is $(\ln H/L)^2/(4\ln 2)$; the Garman–Klass estimator is $\tfrac12(\ln H/L)^2 - (2\ln 2 - 1)(\ln C/O)^2$; the Rogers–Satchell estimator is $\ln(H/C)\ln(H/O) + \ln(L/C)\ln(L/O)$. The Yang–Zhang estimator over $n$ days adds the sample variance of overnight returns, $k$ times that of open-to-close returns and $1 - k$ times the average Rogers–Satchell term, with $k = 0.34/(1.34 + (n+1)/(n-1))$.