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Easy · statistical_analysis · Quant Researcher interview question · volatility, ohlc, statistics, realized-variance, numpy-free
The Rogers-Satchell volatility estimator is a method for estimating historical volatility that uses open, high, low, and close prices. It is considered more efficient than simpler estimators because it accounts for price trends (drift) and is unbiased. In quantitative finance, it is frequently used as a daily realized variance proxy for calibrating volatility models and in risk management. Task Implement the function solution(open_: list, high: list, low: list, close: list) -> float to compute