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Difficulty: Medium
Category: time_series
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Topics: time-series, har-rv, realized-volatility, ols, volatility-forecasting, numpy
The Heterogeneous Autoregressive Realized Volatility (HAR-RV) model captures volatility's long-memory property using a simple cascade of daily, weekly, and monthly volatility components. It is a standard baseline in high-frequency finance for forecasting realized volatility, often outperforming traditional GARCH models. Estimating its parameters via Ordinary Least Squares (OLS) is a common task for quantitative researchers. Task Implement the function solution(rv: listfloat) -> dict to estimate
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