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Difficulty: Medium
Category: time_series
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Topics: pacf, partial_autocorrelation, levinson_durbin, ar_identification, time_series
The Partial Autocorrelation Function (PACF) isolates the direct correlation between a time series and its lagged version, controlling for the effects of all shorter lags. This makes it a primary diagnostic tool in quantitative finance for identifying the order of autoregressive (AR) models, analyzing strategy residual persistence, and modeling microstructure noise. This problem requires implementing the PACF by solving the Yule-Walker equations. Task Implement the function yule_walker_pacf(x: l
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