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Medium · statistical_analysis · Quant Researcher interview question · cochrane_orcutt, generalized_least_squares, serial_correlation, ar1_errors, statistical_analysis
Time series regressions in quantitative finance often exhibit serially correlated errors, rendering Ordinary Least Squares (OLS) inefficient. The Cochrane-Orcutt procedure provides an iterative method to obtain efficient Generalized Least Squares (GLS) estimates by correcting for first-order autoregressive (AR(1)) errors. It involves repeatedly estimating the autocorrelation coefficient and re-running OLS on quasi-differenced data until parameter estimates converge. Task Implement the function