Intro to Time Series
BFGS, which stands for Broyden-Fletcher-Goldfarb-Shanno, is an iterative algorithm used for solving unconstrained nonlinear optimization problems. This method is particularly useful in estimating parameters in statistical models like ARCH models, as it provides a way to efficiently find the minimum of a function by approximating the Hessian matrix. BFGS is valued for its ability to converge quickly, making it a popular choice in econometrics and time series analysis.
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