Quantile Regression
Many investors1 use regression methods to gauge the relative attractiveness of different firms, the risks inherent in active or passive portfolios, the historical performance of investment factors, and similar topics. Such research often focuses on understanding the “central tendency” within a data set, and for this purpose perhaps the most commonly used tool is regression based on ordinary least squares (OLS) approaches. OLS methods are designed to find the “line of best fit” by minimizing the sum of squared errors from individual data points. OLS analysis generally does a good job of describing the central tendency within a data set, but typically will be much less effective at describing the behavior of data points that are distant from the line of best fit. Quantile regressions, however, can be useful in such investigations. This statistical approach ...
Get Encyclopedia of Financial Models, 3 Volume Set now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.