Partial-sample regression function to estimate the similarity, informativeness, and relevance of dependent variables.


Estimate results from the partial-sample regression model as described by Czasonis, Kritzman, and Turkington in their 2020 research paper (Journal of Portfolio Management, see reference link below).

One of our principals, Mark Kritzman, introduces this powerful model in a lecture at State Street's research retreat in 2020. View a recording on the lecture below.


The following describes the function signature for use in Microsoft Excel's formula bar.


Name-Value Optional Arguments

Specify optional pairs of arguments where Name is the option argument name and Value is the corresponding input object. Name-value arguments must appear after other input arguments above, but the order of these pairs does not matter.


=PSR(whichStat, y, x, theta, "Name1", value1, "Name2", value2, ..., "NameN", valueN) 


The function's output will vary depending on the specification of the whichStat argument. The following table will describe the corresponding output result. For M-dependent variables (y) and N-independent variables (x) across T-observations:


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