mathGmvMuCov

Compute the weights, mean return and volatility of a GMV portfolio based on
user specified mean vector and covariance matrix

A collection of functions and data sets that support teaching
a quantitative finance MS level course on Portfolio Construction and Risk
Analysis, and the writing of a textbook for such a course.  The package is
unique in providing several real-world data sets that may be used for problem
assignments and student projects.  The data sets include cross-sections of
stock data from the Center for Research on Security Prices, LLC (CRSP),
corresponding factor exposures data from S&P Global, and several SP500 data
sets.

Doug Martin

PCRA

Companion to Portfolio Construction and Risk Analysis

Alexios Galanos

Kirk Li

Jon Spinney

Thomas Philips

mathGmvMuCov function

<dl><dt>muRet</dt>
<dd>Mean vector</dd>
<dt>volRet</dt>
<dd>Volatility vector</dd>
<dt>corrRet</dt>
<dd>matrix of correlations</dd>
<dt>digits</dt>
<dd>Integer value number of decimal places, default 3</dd></dl>

Arguments

Global Minimum Variance Portfolios From Mu and Cov — mathGmvMuCov

<dl>

<dt>muRet</dt>
<dd>Mean vector</dd>


<dt>volRet</dt>
<dd>Volatility vector</dd>


<dt>corrRet</dt>
<dd>matrix of correlations</dd>


<dt>digits</dt>
<dd>Integer value number of decimal places, default 3</dd>

</dl>

mathGmvMuCov: Global Minimum Variance Portfolios From Mu and Cov

Description

Usage

Value

Arguments

Examples