muS.sp500: Return Expectation and Covariance for "FRAPO"s SP500 data

Description Usage Format Source See Also Examples

Description

If R_{j,t} are the basically the scale standardized log returns for j = 1,2,…,476 of 476 stocks from S&P 500, as from SP500, then mu_j = E[R_{j,*}] somehow averaged over time; actually as predicted by muSigma() at the end of the time period, and Sigma[j,k] = Cov(R[j], R[k]) are estimated covariances.

These are the main “inputs” needed for the CLA algorithm, see CLA.

Usage

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data("muS.sp500")

Format

A list with two components,

mu

Named num [1:476] 0.00233 0.0035 0.01209 0.00322 0.00249 ...
names : chr [1:476] "A" "AA" "AAPL" "ABC" ...

covar

num [1:476, 1:476] 0.001498 0.000531 0.000536 ...

Source

It is as simple as this:

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    data(SP500, package="FRAPO")
    system.time(muS.sp500 <- muSigmaGarch(SP500))   #   26 sec. (lynne, 2017)
  

See Also

muSigmaGarch() which was used to construct it.

Examples

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Example output

List of 2
 $ mu   : Named num [1:476] 0.00233 0.0035 0.01209 0.00322 0.00249 ...
  ..- attr(*, "names")= chr [1:476] "A" "AA" "AAPL" "ABC" ...
 $ covar: num [1:476, 1:476] 0.001498 0.000531 0.000536 0.000305 0.000351 ...

CLA documentation built on Dec. 16, 2021, 5:07 p.m.