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Using the selectCRSPandSPGMI function with stocksCRSP and factorsSPGMI, create a similar dataset to factorsDataSetDjia5Yrs and replace in all examples. When done, move the legacy data set to the sandbox. Related to #25
Running grep -rnw factorDataSetDjia5Yrs R/*.R in the linux terminal gives me:
Using the
selectCRSPandSPGMI
function withstocksCRSP
andfactorsSPGMI
, create a similar dataset tofactorsDataSetDjia5Yrs
and replace in all examples. When done, move the legacy data set to the sandbox. Related to #25Running
grep -rnw factorDataSetDjia5Yrs R/*.R
in the linux terminal gives me:R/assetDecomp.R:30:#'data("factorDataSetDjia5Yrs")
R/assetDecomp.R:35:#'fit <- fitFfm(data=factorDataSetDjia5Yrs, asset.var="TICKER", ret.var="RETURN",
R/exposuresTseries.R:22:#' data("factorDataSetDjia5Yrs")
R/exposuresTseries.R:26:#'exposuresTseries(factorDataSetDjia5Yrs,tickers = tickers,which.exposures = "MKTCAP")
R/exposuresTseries.R:30:#'exposuresTseries(factorDataSetDjia5Yrs,tickers = tickers,plot.returns = FALSE)
R/exposuresTseries.R:33:#'exposuresTseries(factorDataSetDjia5Yrs,tickers = tickers,plot.returns = TRUE, axis.cex = 0.8,
R/factorDataSetDjia5Yrs.R:1:#' factorDataSetDjia5Yrs
R/factorDataSetDjia5Yrs.R:14:#' @Usage data('factorDataSetDjia5Yrs')
R/factorDataSetDjia5Yrs.R:38:#' data(factorDataSetDjia5Yrs)
R/factorDataSetDjia5Yrs.R:39:#' str(factorDataSetDjia5Yrs)
R/factorDataSetDjia5Yrs.R:40:"factorDataSetDjia5Yrs"
R/fitFfm.R:180:#' data("factorDataSetDjia5Yrs")
R/fitFfm.R:184:#' fit <- fitFfm(data=factorDataSetDjia5Yrs, asset.var="TICKER", ret.var="RETURN",
R/fitFfm.R:190:#' fit1 <- fitFfm(data=factorDataSetDjia5Yrs, asset.var="TICKER", ret.var="RETURN",
R/fitFfm.R:196:#' factorDataSetDjia5Yrs$COUNTRY = rep(rep(c(rep("US", 1 ),rep("GERMANY", 1 )), 11), 60)
R/fitFfm.R:199:#' # fit.MICM <- fitFfm(data=factorDataSetDjia5Yrs, asset.var="TICKER", ret.var="RETURN",
R/fmmcSemiParam.R:102:#' data("factorDataSetDjia5Yrs")
R/fmmcSemiParam.R:104:#' fit.ffm <- fitFfm(data = factorDataSetDjia5Yrs,
R/fmRsq.R:34:#' data("factorDataSetDjia5Yrs")
R/fmRsq.R:38:#' fit <- fitFfm(data = factorDataSetDjia5Yrs,
R/fmRsq.R:47:#' fit1 <- fitFfm(data=factorDataSetDjia5Yrs, asset.var="TICKER", ret.var="RETURN",
R/fmTstats.R:55:#' data("factorDataSetDjia5Yrs")
R/fmTstats.R:58:#' fit <- fitFfm(data = factorDataSetDjia5Yrs,
R/fmTstats.R:70:#' fit1 <- fitFfm(data = factorDataSetDjia5Yrs, asset.var = "TICKER",
R/fmTstats.R:82:#' # factorDataSetDjia5Yrs$COUNTRY = rep(rep(c(rep("US", 1 ), rep("GERMANY", 1 )), 11), 60)
R/fmTstats.R:84:#' # fit.MICM <- fitFfm(data = factorDataSetDjia5Yrs,
R/plot.ffm.R:112:#' data("factorDataSetDjia5Yrs")
R/plot.ffm.R:116:#' fit.style.sector <- fitFfm(data=factorDataSetDjia5Yrs, asset.var="TICKER",
R/predict.ffm.R:36:#' data("factorDataSetDjia5Yrs")
R/predict.ffm.R:39:#' fit <- fitFfm(data = factorDataSetDjia5Yrs,
R/predict.ffm.R:46:#' newdata <- as.data.frame(unique(factorDataSetDjia5Yrs$TICKER))
R/print.ffm.R:21:#' data("factorDataSetDjia5Yrs")
R/print.ffm.R:23:#' fit.style.sector <- fitFfm(data=factorDataSetDjia5Yrs,
R/summary.ffm.R:38:#' data("factorDataSetDjia5Yrs")
R/summary.ffm.R:41:#' fit <- fitFfm(data = factorDataSetDjia5Yrs,
R/VIF.R:32:#' data("factorDataSetDjia5Yrs")
R/VIF.R:36:#' fit <- fitFfm(data=factorDataSetDjia5Yrs, asset.var="TICKER", ret.var="RETURN",
R/wtsDjiaGmvLo.R:5:#' @description Contains weights obtained after optimizing the portfolio returns of the 30 DJIA stocks (from dataset \link{factorDataSetDjia5Yrs})
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