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Description
With the following example:
https://github.com/braverock/FactorAnalytics/blob/master/R/plot.ffm.R#L111-L122
data(factorDataSetDjia5Yrs)
# fit a fundamental factor model
exposure.vars <- c("P2B", "MKTCAP")
fit.style.sector <- fitFfm(data=factorDataSetDjia5Yrs, asset.var="TICKER",
ret.var="RETURN", date.var="DATE",
exposure.vars=exposure.vars)
plot(fit.style.sector)
Make a plot selection (or 0 to exit):
1: Distribution of factor returns
2: Factor exposures from the last period
3: Actual and Fitted asset returns
4: Time-series of R-squared values
5: Residual variance across assets
6: Scatterplot matrix of residuals, with histograms, density overlays, correlations and significance stars
7: Factor Model Residual Correlation
8: Factor Model Return Correlation
9: Factor Contribution to SD
10: Factor Contribution to ES
11: Factor Contribution to VaR
12: Time series of factor returns
option 3: Actual and Fitted asset returns
Error in xts(x, order.by = order.by, frequency = frequency, .CLASS = "double", :
NROW(x) must match length(order.by)
option 4: Time-series of R-squared values
Doesn't have an error, but chart isn't produced
option 8: Factor Model Return Correlation
rror in cov2cor(fmCov(x)[a.sub, a.sub]) :
'V' is not a square numeric matrix
Also some, slightly different issues with data.table methodology.