Index valuations

Undoubtedly people have noticed that there has been major performance discrepancies of the various indices this year. YTD, FT100 has risen 6.2%, FT250 by a monster 20.6%, and AIM 100 is down 1.9%. Where next for the indices?

I thought it would be useful to calculate median PERs for each index. Data was taken from Sharelock Holmes, and is subject to all hte tedious caveats.

For FT100, it’s 13.6.

For FT250, it’s 13.3 (excluding ITs)

For AIM, it’s 4.5. This figure shouldn’t cause too much excitement, though, as it’s a rather large collection of companies – much of which is probably uninvestable – so I wouldn’t impute too much meaning into it.

For the largest 100 AIM companies by market cap, the PER us 13.4,

In other words, everything is about neck-and-neck, with no clear-cut attractive universe. Indices look around fair value, too, so it’s anyone’s guess if the markets are going up or down for here.

So there we have it: anything could happen.

Here’s my R script which generated this:

tab <- read.csv(“~/Documents/StatsList.csv”, header= TRUE)
summary(tab)
tab <- tab[ , which(names(tab) %in% c(“EPIC”, “MarketCap”, “PER”, “FTSE_Index”))] summary(tab)

s <- subset(tab, tab$FTSE_Index == “FTSE100”)
s
v <- as.vector(s$PER)
median(v, na.rm=TRUE)

s <- subset(tab, tab$FTSE_Index == “FTSE250”)
s
v <- as.vector(s$PER)
median(v, na.rm=TRUE)

s <- subset(tab, tab$FTSE_Index == “AIM”)
o <- s[order(s$MarketCap),]
v <- as.vector(o$PER)
w <- rev(v)
w[0:100]
median(w[0:100], na.rm=TRUE)

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About mcturra2000

Computer programmer living in Scotland.
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