Put your data in a real time series (xts) object and use the CAPM.*
functions from the PerformanceAnalytics package.
MW
On Tue, Jun 4, 2013 at 10:15 AM, Katherine Gobin
wrote:
> Dear R forum
>
> I have a dataframe (of prices) as given below -
>
> dat
> = data.frame(company = rep(c("A", "B", "C", "D", "index"), each = 5),
> prices = c(runif(5, 10, 12), runif(5, 108, 112), runif(5, 500, 510),
> runif(5, 40, 50), runif(5, 1000, 1020)))
>
>company prices
> 1A 10.61727
> 2A 10.51892
> 3A 11.80495
> 4A 11.15243
> 5A 10.77543
> 6B 111.23817
> 7B 109.19825
> 8B
> 108.80053
> 9B 110.79876
> 10 B 108.84385
> 11 C 504.71801
> 12 C 504.11778
> 13 C 502.89416
> 14 C 500.65996
> 15 C 502.26748
> 16 D 42.35901
> 17 D 43.71947
> 18 D 46.46092
> 19 D 43.62220
> 20 D 48.47480
> 21 index 1017.24476
> 22 index 1002.88139
> 23 index 1005.16148
> 24 index 1014.54480
> 25 index 1014.12103
>
> I need to find the beta
> of A, B, C and D w.r.t index.
>
> Beta between two variables X and Y (where Y is dependent) is given by,
>
> beta = coef(lm(Y ~ X))[2]
>
> Any guidance is appreciated.
>
> With regards
>
> Katherine
> [[alternative HTML version deleted]]
>
>
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