2

I have a dataframe that has a column for time, symbol, price, volatility. I use this dataframe to run a first pass OLS regression using dummy variables for the symbol

fit <- lm(volatility~factor(symbol) + 0

Then I want to use the coefficients from that regression in a second pass regression, so I save the coeffiecients of the regression to reuse and then I want to use that to scale volatility

scale <- summary(fit)$coefficients[,1]
yscale <- volatility/scale
fit2 <- lm(yscale~factor(time) + factor(symbol)*factor(time) + 0

The problem that I am having is that I want to use the factor coefficients that are applicable to each symbol. So in the original dataframe I want to divide the volatility by the coeffiecient that matches its symbol. So, if I have symbols, DDX, CTY, LOL then I want to divide DDX's volatility by the coefficient with factor DDX from the regression then do the same for CTY and LOL. Also, I need to figure out how to do the product in the second fit2 coefficient.

samooch
  • 81
  • 1
  • 1
  • 5

1 Answers1

1

You should provide a reproducible example to get an exact answers. Here some data:

dat <- data.frame(volatility= rnorm(30),
                  symbol = sample(c('DDX', 'CTY', 'LOL'),30,rep=TRUE))
fit <- lm(volatility~factor(symbol) + 0,data=dat)
mm <- coef(fit)
names(mm) <- gsub('factor\\(symbol\\)','',names(mm))

I transform the names to get a pretty names that can be used later :

   CTY        DDX        LOL 
 -0.1991273  0.1331980 -0.1567511

Then using transform , I divide each volatility with the corresponding coefficients:

transform(dat,vol.scale = volatility/mm[symbol],coef = mm[symbol])
      volatility symbol    vol.scale       coef
1  -0.592306253    DDX  -4.44680974  0.1331980
2   1.143486046    DDX   8.58485769  0.1331980
3  -0.693694139    LOL   4.42544868 -0.1567511
4  -0.166050131    LOL   1.05932325 -0.1567511
5   1.381900588    CTY  -6.93978353 -0.1991273
..............................
agstudy
  • 119,832
  • 17
  • 199
  • 261
  • thanks so much, that works well. I now have to go read a little on the transform statement to see how to use it better – samooch Jun 26 '13 at 01:13
  • @user2521266 You are welcome. it is similar to `with` ...Note you should its result like `dat <- transform(...)` to get effective change... – agstudy Jun 26 '13 at 01:16
  • ok @agstudy now I need to do the second regression. Both factor(symbol) and factor(time) will be treated as dummy variables in the regression so how do I get lm to evaluate them as a product for that second coefficient? if I try to combine them beforehand, the multiplication doesn't work as '*' is not a function for factors and if I do it in lm then the product doesn't work as that is more for effects I believe. – samooch Jun 26 '13 at 19:54