[R-SIG-Finance] Quantile Regression-Fit Stock data

[Dirk Eddelbuettel]

On 4 December 2010 at 09:28, Ronald McEwan wrote:
| I am new to R 

Well, welcome!   But one piece of advice: you cross-posted at StackOverflow
and here. Cross-posting is seen as distasteful. Don't do it.

| and I am trying to reproduce some of my Excel models in R. In this 
| project I am trying to perform a Quantile Regression on two Securities. I am not 
| able to get the rq() function to read the stock data I retrieve. From what I 
| have read so far I think I have to provide a definition for the data to enable 
| rq() to recognize it. I have not had success with this so far. I would 
| appreciate advice on how to define the stock market data in a way that the 
| function will recognize the data as a valid input. This is what I have so far.

As I told you in an answer on SO which you chose to ignore so far, you also
seem to regress _prices_ on _prices_. I gave you the Granger and Newbold
reference on spurious regression that predates unit roots, cointegrations and
all that -- don't work in prices, work in returns.

Cheers, Dirk

| Thanks,
| Regards,
| Ron McEwan
| 
| 
| # Quantile Regression - Fit Stock data
| 
| # Get Library
| 
| library(quantmod)
| library(quantreg)
| 
| # Get Stock Data
| 
| stk1 <- getSymbols("DD",  from="2009-12-31", auto.assign=FALSE)
| stk2 <- getSymbols("GE",  from="2009-12-31", auto.assign=FALSE)
| 
| # perform quantile regression procedures
| 
| #median (l1) regression  fit for the stock data.
| 
| rq(stk1 ~ stk2,.5) 
| 
| #the 1st quartile, 
|   
| rq(stk1 ~ stk2,.25)  
| 
| #note that 8 of the 21 points lie exactly on this plane in 4-space! 
| #this returns the full rq process
| 
| rq(stk1 ~ stk2, tau=-1)   
| 
| #ordinary sample median --no rank inversion ci
| 
| rq(rnorm(50) ~ 1, ci=FALSE)    
| 
| #weighted sample median 
| 
| rq(rnorm(50) ~ 1, weights=runif(50),ci=FALSE)  
| 
| 
| 
|       
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| 
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-- 
Dirk Eddelbuettel | edd at debian.org | http://dirk.eddelbuettel.com