Select best worst

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Select best worst

Pedro páramo
Hi all,

I have differente stocks

AAcciona<- tq_get("ANA.MC",from = '2019-12-31',get = "stock.prices")
ACS<- tq_get("ACS.MC",from = '2019-12-31',get = "stock.prices")
Aena<- tq_get("AENA.MC",from = '2019-12-31',get = "stock.prices")
Amadeus<- tq_get("AMS.MC",from = '2019-12-31',get = "stock.prices")
ArcelorMittal<- tq_get("MTS.MC",from = '2019-12-31',get = "stock.prices")
BBVA<- tq_get("BBVA.MC",from = '2019-12-31',get = "stock.prices")
Sabadell<- tq_get("SAB.MC",from = '2019-12-31',get = "stock.prices")
Santander<- tq_get("SAN.MC",from = '2019-12-31',get = "stock.prices")
Bankinter<- tq_get("BKT.MC",from = '2019-12-31',get = "stock.prices")
  Indra<- tq_get("IDR.MC",from = '2019-12-31',get = "stock.prices")
And I have applied this code to know the year to date accumulated returns,
the thing is that I want to order them by the last observation (year to
date) and make a plot of the 3 best/worst (bigger/lower
accumulated returns).

¿Is there a way to compare and order the last observation of
STOCKcum_return of each stock and select the 3 top and 3 bottom so I can
plot like worst/best without going manually?

Many thanks in advance

Hope I can explain


Indra_daily_returns <- Indra %>%
  tq_transmute(select = adjusted,           # this specifies which column
to select
               mutate_fun = periodReturn,   # This specifies what to do
with that column
               period = "daily",      # This argument calculates Daily
returns
               col_rename = "idr_returns") # renames the column
Indra_cum_returns <- Indra_daily_returns %>%
  mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
function
  mutate(cumulative_returns = cr - 1)

AAcciona_daily_returns <- AAcciona %>%
  tq_transmute(select = adjusted,           # this specifies which column
to select
               mutate_fun = periodReturn,   # This specifies what to do
with that column
               period = "daily",      # This argument calculates Daily
returns
               col_rename = "idr_returns") # renames the column
AAcciona_cum_returns <- AAcciona_daily_returns %>%
  mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
function
  mutate(cumulative_returns = cr - 1)

ACS_daily_returns <- ACS %>%
  tq_transmute(select = adjusted,           # this specifies which column
to select
               mutate_fun = periodReturn,   # This specifies what to do
with that column
               period = "daily",      # This argument calculates Daily
returns
               col_rename = "idr_returns") # renames the column
ACS_cum_returns <- ACS_daily_returns %>%
  mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
function
  mutate(cumulative_returns = cr - 1)

AENA_daily_returns <- AENA %>%
  tq_transmute(select = adjusted,           # this specifies which column
to select
               mutate_fun = periodReturn,   # This specifies what to do
with that column
               period = "daily",      # This argument calculates Daily
returns
               col_rename = "idr_returns") # renames the column
Aena_cum_returns <- Aaena_daily_returns %>%
  mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
function
  mutate(cumulative_returns = cr - 1)

Amadeus_daily_returns <- Amadeus %>%
  tq_transmute(select = adjusted,           # this specifies which column
to select
               mutate_fun = periodReturn,   # This specifies what to do
with that column
               period = "daily",      # This argument calculates Daily
returns
               col_rename = "idr_returns") # renames the column
Amadeus_cum_returns <- Amadeus_daily_returns %>%
  mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
function
  mutate(cumulative_returns = cr - 1)

ArcerlorMittal_daily_returns <- ArcerlorMittal %>%
  tq_transmute(select = adjusted,           # this specifies which column
to select
               mutate_fun = periodReturn,   # This specifies what to do
with that column
               period = "daily",      # This argument calculates Daily
returns
               col_rename = "idr_returns") # renames the column
ArcerlorMittal_cum_returns <- ArcerlorMittal_daily_returns %>%
  mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
function
  mutate(cumulative_returns = cr - 1)

BBVA_daily_returns <- BBVA %>%
  tq_transmute(select = adjusted,           # this specifies which column
to select
               mutate_fun = periodReturn,   # This specifies what to do
with that column
               period = "daily",      # This argument calculates Daily
returns
               col_rename = "idr_returns") # renames the column
BBVA_cum_returns <- BBVA_daily_returns %>%
  mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
function
  mutate(cumulative_returns = cr - 1)


Sabadell_daily_returns <- Sabadell %>%
  tq_transmute(select = adjusted,           # this specifies which column
to select
               mutate_fun = periodReturn,   # This specifies what to do
with that column
               period = "daily",      # This argument calculates Daily
returns
               col_rename = "idr_returns") # renames the column
Sabadell_cum_returns <- Sabadell_daily_returns %>%
  mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
function
  mutate(cumulative_returns = cr - 1)

Santander_daily_returns <- Santander %>%
  tq_transmute(select = adjusted,           # this specifies which column
to select
               mutate_fun = periodReturn,   # This specifies what to do
with that column
               period = "daily",      # This argument calculates Daily
returns
               col_rename = "idr_returns") # renames the column
Santander_cum_returns <- Santander_daily_returns %>%
  mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
function
  mutate(cumulative_returns = cr - 1)


Bankinter_daily_returns <- Bankinter %>%
  tq_transmute(select = adjusted,           # this specifies which column
to select
               mutate_fun = periodReturn,   # This specifies what to do
with that column
               period = "daily",      # This argument calculates Daily
returns
               col_rename = "idr_returns") # renames the column
Bankinter_cum_returns <- Bankinter_daily_returns %>%
  mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
function
  mutate(cumulative_returns = cr - 1)

        [[alternative HTML version deleted]]

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Re: Select best worst

braverock
Try a *minimal* example...  

I'm not going to take the time to sort through your code, especially
with all the totally unnecessary mutates and pipes.


cret <- rnorm(10) # dummy cumulative returns
names(cret) <- c('a','b','c','d','e','f','g','h','i','j')
sort(cret)

You should be able to easily use this to get the order of the columns
that you want.

Regards,

Brian


--
Brian G. Peterson
ph: +1.773.459.4973
im: bgpbraverock

On Wed, 2020-07-29 at 15:37 +0200, Pedro páramo wrote:

> Hi all,
>
> I have differente stocks
>
> AAcciona<- tq_get("ANA.MC",from = '2019-12-31',get = "stock.prices")
> ACS<- tq_get("ACS.MC",from = '2019-12-31',get = "stock.prices")
> Aena<- tq_get("AENA.MC",from = '2019-12-31',get = "stock.prices")
> Amadeus<- tq_get("AMS.MC",from = '2019-12-31',get = "stock.prices")
> ArcelorMittal<- tq_get("MTS.MC",from = '2019-12-31',get =
> "stock.prices")
> BBVA<- tq_get("BBVA.MC",from = '2019-12-31',get = "stock.prices")
> Sabadell<- tq_get("SAB.MC",from = '2019-12-31',get = "stock.prices")
> Santander<- tq_get("SAN.MC",from = '2019-12-31',get = "stock.prices")
> Bankinter<- tq_get("BKT.MC",from = '2019-12-31',get = "stock.prices")
>   Indra<- tq_get("IDR.MC",from = '2019-12-31',get = "stock.prices")
> And I have applied this code to know the year to date accumulated
> returns,
> the thing is that I want to order them by the last observation (year
> to
> date) and make a plot of the 3 best/worst (bigger/lower
> accumulated returns).
>
> ¿Is there a way to compare and order the last observation of
> STOCKcum_return of each stock and select the 3 top and 3 bottom so I
> can
> plot like worst/best without going manually?
>
> Many thanks in advance
>
> Hope I can explain
>
>
> Indra_daily_returns <- Indra %>%
>   tq_transmute(select = adjusted,           # this specifies which
> column
> to select
>                mutate_fun = periodReturn,   # This specifies what to
> do
> with that column
>                period = "daily",      # This argument calculates
> Daily
> returns
>                col_rename = "idr_returns") # renames the column
> Indra_cum_returns <- Indra_daily_returns %>%
>   mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
> function
>   mutate(cumulative_returns = cr - 1)
>
> AAcciona_daily_returns <- AAcciona %>%
>   tq_transmute(select = adjusted,           # this specifies which
> column
> to select
>                mutate_fun = periodReturn,   # This specifies what to
> do
> with that column
>                period = "daily",      # This argument calculates
> Daily
> returns
>                col_rename = "idr_returns") # renames the column
> AAcciona_cum_returns <- AAcciona_daily_returns %>%
>   mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
> function
>   mutate(cumulative_returns = cr - 1)
>
> ACS_daily_returns <- ACS %>%
>   tq_transmute(select = adjusted,           # this specifies which
> column
> to select
>                mutate_fun = periodReturn,   # This specifies what to
> do
> with that column
>                period = "daily",      # This argument calculates
> Daily
> returns
>                col_rename = "idr_returns") # renames the column
> ACS_cum_returns <- ACS_daily_returns %>%
>   mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
> function
>   mutate(cumulative_returns = cr - 1)
>
> AENA_daily_returns <- AENA %>%
>   tq_transmute(select = adjusted,           # this specifies which
> column
> to select
>                mutate_fun = periodReturn,   # This specifies what to
> do
> with that column
>                period = "daily",      # This argument calculates
> Daily
> returns
>                col_rename = "idr_returns") # renames the column
> Aena_cum_returns <- Aaena_daily_returns %>%
>   mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
> function
>   mutate(cumulative_returns = cr - 1)
>
> Amadeus_daily_returns <- Amadeus %>%
>   tq_transmute(select = adjusted,           # this specifies which
> column
> to select
>                mutate_fun = periodReturn,   # This specifies what to
> do
> with that column
>                period = "daily",      # This argument calculates
> Daily
> returns
>                col_rename = "idr_returns") # renames the column
> Amadeus_cum_returns <- Amadeus_daily_returns %>%
>   mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
> function
>   mutate(cumulative_returns = cr - 1)
>
> ArcerlorMittal_daily_returns <- ArcerlorMittal %>%
>   tq_transmute(select = adjusted,           # this specifies which
> column
> to select
>                mutate_fun = periodReturn,   # This specifies what to
> do
> with that column
>                period = "daily",      # This argument calculates
> Daily
> returns
>                col_rename = "idr_returns") # renames the column
> ArcerlorMittal_cum_returns <- ArcerlorMittal_daily_returns %>%
>   mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
> function
>   mutate(cumulative_returns = cr - 1)
>
> BBVA_daily_returns <- BBVA %>%
>   tq_transmute(select = adjusted,           # this specifies which
> column
> to select
>                mutate_fun = periodReturn,   # This specifies what to
> do
> with that column
>                period = "daily",      # This argument calculates
> Daily
> returns
>                col_rename = "idr_returns") # renames the column
> BBVA_cum_returns <- BBVA_daily_returns %>%
>   mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
> function
>   mutate(cumulative_returns = cr - 1)
>
>
> Sabadell_daily_returns <- Sabadell %>%
>   tq_transmute(select = adjusted,           # this specifies which
> column
> to select
>                mutate_fun = periodReturn,   # This specifies what to
> do
> with that column
>                period = "daily",      # This argument calculates
> Daily
> returns
>                col_rename = "idr_returns") # renames the column
> Sabadell_cum_returns <- Sabadell_daily_returns %>%
>   mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
> function
>   mutate(cumulative_returns = cr - 1)
>
> Santander_daily_returns <- Santander %>%
>   tq_transmute(select = adjusted,           # this specifies which
> column
> to select
>                mutate_fun = periodReturn,   # This specifies what to
> do
> with that column
>                period = "daily",      # This argument calculates
> Daily
> returns
>                col_rename = "idr_returns") # renames the column
> Santander_cum_returns <- Santander_daily_returns %>%
>   mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
> function
>   mutate(cumulative_returns = cr - 1)
>
>
> Bankinter_daily_returns <- Bankinter %>%
>   tq_transmute(select = adjusted,           # this specifies which
> column
> to select
>                mutate_fun = periodReturn,   # This specifies what to
> do
> with that column
>                period = "daily",      # This argument calculates
> Daily
> returns
>                col_rename = "idr_returns") # renames the column
> Bankinter_cum_returns <- Bankinter_daily_returns %>%
>   mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
> function
>   mutate(cumulative_returns = cr - 1)
>
> [[alternative HTML version deleted]]
>
> _______________________________________________
> [hidden email]
>  mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-finance
>
> -- Subscriber-posting only. If you want to post, subscribe first.
> -- Also note that this is not the r-help list where general R
> questions should go.
>
cret <- rnorm(10) # dummy data to represent your returns
names(cret) <- c('a','b','c','d','e','f','g','h','i','j')

sort(cret, decreasing=TRUE)

You can use your column names to easily get the order you want to rearrange things.

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Re: Select best worst

Joshua Ulrich
Note that this was also posted on R-help:
https://stat.ethz.ch/pipermail/r-help/2020-July/468145.html

I answered there, and I include my answer below for others' reference.

--------------------

I don't know how to do this in tidyquant, but here's how you can do it
with quantmod:

# all tickers
tk <- c("ANA.MC", "ACS.MC", "AENA.MC", "AMS.MC", "MTS.MC", "BBVA.MC", "SAB.MC",
  "SAN.MC", "BKT.MC", "CABK.MC", "CLNX.MC", "ENG.MC", "ENC.MC", "ELE.MC",
  "FER.MC", "GRF.MC", "IBE.MC", "ITX.MC", "COL.MC", "IAG.MC", "MAP.MC",
  "MEL.MC", "MRL.MC", "NTGY.MC", "REE.MC", "REP.MC", "SGRE.MC", "TEF.MC",
  "VIS.MC", "ACX.MC", "BKIA.MC", "CIE.MC", "MAS.MC", "ALM.MC", "IDR.MC")

# download them into an environment ('e')
require(quantmod)
getSymbols(tk, from = "2019-12-31", env = (e <- new.env()))

# extract adjusted close column
adj <- lapply(e, Ad)
# calculate daily returns from adjusted data,
# merge into a xts matrix, and fill NA with 0
ret <- do.call(merge, c(lapply(adj, dailyReturn), fill = 0))
# cumulative returns
cumret <- cumprod(1 + ret) - 1
# set names
colnames(cumret) <- names(adj)
last(cumret)
# calculate histogram for period-to-date returns
hist(drop(last(cumret)))

I'm not sure that's the histogram you're looking for, but I hope it
gives you a start toward a solution.

Best,
Josh


On Wed, Jul 29, 2020 at 9:34 AM Brian G. Peterson <[hidden email]> wrote:

>
> Try a *minimal* example...
>
> I'm not going to take the time to sort through your code, especially
> with all the totally unnecessary mutates and pipes.
>
>
> cret <- rnorm(10) # dummy cumulative returns
> names(cret) <- c('a','b','c','d','e','f','g','h','i','j')
> sort(cret)
>
> You should be able to easily use this to get the order of the columns
> that you want.
>
> Regards,
>
> Brian
>
>
> --
> Brian G. Peterson
> ph: +1.773.459.4973
> im: bgpbraverock
>
> On Wed, 2020-07-29 at 15:37 +0200, Pedro páramo wrote:
> > Hi all,
> >
> > I have differente stocks
> >
> > AAcciona<- tq_get("ANA.MC",from = '2019-12-31',get = "stock.prices")
> > ACS<- tq_get("ACS.MC",from = '2019-12-31',get = "stock.prices")
> > Aena<- tq_get("AENA.MC",from = '2019-12-31',get = "stock.prices")
> > Amadeus<- tq_get("AMS.MC",from = '2019-12-31',get = "stock.prices")
> > ArcelorMittal<- tq_get("MTS.MC",from = '2019-12-31',get =
> > "stock.prices")
> > BBVA<- tq_get("BBVA.MC",from = '2019-12-31',get = "stock.prices")
> > Sabadell<- tq_get("SAB.MC",from = '2019-12-31',get = "stock.prices")
> > Santander<- tq_get("SAN.MC",from = '2019-12-31',get = "stock.prices")
> > Bankinter<- tq_get("BKT.MC",from = '2019-12-31',get = "stock.prices")
> >   Indra<- tq_get("IDR.MC",from = '2019-12-31',get = "stock.prices")
> > And I have applied this code to know the year to date accumulated
> > returns,
> > the thing is that I want to order them by the last observation (year
> > to
> > date) and make a plot of the 3 best/worst (bigger/lower
> > accumulated returns).
> >
> > ¿Is there a way to compare and order the last observation of
> > STOCKcum_return of each stock and select the 3 top and 3 bottom so I
> > can
> > plot like worst/best without going manually?
> >
> > Many thanks in advance
> >
> > Hope I can explain
> >
> >
> > Indra_daily_returns <- Indra %>%
> >   tq_transmute(select = adjusted,           # this specifies which
> > column
> > to select
> >                mutate_fun = periodReturn,   # This specifies what to
> > do
> > with that column
> >                period = "daily",      # This argument calculates
> > Daily
> > returns
> >                col_rename = "idr_returns") # renames the column
> > Indra_cum_returns <- Indra_daily_returns %>%
> >   mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
> > function
> >   mutate(cumulative_returns = cr - 1)
> >
> > AAcciona_daily_returns <- AAcciona %>%
> >   tq_transmute(select = adjusted,           # this specifies which
> > column
> > to select
> >                mutate_fun = periodReturn,   # This specifies what to
> > do
> > with that column
> >                period = "daily",      # This argument calculates
> > Daily
> > returns
> >                col_rename = "idr_returns") # renames the column
> > AAcciona_cum_returns <- AAcciona_daily_returns %>%
> >   mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
> > function
> >   mutate(cumulative_returns = cr - 1)
> >
> > ACS_daily_returns <- ACS %>%
> >   tq_transmute(select = adjusted,           # this specifies which
> > column
> > to select
> >                mutate_fun = periodReturn,   # This specifies what to
> > do
> > with that column
> >                period = "daily",      # This argument calculates
> > Daily
> > returns
> >                col_rename = "idr_returns") # renames the column
> > ACS_cum_returns <- ACS_daily_returns %>%
> >   mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
> > function
> >   mutate(cumulative_returns = cr - 1)
> >
> > AENA_daily_returns <- AENA %>%
> >   tq_transmute(select = adjusted,           # this specifies which
> > column
> > to select
> >                mutate_fun = periodReturn,   # This specifies what to
> > do
> > with that column
> >                period = "daily",      # This argument calculates
> > Daily
> > returns
> >                col_rename = "idr_returns") # renames the column
> > Aena_cum_returns <- Aaena_daily_returns %>%
> >   mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
> > function
> >   mutate(cumulative_returns = cr - 1)
> >
> > Amadeus_daily_returns <- Amadeus %>%
> >   tq_transmute(select = adjusted,           # this specifies which
> > column
> > to select
> >                mutate_fun = periodReturn,   # This specifies what to
> > do
> > with that column
> >                period = "daily",      # This argument calculates
> > Daily
> > returns
> >                col_rename = "idr_returns") # renames the column
> > Amadeus_cum_returns <- Amadeus_daily_returns %>%
> >   mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
> > function
> >   mutate(cumulative_returns = cr - 1)
> >
> > ArcerlorMittal_daily_returns <- ArcerlorMittal %>%
> >   tq_transmute(select = adjusted,           # this specifies which
> > column
> > to select
> >                mutate_fun = periodReturn,   # This specifies what to
> > do
> > with that column
> >                period = "daily",      # This argument calculates
> > Daily
> > returns
> >                col_rename = "idr_returns") # renames the column
> > ArcerlorMittal_cum_returns <- ArcerlorMittal_daily_returns %>%
> >   mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
> > function
> >   mutate(cumulative_returns = cr - 1)
> >
> > BBVA_daily_returns <- BBVA %>%
> >   tq_transmute(select = adjusted,           # this specifies which
> > column
> > to select
> >                mutate_fun = periodReturn,   # This specifies what to
> > do
> > with that column
> >                period = "daily",      # This argument calculates
> > Daily
> > returns
> >                col_rename = "idr_returns") # renames the column
> > BBVA_cum_returns <- BBVA_daily_returns %>%
> >   mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
> > function
> >   mutate(cumulative_returns = cr - 1)
> >
> >
> > Sabadell_daily_returns <- Sabadell %>%
> >   tq_transmute(select = adjusted,           # this specifies which
> > column
> > to select
> >                mutate_fun = periodReturn,   # This specifies what to
> > do
> > with that column
> >                period = "daily",      # This argument calculates
> > Daily
> > returns
> >                col_rename = "idr_returns") # renames the column
> > Sabadell_cum_returns <- Sabadell_daily_returns %>%
> >   mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
> > function
> >   mutate(cumulative_returns = cr - 1)
> >
> > Santander_daily_returns <- Santander %>%
> >   tq_transmute(select = adjusted,           # this specifies which
> > column
> > to select
> >                mutate_fun = periodReturn,   # This specifies what to
> > do
> > with that column
> >                period = "daily",      # This argument calculates
> > Daily
> > returns
> >                col_rename = "idr_returns") # renames the column
> > Santander_cum_returns <- Santander_daily_returns %>%
> >   mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
> > function
> >   mutate(cumulative_returns = cr - 1)
> >
> >
> > Bankinter_daily_returns <- Bankinter %>%
> >   tq_transmute(select = adjusted,           # this specifies which
> > column
> > to select
> >                mutate_fun = periodReturn,   # This specifies what to
> > do
> > with that column
> >                period = "daily",      # This argument calculates
> > Daily
> > returns
> >                col_rename = "idr_returns") # renames the column
> > Bankinter_cum_returns <- Bankinter_daily_returns %>%
> >   mutate(cr = cumprod(1 + idr_returns)) %>%      # using the cumprod
> > function
> >   mutate(cumulative_returns = cr - 1)
> >
> >       [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > [hidden email]
> >  mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-sig-finance
> >
> > -- Subscriber-posting only. If you want to post, subscribe first.
> > -- Also note that this is not the r-help list where general R
> > questions should go.
> >
> cret <- rnorm(10) # dummy data to represent your returns
> names(cret) <- c('a','b','c','d','e','f','g','h','i','j')
>
> sort(cret, decreasing=TRUE)
>
> You can use your column names to easily get the order you want to rearrange things.
>
> _______________________________________________
> [hidden email] mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-finance
> -- Subscriber-posting only. If you want to post, subscribe first.
> -- Also note that this is not the r-help list where general R questions should go.



--
Joshua Ulrich  |  about.me/joshuaulrich
FOSS Trading  |  www.fosstrading.com

_______________________________________________
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