[R-SIG-Finance] Select best worst
Joshua Ulrich
jo@h@m@u|r|ch @end|ng |rom gm@||@com
Fri Jul 31 17:21:25 CEST 2020
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 <brian using braverock.com> 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]]
> >
> > _______________________________________________
> > R-SIG-Finance using r-project.org
> > 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.
>
> _______________________________________________
> R-SIG-Finance using r-project.org 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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