set.seed(12345)
RaRb_tibble<-tibble(date=as.Date(as.yearmon("2009-01-01")+seq(1/12,3,1/12),frac=1),
             Ra=rnorm(3*12,0.06/12,.01),
             Rb=rnorm(3*12,0.055/12,.01))


#current tidyquant design
RaRb_tibble %>%
  tq_performance(Ra = Ra, Rb = Rb, performance_fun = table.CAPM)

#It must be tidy to do common plots
RaRb_tidy<-RaRb_tibble %>% 
  gather(asset,return,-date) %>% 
  group_by(asset) %>% 
  mutate(wealth.index=cumprod(1+return))

ggplot(RaRb_tidy,aes(x=date,y=wealth.index,color=asset))+geom_line()

# make RaRb helper function

#set what we want to pull from the long-style data frame
#match asset symbols to their benchmark symbols
RaRb_names<-tibble(Ra_name=c('AGTHX','FDEGX'),
                   Rb_name=c('SPX','SPX'))

#Rf could be a list matching number of rows in the RaRb_names table if 
# we are looking at assets in more than one currency,
# otherwise a single name value.
Rf_names<-'LD12TRUU' 

#names of the relevant columns in the data frame                   
name_col<-'symbol'
return_col<- 'return'

#the actual helper function
make_RaRbRf<-function(x,name_col,return_col,RaRb_names,Rf_names=NULL) {
  #function to take a list of portfolios/funds/stocks and 
  # merge with a list of benchmarks and, optionally, risk-free rate.
  # no error checking.
  #I am looping rather than applying. Shrug.
  #I really hate the squirrelly way we have to pass variable column names to filter and select 
  RaRbRf<-tibble()
  for (n in 1:nrow(RaRb_names)) {
    Ra<-x %>% 
      ungroup() %>% 
      filter_(paste(name_col," == '",RaRb_names$Ra_name[n],"'",sep='')) %>% 
      select(date,asset=get(name_col),Ra=get(return_col))
    Rb<-x %>% 
      ungroup() %>% 
      filter_(paste(name_col," == '",RaRb_names$Rb_name[n],"'",sep='')) %>% 
      select(date=date,benchmark=get(name_col),Rb=get(return_col))
    if (!(is.null(Rf_names))){
      if (length(Rf_names)<nrow(RaRb_names)){  #unmatched vectors. use only first Rf rate
        Rf<-x %>% 
          ungroup() %>% 
          filter_(paste(name_col," == '",Rf_names[1],"'",sep='')) %>% 
          select(date=date,Rf_rate=get(name_col),Rf=get(return_col))
      } else{ #multiple Rf rates
        Rf<-x %>% 
          ungroup() %>% 
          filter_(paste(name_col," == '",Rf_names[n],"'",sep='')) %>% 
          select(date=date,Rf_rate=get(name_col),Rf=get(return_col))
        
      }
      RaRbRf<-Ra %>% 
        left_join(Rb,by='date') %>% 
        left_join(Rf,by='date') %>% 
        bind_rows(RaRbRf)
    } else{
      RaRbRf<-Ra %>% 
        left_join(Rb,by='date') %>% 
        bind_rows(RaRbRf)
    }
  }
  return (group_by(RaRbRf,asset))
} #END FUNCTION

# test it out
make_RaRbRf(blp_bdh_tq,name_col,return_col,RaRb_names,Rf_names)
#Source: local data frame [252 x 7]
#Groups: asset [2]
#         date asset            Ra benchmark          Rb  Rf_rate          Rf
#       <date> <chr>         <dbl>     <chr>       <dbl>    <chr>       <dbl>
#1  2007-01-31 FDEGX  2.956467e-02       SPX  0.01614987 LD12TRUU 0.004266667
#2  2007-02-28 FDEGX -2.517091e-06       SPX -0.01956115 LD12TRUU 0.004300000
#3  2007-03-31 FDEGX  1.007866e-03       SPX  0.01118683 LD12TRUU 0.004200000
#4  2007-04-30 FDEGX  5.135944e-02       SPX  0.04429756 LD12TRUU 0.004091667
#5  2007-05-31 FDEGX  3.831427e-02       SPX  0.03489320 LD12TRUU 0.003941667
#6  2007-06-30 FDEGX  1.752771e-02       SPX -0.01661234 LD12TRUU 0.004016667
#7  2007-07-31 FDEGX  1.541267e-02       SPX -0.03100609 LD12TRUU 0.004133333
#8  2007-08-31 FDEGX -4.464409e-03       SPX  0.01498840 LD12TRUU 0.003341667
#9  2007-09-30 FDEGX  6.143493e-02       SPX  0.03740037 LD12TRUU 0.003183333
#10 2007-10-31 FDEGX  6.041405e-02       SPX  0.01590713 LD12TRUU 0.003283333
## ... with 242 more rows

#without Rf
make_RaRbRf(blp_bdh_tq,name_col,return_col,RaRb_names)

# Example from github, with unnest() removed to keep as list column
x <- tibble(symbol = c("FB", "AMZN", "NFLX", "GOOGL")) %>%
     mutate(stock.prices = map(.x = symbol,
                               .f = ~ tq_get(.x, get = "stock.prices")))

# For each tibble in the nested tibble, perform the function runSD on the Ad column
x %>% mutate(stock.prices = stock.prices %>% map(~tq_mutate(data = .x,
                                                           ohlc_fun = Ad, 
                                                           mutate_fun = runSD)))

# What about an easier way?

# In the unnested form
y <- unnest(x)

# First group by the symbols
y <- group_by(y, symbol)

# dplyr mutate seems to know what to do here
y %>% mutate(sd = runSD(adjusted))

# I thought tq_mutate should work, but it doesn't
y %>% tq_mutate(ohlc_fun = Ad, mutate_fun = runSD)

# Some debugging results
debugonce(as_xts_)
y %>% tq_mutate(ohlc_fun = Ad, mutate_fun = runSD)
#Stepping through, it seems to fail during the call to 'xts::xts[,-1]' because of the added groups
#select_() will add the grouping back to the single column of dates as the first column. Now the ordering is out of whack when converting to xts

"
Adding missing grouping variables: `symbol`
Error in sum(x[beg:(n + beg - 1)]) : 
  invalid type (character) of argument
"

Warning message:
x = 'CBOE/VIX', get = 'quandl.datatable': Error: {"quandl_error":{"code":"QECx02","message":"The following datatable 'CBOE/VIX' does not exist."}}
 

debug: quandl.api.handl_errors(response)
List of 10
 $ url        : chr "https://www.quandl.com/api/v3/datasets/CBOE/VIX?transform=&collapse=&order=desc"
 $ status_code: int 200

set.seed(12345)
RaRf<-tibble(date=as.Date(as.yearmon("2009-01-01")+seq(1/12,3,1/12),frac=1),
       Ra=rnorm(3*12,.06/12,.01),
       Rf=rnorm(3*12,.02/12,.001))


RaRf_xts<-as_xts(RaRf,date_col = date)

#in tidyquant -------------------------
# vector for Rf NOT accepted
RaRf %>%
  tq_performance(Ra = Ra, Rf = Rf, performance_fun = SharpeRatio)

#Error in tq_performance_.tbl_df(data = data, Ra = lazyeval::expr_text(Ra),  : 
#object 'ret' not found
#In addition: Warning message:
#  In fun_performance(eval(parse(text = Ra)), ...) : object 'Rf' not found

#in PerformanceAnalytics -------------------------
# vector for Rf accepted
SharpeRatio(RaRf_xts$Ra,RaRF_xts$Rf)
                                       Ra
#StdDev Sharpe (Rf=0.2%, p=95%): 0.5956861
#VaR Sharpe (Rf=0.2%, p=95%):    0.6704678
#ES Sharpe (Rf=0.2%, p=95%):     0.4820222

> tq_get("AAPL", "key.ratios")
additional arguments ignored in warning()
[1] NA
Warning messages:
1: x = 'AAPL', get = 'stock.prices': Error in download.file(paste(yahoo.URL, "s=", Symbols.name, "&a=", from.m, : cannot open URL 'https://ichart.finance.yahoo.com/table.csv?s=AAPL&a=4&b=17&c=2005&d=4&e=17&f=2017&g=d&q=q&y=0&z=AAPL&x=.csv'
 
2: x = 'AAPL', get = 'key.ratios': Error in value[[3L]](cond): object 'key_ratios' not found

library(tidyquant)

CL_F1 = tq_get('CHRIS/CME_GC1', get = 'quandl')

ggplot(subset(CL_F1,date > '2016-01-01'),aes(x = date, y = settle)) +
  geom_line() +                  
  geom_ma(ma_fun = EMA, n = 126)

CL_F1_multi = tq_get(x = c('CHRIS/CME_GC1', 'CHRIS/CME_C10'),
               get = 'quandl')
CL_F1_multi_sorted <- CL_F1_multi %>%
    mutate(symbol = forcats::as_factor(symbol)) %>%
    arrange(symbol, date) %>%
    mutate(symbol = as.character(symbol))

> tq_index_options()
[1] "RUSSELL1000" "RUSSELL2000" "RUSSELL3000" "DOW"         "DOWGLOBAL"   "SP400"      
[7] "SP500"       "SP600"       "SP1000"     

> tq_index("DOW")
Getting holdings for DOW
# A tibble: 0 x 0
Warning message:
In tq_index("DOW") : Error at DOW during download. 
Error: NoSuchMethodError (Java): org.apache.poi.hssf.usermodel.HSSFWorkbook.getNumCellStyles()I

tq_index('SP500')
Getting data...

[1] NA
Warning message:
In value[[3L]](cond) :
  Could not access http://www.marketvolume.com/indexes_exchanges/sp500_components.asp?s=SPX&row=0. If problem persists, try setting `use_fallback = TRUE` to return the last dowloaded data set.

tq_get(c("AAPL", "GOOGL")

# A tibble: 0 x 2
# ... with 2 variables: symbol <chr>, stock.prices <list>
Warning messages:
1: x = 'AAPL', get = 'stock.prices': Error in charToDate(x): character string is not in a standard unambiguous format
 Removing AAPL.
2: x = 'GOOGL', get = 'stock.prices': Error in charToDate(x): character string is not in a standard unambiguous format
 Removing GOOGL.
3: In value[[3L]](cond) : Returning as nested data frame.

tq_get(tibble(symbol = c("AAPL", "GOOGL"))) 

R version 3.4.1 (2017-06-30)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.2 LTS

Matrix products: default
BLAS: /usr/lib/libblas/libblas.so.3.6.0
LAPACK: /usr/lib/lapack/liblapack.so.3.6.0

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C
 [9] LC_ADDRESS=C               LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base

other attached packages:
 [1] bindrcpp_0.2                  tidyquant_0.5.2
 [3] dplyr_0.7.2                   purrr_0.2.3
 [5] readr_1.1.1                   tidyr_0.6.3
 [7] tibble_1.3.3                  ggplot2_2.2.1
 [9] tidyverse_1.1.1               quantmod_0.4-10
[11] TTR_0.23-2                    PerformanceAnalytics_1.4.3541
[13] xts_0.10-0                    zoo_1.8-0
[15] lubridate_1.6.0

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.12     cellranger_1.1.0 compiler_3.4.1   plyr_1.8.4
 [5] bindr_0.1        forcats_0.2.0    tools_3.4.1      jsonlite_1.5
 [9] nlme_3.1-131     gtable_0.2.0     lattice_0.20-35  pkgconfig_2.0.1
[13] rlang_0.1.1      psych_1.7.5      curl_2.8.1       parallel_3.4.1
[17] haven_1.1.0      xml2_1.1.1       httr_1.2.1       stringr_1.2.0
[21] hms_0.3          grid_3.4.1       glue_1.1.1       R6_2.2.2
[25] Quandl_2.8.0     readxl_1.0.0     foreign_0.8-69   modelr_0.1.0
[29] reshape2_1.4.2   magrittr_1.5     scales_0.4.1     rvest_0.3.2
[33] assertthat_0.2.0 mnormt_1.5-5     colorspace_1.3-2 stringi_1.1.5
[37] lazyeval_0.2.0   munsell_0.4.3    broom_0.4.2

mean_tidyverse_downloads_w <- tidyverse_downloads %>%
    tq_transmute(
        select     = count,
        mutate_fun = apply.weekly, 
        FUN        = mean,
        na.rm      = TRUE,
        col_rename = "mean_count"
    )

#get sector prices
from <- today() - years(10)
sector_prices <- ticker %>% tq_get(get = "stock.prices", from = from, to = today())
sector_monthly_returns <- sector_prices %>% group_by(symbol) %>% tq_transmute(select=adjusted, periodReturn, period = "monthly", col_rename = "Rb") %>% ungroup()

sector_growth_monthly <-  sector_monthly_returns %>% group_by(symbol) %>%
    tq_portfolio(assets_col   = symbol, 
                 returns_col  = Rb, 
                 weights      = 1, 
                 col_rename   = "investment.growth",
                 wealth.index = TRUE) %>%
    mutate(investment.growth = investment.growth * 10000, symbol = rep(symbol, n()))

> tq_get("WIKI/FOOBAR", get = "stock.prices")
[1] NA
Warning message:
In value[[3L]](cond) :
  Error at WIKI/FOOBAR during call to get = 'stock.prices'.
> tq_get("FOO/BAR", get = "quandl.data.table")
[1] NA
Warning message:
In value[[3L]](cond) :
  Error at FOO/BAR during call to get = 'quandl.datatable'.

tech_stock  <- tq_get(c(“AAPL”, “GOOG”, “TWTR"), get = "stock.prices", from = "2006-01-01") 

Conflicts with tidy packages

    date stock         rtrn
  <date> <chr>        <dbl>

c("AAPL", "GOOG") %>%
    tq_get(get = "key.stats")
>>> Error in eval(substitute(expr), envir, enclos) : 
>>>   Can not automatically convert from character to integer in column "Last.Trade.Size".

tq_get_blpapi<-function(secs,get="bdh",...){
  if (!("bdh" %in% get)) {
    stop("only bdh is implemented")
  }
  Rblpapi::blpConnect() #must have a valid blp session running
  blp_bdh  <-Rblpapi::bdh(secs,...=...)
 #tidy what Bloomberg gives us.
  blp_bdh_tq<-bind_rows(blp_bdh,.id='symbol')%>%
    separate(symbol,c('symbol','sector')) %>%
    select(date,symbol,everything())%>%
    group_by(sector,symbol)
  return(blp_bdh_tq)
}

# ----------------------------------------------------------
# What a Rblpapi::bdh function might look like in tidyquant

#form of the bdh function
START_DATE=as.Date("2007-01-01")
secs = c('SPX Index','AGTHX Equity','FDEGX Equity','LD12TRUU Index')
#BDH_OPTIONS = c("periodicitySelection"="MONTHLY")
#BBG_bdh  <-Rblpapi::bdh(secs,
#                  fields=c('RETURN','PRICE'), # not valid fields 
#                  start.date = START_DATE,
#                  end.date=Sys.Date(),
#                  options=BDH_OPTIONS)


#create an object that looks like what bdh will return using only public sources
#get from FRED
tbills_3mo <- tq_get("DGS3MO", get = "economic.data")
#convert to monthly rate
risk_free_rate <- tbills_3mo %>% transmute(date,Rf=price/100)
risk_free_rate_monthly<-risk_free_rate %>% 
  tq_transmute(select = Rf, 
               mutate_fun = to.monthly,
               indexAt='lastof',
               col_rename="return") %>% 
  mutate(return=return/12)

funds  <- tq_get(c("^SP500TR",'AGTHX','FDEGX'), 
                 get = "stock.prices", 
                 from = "2007-01-01") %>% 
  group_by(symbol)
#convert to monthly returns
funds_monthly<-funds %>% 
  tq_transmute(select     = adjusted, 
               mutate_fun = periodReturn,
               indexAt = 'lastof',
               period     = "monthly", 
               col_rename = "return") #%>% 

funds_monthly


#simulate what Rblpapi::bdh() will return
blp_bdh<-list(
  
  `LD12TRUU Index`=risk_free_rate_monthly %>% 
    select(date,return) %>% 
    mutate(wealth=cumprod(1+return)) %>% 
    as.data.frame() ,

`SPX Index`=funds_monthly %>% 
  filter(symbol=="^SP500TR") %>% 
  ungroup() %>% 
  select(date,return) %>% 
  mutate(wealth=cumprod(1+return)) %>% 
  as.data.frame(),

`AGTHX Equity`=funds_monthly %>% 
  filter(symbol=='AGTHX') %>% 
  ungroup() %>% 
  select(date,return) %>% 
  mutate(wealth=cumprod(1+return)) %>% 
  as.data.frame(),

`FDEGX Equity`=funds_monthly %>% 
  filter(symbol=='FDEGX') %>% 
  ungroup() %>% 
  select(date,return) %>% 
  mutate(wealth=cumprod(1+return)) %>% 
  as.data.frame()
)

blp_bdh

#Covert what Rblpapi returns to something like what tq_get returns
blp_bdh_tq<-bind_rows(blp_bdh,.id='symbol')%>%
  separate(symbol,c('symbol','sector')) %>%
  select(date,symbol,everything())%>%
  group_by(sector,symbol)
blp_bdh_tq

#a prototype tq_get for Rblpapi. Embed tidy coversion routine from above
tq_get_blpapi<-function(secs,get="bdh",...){
  if (!("bdh" %in% get)) {
    stop("only bdh is implemented")
  }
  Rblpapi::blpConnect() #must have a valid blp session running
  blp_bdh  <-Rblpapi::bdh(secs,...=...)
  blp_bdh_tq<-bind_rows(blp_bdh,.id='symbol')%>%
    separate(symbol,c('symbol','sector')) %>%
    select(date,symbol,everything())%>%
    group_by(sector,symbol)
  return(blp_bdh_tq)
}

# Working BBG Data get. Won't work if no blp session is running. Skip to 'fake it' below.
# CAUTION: The order of the returned series may not be the same as order of the inputs
# CAUTION: There is no guarantee that the all securities will have values for the same dates.
opts = c("periodicitySelection"="MONTHLY")
fields=c('DAY_TO_DAY_TOT_RETURN_GROSS_DVDS',"LAST_PRICE")

funds_and_bm<-tq_get_blpapi(secs,
              fields=fields,
              options=opts,
              start.date=as.Date("2015-01-01"),
              end.date=Sys.Date())

#fake it if no blpapi
#not using actual BBG field names which I usually rename anyway
funds_and_bm<-blp_bdh_tq

#looks okay?
funds_and_bm %>% 
  summarize(Avg_Return=mean(return),n=n())
## A tibble: 4 x 4
## Groups:   sector [?]
##  sector   symbol    Avg_Return     n
#  <chr>    <chr>        <dbl> <int>
#1 Equity    AGTHX 7.340296e-03   126
#2 Equity    FDEGX 6.885127e-03   126
#3  Index LD12TRUU 1.058918   126
#4  Index      SPX 7.043102e-03   126

ggplot(funds_and_bm,aes(x=date,y=wealth,color=symbol))+geom_line()

#symbol  stock_price   financials
#AAPL    [tibble RxC]  [tibble RxC]

library(tidyquant)
library(xlsx)
stock_list <- read.xlsx(file = "foobar.xlsx", sheetIndex = 1, ) %>%
    as_tibble() %>%
    mutate(value = as.character(value))
stock_list

stock_list %>%
    tq_get(get = "key.ratios")

# A tibble: 763 × 3
# value           section               data
# <chr>             <chr>             <list>
#     1    EFX        Financials <tibble [150 × 5]>
#     2    EFX     Profitability <tibble [170 × 5]>
#     3    EFX            Growth <tibble [160 × 5]>
#     4    EFX         Cash Flow  <tibble [50 × 5]>
#     5    EFX  Financial Health <tibble [240 × 5]>
#     6    EFX Efficiency Ratios  <tibble [80 × 5]>
#     7    EFX  Valuation Ratios  <tibble [40 × 5]>
#     8    TRU        Financials <tibble [150 × 5]>
#     9    TRU     Profitability <tibble [170 × 5]>
#     10   TRU            Growth <tibble [160 × 5]>
#     # ... with 753 more rows
#     There were 15 warnings (use warnings() to see them)

> warnings()
# Warning messages:
#     1: In download.file(url[1], destfile = tmp, quiet = TRUE) :
#     cannot open URL 'http://financials.morningstar.com/finan/ajax/exportKR2CSV.html?&callback=?&t=XNAS:WAL&region=usa&culture=en-US&cur=&order=asc': HTTP status was '500 Internal Server Error'
# 2: In value[[3L]](cond) :
#     Error at WAL during call to get = 'key.ratios'. Removing WAL.
# 3: In download.file(url[1], destfile = tmp, quiet = TRUE) :
#     cannot open URL 'http://financials.morningstar.com/finan/ajax/exportKR2CSV.html?&callback=?&t=XNAS:MS&region=usa&culture=en-US&cur=&order=asc': HTTP status was '500 Internal Server Error'
# 4: In value[[3L]](cond) :
#     Error at MS during call to get = 'key.ratios'. Removing MS.
# 5: In value[[3L]](cond) :
#     Error at CG during call to get = 'key.ratios'. Removing CG.
# 6: In readLines(tmp) :
#     incomplete final line found on 'C:\Users\mdanc\AppData\Local\Temp\RtmpotdUjr\file2d746b9320c3'
# 7: In value[[3L]](cond) :
#     Error at VNTV during call to get = 'key.ratios'. Removing VNTV.
# 8: In value[[3L]](cond) :
#     Error at BKFS during call to get = 'key.ratios'. Removing BKFS.
# 9: In value[[3L]](cond) :
#     Error at RMAX during call to get = 'key.ratios'. Removing RMAX.
# 10: In value[[3L]](cond) :
#     Error at APAM during call to get = 'key.ratios'. Removing APAM.
# 11: All formats failed to parse. No formats found.
# 12: In download.file(url[1], destfile = tmp, quiet = TRUE) :
#     cannot open URL 'http://financials.morningstar.com/finan/ajax/exportKR2CSV.html?&callback=?&t=XNAS:FLT&region=usa&culture=en-US&cur=&order=asc': HTTP status was '500 Internal Server Error'
# 13: In value[[3L]](cond) :
#     Error at FLT during call to get = 'key.ratios'. Removing FLT.
# 14: In download.file(url[1], destfile = tmp, quiet = TRUE) :
#     cannot open URL 'http://financials.morningstar.com/finan/ajax/exportKR2CSV.html?&callback=?&t=XNAS:AL&region=usa&culture=en-US&cur=&order=asc': HTTP status was '500 Internal Server Error'
# 15: In value[[3L]](cond) :
#     Error at AL during call to get = 'key.ratios'. Removing AL.

> tq_index("SP500")
Getting data...

[1] NA
Warning message:
In value[[3L]](cond) :
  Could not access http://www.marketvolume.com/indexes_exchanges/sp500_components.asp?s=SPX&row=0. If problem persists, try setting `use_fallback = TRUE` to return the last dowloaded data set.

> tq_index("SP500", use_fallback = TRUE)
Using fallback dataset last downloaded 2017-01-19.
# A tibble: 501 × 2
   symbol                   company
    <chr>                     <chr>
1     MMM                        3M
2     ABT       ABBOTT LABORATORIES
3    ABBV                ABBVIE INC
4     ACN                 ACCENTURE
5    ATVI       ACTIVISION BLIZZARD
6     AYI             ACUITY BRANDS
7    ADBE             ADOBE SYSTEMS
8     AAP        ADVANCE AUTO PARTS
9     AET                     AETNA
10    AMG AFFILIATED MANAGERS GROUP
# ... with 491 more rows

> tq_get("AAPL")
[1] NA
Warning message:
x = 'AAPL', get = 'stock.prices': Error in download.file(paste(yahoo.URL, "s=", Symbols.name, "&a=", from.m, : cannot open URL 'https://ichart.finance.yahoo.com/table.csv?s=AAPL&a=0&b=01&c=2007&d=4&e=17&f=2017&g=d&q=q&y=0&z=AAPL&x=.csv'

> tq_get("WIKI/AAPL", get = "quandl", from = "2007-01-01", to = "2017-01-01")
# A tibble: 2,518 × 13
         date  open  high   low close    volume ex.dividend split.ratio adj.open adj.high  adj.low adj.close
       <date> <dbl> <dbl> <dbl> <dbl>     <dbl>       <dbl>       <dbl>    <dbl>    <dbl>    <dbl>     <dbl>
1  2007-01-03 86.29 86.58 81.90 83.80  44225700           0           1 11.13446 11.17188 10.56800  10.81316
2  2007-01-04 84.05 85.95 83.82 85.66  30259300           0           1 10.84542 11.09059 10.81575  11.05317
3  2007-01-05 85.77 86.20 84.40 85.05  29812200           0           1 11.06736 11.12285 10.89059  10.97446
4  2007-01-08 85.96 86.53 85.28 85.47  28468100           0           1 11.09188 11.16543 11.00414  11.02865
5  2007-01-09 86.45 92.98 85.15 92.57 119617800           0           1 11.15511 11.99771 10.98736  11.94480
6  2007-01-10 94.75 97.80 93.45 97.00 105460000           0           1 12.22610 12.61966 12.05836  12.51643
7  2007-01-11 95.94 96.78 95.10 95.80  51437600           0           1 12.37965 12.48804 12.27126  12.36159
8  2007-01-12 94.59 95.06 93.23 94.62  46881800           0           1 12.20546 12.26610 12.02997  12.20933
9  2007-01-16 95.68 97.25 95.45 97.10  44431300           0           1 12.34610 12.54869 12.31643  12.52934
10 2007-01-17 97.56 97.60 94.82 94.95  58795000           0           1 12.58869 12.59385 12.23513  12.25191
# ... with 2,508 more rows, and 1 more variables: adj.volume <dbl>
Warning message:
No Quandl API key detected. Limited to 50 anonymous calls per day. Set key with 'quandl_api_key()'. 

set.seed(12345)
Ra_tibble<-tibble(date=as.yearmon("2009-01-01")+seq(1/12,3,1/12),
             Ra=rnorm(3*12,.06/12,.01))

Ra_xts<-as_xts(Ra_tibble,date_col = date)

#in tidyquant -------------------------
# yearmon for date NOT accepted
Ra_tibble %>%
  tq_performance(Ra = Ra, Rf = 0.02/12, performance_fun = SharpeRatio)

#Error in get_col_name_date_or_date_time(data) : 
#No date or POSIXct column found in `data`.

#fix it - easy enough!
Ra_tibble %>% 
  mutate(date=as.Date(date,frac=1)) %>%
  tq_performance(Ra = Ra, Rf = 0.02/12, performance_fun = SharpeRatio)
# A tibble: 1 × 3
#`ESSharpe(Rf=0.2%,p=95%)` `StdDevSharpe(Rf=0.2%,p=95%)` `VaRSharpe(Rf=0.2%,p=95%)`
#*                     <dbl>                         <dbl>                      <dbl>
#  1                 0.6415755                     0.6305925                  0.8175275

#in PerformanceAnalytics -------------------------
# yearmon for date accepted
SharpeRatio(Ra_xts$Ra,Rf=0.02/12)
#                                    Ra
#StdDev Sharpe (Rf=0.2%, p=95%): 0.6305925
#VaR Sharpe (Rf=0.2%, p=95%):    0.8175275
#ES Sharpe (Rf=0.2%, p=95%):     0.6415755

Output created: report.html
Error in as.POSIXlt(x, tz = tz(x)) : 
  argument "x" absent, with no default
Calls: .Last -> message -> date -> date.default -> as.POSIXlt
Execution interrupted

    Error in as.POSIXlt(x, tz = tz(x)) :
      el argumento "x" está ausente, sin valor por omisión
    Fatal error: error during cleanup
    
    Error in as.POSIXlt(x, tz = tz(x)) :
      el argumento "x" está ausente, sin valor por omisión
    Fatal error: error during cleanup
    
    Error in as.POSIXlt(x, tz = tz(x)) :
      el argumento "x" está ausente, sin valor por omisión
    Fatal error: error during cleanup
......
....
...

## R version 3.4.1 (2017-06-30)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 16.04.3 LTS
## 
## Matrix products: default
## BLAS: /usr/lib/libblas/libblas.so.3.6.0
## LAPACK: /usr/lib/lapack/liblapack.so.3.6.0
## 
## locale:
##  [1] LC_CTYPE=es_ES.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=es_ES.UTF-8        LC_COLLATE=es_ES.UTF-8    
##  [5] LC_MONETARY=es_ES.UTF-8    LC_MESSAGES=es_ES.UTF-8   
##  [7] LC_PAPER=es_ES.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=es_ES.UTF-8 LC_IDENTIFICATION=C       
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## loaded via a namespace (and not attached):
##  [1] compiler_3.4.1  backports_1.0.5 magrittr_1.5    rprojroot_1.2  
##  [5] tools_3.4.1     htmltools_0.3.6 yaml_2.1.14     Rcpp_0.12.12   
##  [9] stringi_1.1.5   rmarkdown_1.6   knitr_1.17      stringr_1.2.0  
## [13] digest_0.6.12   evaluate_0.10.1