hw08

con = gzcon(url('http://www.systematicportfolio.com/sit.gz', 'rb'))
source(con)
close(con)

load.packages('quantmod')

## Warning: package 'quantmod' was built under R version 3.5.3

## Warning: package 'xts' was built under R version 3.5.3

## Warning: package 'zoo' was built under R version 3.5.3

## 
## Attaching package: 'zoo'

## The following objects are masked from 'package:base':
## 
##     as.Date, as.Date.numeric

## Warning: package 'TTR' was built under R version 3.5.3

## 
## Attaching package: 'TTR'

## The following object is masked _by_ '.GlobalEnv':
## 
##     DVI

## Version 0.4-0 included new data defaults. See ?getSymbols.

讀取etf4_xts_all的資料，有0050、0056、006205、00646四筆資料，並且去掉NA值。

etf4.all<-readRDS("D:/gitest/gitest01/0408/etf4_xts_all")
head(etf4.all)

##             0050  0056 006205 00646
## 2009-01-05 34.30 14.00     NA    NA
## 2009-01-06 34.21 14.02     NA    NA
## 2009-01-07 34.59 14.28     NA    NA
## 2009-01-08 33.21 13.86     NA    NA
## 2009-01-09 32.32 13.61     NA    NA
## 2009-01-10 31.91 13.55     NA    NA

str(etf4.all)

## An 'xts' object on 2009-01-05/2018-12-28 containing:
##   Data: num [1:2474, 1:4] 34.3 34.2 34.6 33.2 32.3 ...
##  - attr(*, "dimnames")=List of 2
##   ..$ : NULL
##   ..$ : chr [1:4] "0050" "0056" "006205" "00646"
##   Indexed by objects of class: [Date] TZ: UTC
##   xts Attributes:  
##  NULL

etf4.all.1<-etf4.all[complete.cases(etf4.all),]
head(etf4.all.1)

##             0050  0056 006205 00646
## 2015-12-14 59.35 21.06  30.98 19.54
## 2015-12-15 59.59 21.25  31.66 19.70
## 2015-12-16 60.11 21.50  31.67 19.80
## 2015-12-17 60.78 21.76  32.06 20.05
## 2015-12-18 60.78 21.97  32.23 19.87
## 2015-12-21 60.31 21.99  32.62 19.64

tail(etf4.all.1)

##             0050  0056 006205 00646
## 2018-12-22 74.75 24.15  25.08 22.93
## 2018-12-24 74.67 24.16  25.25 22.72
## 2018-12-25 73.57 23.90  24.90 22.51
## 2018-12-26 73.87 23.83  25.16 22.13
## 2018-12-27 74.81 23.96  25.30 22.95
## 2018-12-28 75.21 23.92  25.24 23.16

0050

讀取0050的資料。

library(xts)
data1<-new.env()
data1$prices<-etf4.all.1$'0050'
prices<-data1$prices

sma50<-SMA(prices, 50)
head(sma50, 51)

##                SMA
## 2015-12-14      NA
## 2015-12-15      NA
## 2015-12-16      NA
## 2015-12-17      NA
## 2015-12-18      NA
## 2015-12-21      NA
## 2015-12-22      NA
## 2015-12-23      NA
## 2015-12-24      NA
## 2015-12-25      NA
## 2015-12-28      NA
## 2015-12-29      NA
## 2015-12-30      NA
## 2015-12-31      NA
## 2016-01-04      NA
## 2016-01-05      NA
## 2016-01-06      NA
## 2016-01-07      NA
## 2016-01-08      NA
## 2016-01-11      NA
## 2016-01-12      NA
## 2016-01-13      NA
## 2016-01-14      NA
## 2016-01-15      NA
## 2016-01-18      NA
## 2016-01-19      NA
## 2016-01-20      NA
## 2016-01-21      NA
## 2016-01-22      NA
## 2016-01-25      NA
## 2016-01-26      NA
## 2016-01-27      NA
## 2016-01-28      NA
## 2016-01-29      NA
## 2016-01-30      NA
## 2016-02-01      NA
## 2016-02-02      NA
## 2016-02-03      NA
## 2016-02-15      NA
## 2016-02-16      NA
## 2016-02-17      NA
## 2016-02-18      NA
## 2016-02-19      NA
## 2016-02-22      NA
## 2016-02-23      NA
## 2016-02-24      NA
## 2016-02-25      NA
## 2016-02-26      NA
## 2016-03-01      NA
## 2016-03-02 59.2194
## 2016-03-03 59.2900

分別看日期、價錢。

bt.prep(data1, align='keep.all')
names(data1)

## [1] "prices"          "dates"           "weight"          "symbolnames"    
## [5] "execution.price"

data1$dates

##   [1] "2015-12-14" "2015-12-15" "2015-12-16" "2015-12-17" "2015-12-18"
##   [6] "2015-12-21" "2015-12-22" "2015-12-23" "2015-12-24" "2015-12-25"
##  [11] "2015-12-28" "2015-12-29" "2015-12-30" "2015-12-31" "2016-01-04"
##  [16] "2016-01-05" "2016-01-06" "2016-01-07" "2016-01-08" "2016-01-11"
##  [21] "2016-01-12" "2016-01-13" "2016-01-14" "2016-01-15" "2016-01-18"
##  [26] "2016-01-19" "2016-01-20" "2016-01-21" "2016-01-22" "2016-01-25"
##  [31] "2016-01-26" "2016-01-27" "2016-01-28" "2016-01-29" "2016-01-30"
##  [36] "2016-02-01" "2016-02-02" "2016-02-03" "2016-02-15" "2016-02-16"
##  [41] "2016-02-17" "2016-02-18" "2016-02-19" "2016-02-22" "2016-02-23"
##  [46] "2016-02-24" "2016-02-25" "2016-02-26" "2016-03-01" "2016-03-02"
##  [51] "2016-03-03" "2016-03-04" "2016-03-07" "2016-03-08" "2016-03-09"
##  [56] "2016-03-10" "2016-03-11" "2016-03-14" "2016-03-15" "2016-03-16"
##  [61] "2016-03-17" "2016-03-18" "2016-03-21" "2016-03-22" "2016-03-23"
##  [66] "2016-03-24" "2016-03-25" "2016-03-28" "2016-03-29" "2016-03-30"
##  [71] "2016-03-31" "2016-04-01" "2016-04-06" "2016-04-07" "2016-04-08"
##  [76] "2016-04-11" "2016-04-12" "2016-04-13" "2016-04-14" "2016-04-15"
##  [81] "2016-04-18" "2016-04-19" "2016-04-20" "2016-04-21" "2016-04-22"
##  [86] "2016-04-25" "2016-04-26" "2016-04-27" "2016-04-28" "2016-04-29"
##  [91] "2016-05-03" "2016-05-04" "2016-05-05" "2016-05-06" "2016-05-09"
##  [96] "2016-05-10" "2016-05-11" "2016-05-12" "2016-05-13" "2016-05-16"
## [101] "2016-05-17" "2016-05-18" "2016-05-19" "2016-05-20" "2016-05-23"
## [106] "2016-05-24" "2016-05-25" "2016-05-26" "2016-05-27" "2016-05-30"
## [111] "2016-05-31" "2016-06-01" "2016-06-02" "2016-06-03" "2016-06-04"
## [116] "2016-06-06" "2016-06-07" "2016-06-08" "2016-06-13" "2016-06-14"
## [121] "2016-06-15" "2016-06-16" "2016-06-17" "2016-06-20" "2016-06-21"
## [126] "2016-06-22" "2016-06-23" "2016-06-24" "2016-06-27" "2016-06-28"
## [131] "2016-06-29" "2016-06-30" "2016-07-01" "2016-07-04" "2016-07-05"
## [136] "2016-07-06" "2016-07-07" "2016-07-11" "2016-07-12" "2016-07-13"
## [141] "2016-07-14" "2016-07-15" "2016-07-18" "2016-07-19" "2016-07-20"
## [146] "2016-07-21" "2016-07-22" "2016-07-25" "2016-07-26" "2016-07-27"
## [151] "2016-07-28" "2016-07-29" "2016-08-01" "2016-08-02" "2016-08-03"
## [156] "2016-08-04" "2016-08-05" "2016-08-08" "2016-08-09" "2016-08-10"
## [161] "2016-08-11" "2016-08-12" "2016-08-15" "2016-08-16" "2016-08-17"
## [166] "2016-08-18" "2016-08-19" "2016-08-22" "2016-08-23" "2016-08-24"
## [171] "2016-08-25" "2016-08-26" "2016-08-29" "2016-08-30" "2016-08-31"
## [176] "2016-09-01" "2016-09-02" "2016-09-05" "2016-09-06" "2016-09-07"
## [181] "2016-09-08" "2016-09-09" "2016-09-10" "2016-09-12" "2016-09-13"
## [186] "2016-09-14" "2016-09-19" "2016-09-20" "2016-09-21" "2016-09-22"
## [191] "2016-09-23" "2016-09-26" "2016-09-29" "2016-09-30" "2016-10-03"
## [196] "2016-10-04" "2016-10-05" "2016-10-06" "2016-10-07" "2016-10-11"
## [201] "2016-10-12" "2016-10-13" "2016-10-14" "2016-10-17" "2016-10-18"
## [206] "2016-10-19" "2016-10-20" "2016-10-21" "2016-10-24" "2016-10-25"
## [211] "2016-10-26" "2016-10-27" "2016-10-28" "2016-10-31" "2016-11-01"
## [216] "2016-11-02" "2016-11-03" "2016-11-04" "2016-11-07" "2016-11-08"
## [221] "2016-11-09" "2016-11-10" "2016-11-11" "2016-11-14" "2016-11-15"
## [226] "2016-11-16" "2016-11-17" "2016-11-18" "2016-11-21" "2016-11-22"
## [231] "2016-11-23" "2016-11-24" "2016-11-25" "2016-11-28" "2016-11-29"
## [236] "2016-11-30" "2016-12-01" "2016-12-02" "2016-12-05" "2016-12-06"
## [241] "2016-12-07" "2016-12-08" "2016-12-09" "2016-12-12" "2016-12-13"
## [246] "2016-12-14" "2016-12-15" "2016-12-16" "2016-12-19" "2016-12-20"
## [251] "2016-12-21" "2016-12-22" "2016-12-23" "2016-12-26" "2016-12-27"
## [256] "2016-12-28" "2016-12-29" "2016-12-30" "2017-01-03" "2017-01-04"
## [261] "2017-01-05" "2017-01-06" "2017-01-09" "2017-01-10" "2017-01-11"
## [266] "2017-01-12" "2017-01-13" "2017-01-16" "2017-01-17" "2017-01-18"
## [271] "2017-01-19" "2017-01-20" "2017-01-23" "2017-01-24" "2017-02-02"
## [276] "2017-02-03" "2017-02-06" "2017-02-07" "2017-02-08" "2017-02-09"
## [281] "2017-02-10" "2017-02-13" "2017-02-14" "2017-02-15" "2017-02-16"
## [286] "2017-02-17" "2017-02-18" "2017-02-20" "2017-02-21" "2017-02-22"
## [291] "2017-02-23" "2017-02-24" "2017-03-01" "2017-03-02" "2017-03-03"
## [296] "2017-03-06" "2017-03-07" "2017-03-08" "2017-03-09" "2017-03-10"
## [301] "2017-03-13" "2017-03-14" "2017-03-15" "2017-03-16" "2017-03-17"
## [306] "2017-03-20" "2017-03-21" "2017-03-22" "2017-03-23" "2017-03-24"
## [311] "2017-03-27" "2017-03-28" "2017-03-29" "2017-03-30" "2017-03-31"
## [316] "2017-04-05" "2017-04-06" "2017-04-07" "2017-04-10" "2017-04-11"
## [321] "2017-04-12" "2017-04-13" "2017-04-14" "2017-04-17" "2017-04-18"
## [326] "2017-04-19" "2017-04-20" "2017-04-21" "2017-04-24" "2017-04-25"
## [331] "2017-04-26" "2017-04-27" "2017-04-28" "2017-05-02" "2017-05-03"
## [336] "2017-05-04" "2017-05-05" "2017-05-08" "2017-05-09" "2017-05-10"
## [341] "2017-05-11" "2017-05-12" "2017-05-15" "2017-05-16" "2017-05-17"
## [346] "2017-05-18" "2017-05-19" "2017-05-22" "2017-05-23" "2017-05-24"
## [351] "2017-05-25" "2017-05-26" "2017-05-31" "2017-06-01" "2017-06-02"
## [356] "2017-06-03" "2017-06-05" "2017-06-06" "2017-06-07" "2017-06-08"
## [361] "2017-06-09" "2017-06-12" "2017-06-13" "2017-06-14" "2017-06-15"
## [366] "2017-06-16" "2017-06-19" "2017-06-20" "2017-06-21" "2017-06-22"
## [371] "2017-06-23" "2017-06-26" "2017-06-27" "2017-06-28" "2017-06-29"
## [376] "2017-06-30" "2017-07-03" "2017-07-04" "2017-07-05" "2017-07-06"
## [381] "2017-07-07" "2017-07-10" "2017-07-11" "2017-07-12" "2017-07-13"
## [386] "2017-07-14" "2017-07-17" "2017-07-18" "2017-07-19" "2017-07-20"
## [391] "2017-07-21" "2017-07-24" "2017-07-25" "2017-07-26" "2017-07-27"
## [396] "2017-07-28" "2017-07-31" "2017-08-01" "2017-08-02" "2017-08-03"
## [401] "2017-08-04" "2017-08-07" "2017-08-08" "2017-08-09" "2017-08-10"
## [406] "2017-08-11" "2017-08-14" "2017-08-15" "2017-08-16" "2017-08-17"
## [411] "2017-08-18" "2017-08-21" "2017-08-22" "2017-08-23" "2017-08-24"
## [416] "2017-08-25" "2017-08-28" "2017-08-29" "2017-08-30" "2017-08-31"
## [421] "2017-09-01" "2017-09-04" "2017-09-05" "2017-09-06" "2017-09-07"
## [426] "2017-09-08" "2017-09-11" "2017-09-12" "2017-09-13" "2017-09-14"
## [431] "2017-09-15" "2017-09-18" "2017-09-19" "2017-09-20" "2017-09-21"
## [436] "2017-09-22" "2017-09-25" "2017-09-26" "2017-09-27" "2017-09-28"
## [441] "2017-09-29" "2017-09-30" "2017-10-02" "2017-10-03" "2017-10-05"
## [446] "2017-10-06" "2017-10-11" "2017-10-12" "2017-10-13" "2017-10-16"
## [451] "2017-10-17" "2017-10-18" "2017-10-19" "2017-10-20" "2017-10-23"
## [456] "2017-10-24" "2017-10-25" "2017-10-26" "2017-10-27" "2017-10-30"
## [461] "2017-10-31" "2017-11-01" "2017-11-02" "2017-11-03" "2017-11-06"
## [466] "2017-11-07" "2017-11-08" "2017-11-09" "2017-11-10" "2017-11-13"
## [471] "2017-11-14" "2017-11-15" "2017-11-16" "2017-11-17" "2017-11-20"
## [476] "2017-11-21" "2017-11-22" "2017-11-23" "2017-11-24" "2017-11-27"
## [481] "2017-11-28" "2017-11-29" "2017-11-30" "2017-12-01" "2017-12-04"
## [486] "2017-12-05" "2017-12-06" "2017-12-07" "2017-12-08" "2017-12-11"
## [491] "2017-12-12" "2017-12-13" "2017-12-14" "2017-12-15" "2017-12-18"
## [496] "2017-12-19" "2017-12-20" "2017-12-21" "2017-12-22" "2017-12-25"
## [501] "2017-12-26" "2017-12-27" "2017-12-28" "2017-12-29" "2018-01-02"
## [506] "2018-01-03" "2018-01-04" "2018-01-05" "2018-01-08" "2018-01-09"
## [511] "2018-01-10" "2018-01-11" "2018-01-12" "2018-01-15" "2018-01-16"
## [516] "2018-01-17" "2018-01-18" "2018-01-19" "2018-01-22" "2018-01-23"
## [521] "2018-01-24" "2018-01-25" "2018-01-26" "2018-01-29" "2018-01-30"
## [526] "2018-01-31" "2018-02-01" "2018-02-02" "2018-02-05" "2018-02-06"
## [531] "2018-02-07" "2018-02-08" "2018-02-09" "2018-02-12" "2018-02-21"
## [536] "2018-02-22" "2018-02-23" "2018-02-26" "2018-02-27" "2018-03-01"
## [541] "2018-03-02" "2018-03-05" "2018-03-06" "2018-03-07" "2018-03-08"
## [546] "2018-03-09" "2018-03-12" "2018-03-13" "2018-03-14" "2018-03-15"
## [551] "2018-03-16" "2018-03-19" "2018-03-20" "2018-03-21" "2018-03-22"
## [556] "2018-03-23" "2018-03-26" "2018-03-27" "2018-03-28" "2018-03-29"
## [561] "2018-03-30" "2018-03-31" "2018-04-02" "2018-04-03" "2018-04-09"
## [566] "2018-04-10" "2018-04-11" "2018-04-12" "2018-04-13" "2018-04-16"
## [571] "2018-04-17" "2018-04-18" "2018-04-19" "2018-04-20" "2018-04-23"
## [576] "2018-04-24" "2018-04-25" "2018-04-26" "2018-04-27" "2018-04-30"
## [581] "2018-05-02" "2018-05-03" "2018-05-04" "2018-05-07" "2018-05-08"
## [586] "2018-05-09" "2018-05-10" "2018-05-11" "2018-05-14" "2018-05-15"
## [591] "2018-05-16" "2018-05-17" "2018-05-18" "2018-05-21" "2018-05-22"
## [596] "2018-05-23" "2018-05-24" "2018-05-25" "2018-05-28" "2018-05-29"
## [601] "2018-05-30" "2018-05-31" "2018-06-01" "2018-06-04" "2018-06-05"
## [606] "2018-06-06" "2018-06-07" "2018-06-08" "2018-06-11" "2018-06-12"
## [611] "2018-06-13" "2018-06-14" "2018-06-15" "2018-06-19" "2018-06-20"
## [616] "2018-06-21" "2018-06-22" "2018-06-25" "2018-06-26" "2018-06-27"
## [621] "2018-06-28" "2018-06-29" "2018-07-02" "2018-07-03" "2018-07-04"
## [626] "2018-07-05" "2018-07-06" "2018-07-09" "2018-07-10" "2018-07-11"
## [631] "2018-07-12" "2018-07-13" "2018-07-16" "2018-07-17" "2018-07-18"
## [636] "2018-07-19" "2018-07-20" "2018-07-23" "2018-07-24" "2018-07-25"
## [641] "2018-07-26" "2018-07-27" "2018-07-30" "2018-07-31" "2018-08-01"
## [646] "2018-08-02" "2018-08-03" "2018-08-06" "2018-08-07" "2018-08-08"
## [651] "2018-08-09" "2018-08-10" "2018-08-13" "2018-08-14" "2018-08-15"
## [656] "2018-08-16" "2018-08-17" "2018-08-20" "2018-08-21" "2018-08-22"
## [661] "2018-08-23" "2018-08-24" "2018-08-27" "2018-08-28" "2018-08-29"
## [666] "2018-08-30" "2018-08-31" "2018-09-03" "2018-09-04" "2018-09-05"
## [671] "2018-09-06" "2018-09-07" "2018-09-10" "2018-09-11" "2018-09-12"
## [676] "2018-09-13" "2018-09-14" "2018-09-17" "2018-09-18" "2018-09-19"
## [681] "2018-09-20" "2018-09-21" "2018-09-25" "2018-09-26" "2018-09-27"
## [686] "2018-09-28" "2018-10-01" "2018-10-02" "2018-10-03" "2018-10-04"
## [691] "2018-10-05" "2018-10-08" "2018-10-09" "2018-10-11" "2018-10-12"
## [696] "2018-10-15" "2018-10-16" "2018-10-17" "2018-10-18" "2018-10-19"
## [701] "2018-10-22" "2018-10-23" "2018-10-24" "2018-10-25" "2018-10-26"
## [706] "2018-10-29" "2018-10-30" "2018-10-31" "2018-11-01" "2018-11-02"
## [711] "2018-11-05" "2018-11-06" "2018-11-07" "2018-11-08" "2018-11-09"
## [716] "2018-11-12" "2018-11-13" "2018-11-14" "2018-11-15" "2018-11-16"
## [721] "2018-11-19" "2018-11-20" "2018-11-21" "2018-11-22" "2018-11-23"
## [726] "2018-11-26" "2018-11-27" "2018-11-28" "2018-11-29" "2018-11-30"
## [731] "2018-12-03" "2018-12-04" "2018-12-05" "2018-12-06" "2018-12-07"
## [736] "2018-12-10" "2018-12-11" "2018-12-12" "2018-12-13" "2018-12-14"
## [741] "2018-12-17" "2018-12-18" "2018-12-19" "2018-12-20" "2018-12-21"
## [746] "2018-12-22" "2018-12-24" "2018-12-25" "2018-12-26" "2018-12-27"
## [751] "2018-12-28"

data1$prices

##            prices
## 2015-12-14     NA
## 2015-12-15     NA
## 2015-12-16     NA
## 2015-12-17     NA
## 2015-12-18     NA
## 2015-12-21     NA
## 2015-12-22     NA
## 2015-12-23     NA
## 2015-12-24     NA
## 2015-12-25     NA
## 2015-12-28     NA
## 2015-12-29     NA
## 2015-12-30     NA
## 2015-12-31     NA
## 2016-01-04     NA
## 2016-01-05     NA
## 2016-01-06     NA
## 2016-01-07     NA
## 2016-01-08     NA
## 2016-01-11     NA
## 2016-01-12     NA
## 2016-01-13     NA
## 2016-01-14     NA
## 2016-01-15     NA
## 2016-01-18     NA
## 2016-01-19     NA
## 2016-01-20     NA
## 2016-01-21     NA
## 2016-01-22     NA
## 2016-01-25     NA
## 2016-01-26     NA
## 2016-01-27     NA
## 2016-01-28     NA
## 2016-01-29     NA
## 2016-01-30     NA
## 2016-02-01     NA
## 2016-02-02     NA
## 2016-02-03     NA
## 2016-02-15     NA
## 2016-02-16     NA
## 2016-02-17     NA
## 2016-02-18     NA
## 2016-02-19     NA
## 2016-02-22     NA
## 2016-02-23     NA
## 2016-02-24     NA
## 2016-02-25     NA
## 2016-02-26     NA
## 2016-03-01     NA
## 2016-03-02     NA
## 2016-03-03     NA
## 2016-03-04     NA
## 2016-03-07     NA
## 2016-03-08     NA
## 2016-03-09     NA
## 2016-03-10     NA
## 2016-03-11     NA
## 2016-03-14     NA
## 2016-03-15     NA
## 2016-03-16     NA
## 2016-03-17     NA
## 2016-03-18     NA
## 2016-03-21     NA
## 2016-03-22     NA
## 2016-03-23     NA
## 2016-03-24     NA
## 2016-03-25     NA
## 2016-03-28     NA
## 2016-03-29     NA
## 2016-03-30     NA
## 2016-03-31     NA
## 2016-04-01     NA
## 2016-04-06     NA
## 2016-04-07     NA
## 2016-04-08     NA
## 2016-04-11     NA
## 2016-04-12     NA
## 2016-04-13     NA
## 2016-04-14     NA
## 2016-04-15     NA
## 2016-04-18     NA
## 2016-04-19     NA
## 2016-04-20     NA
## 2016-04-21     NA
## 2016-04-22     NA
## 2016-04-25     NA
## 2016-04-26     NA
## 2016-04-27     NA
## 2016-04-28     NA
## 2016-04-29     NA
## 2016-05-03     NA
## 2016-05-04     NA
## 2016-05-05     NA
## 2016-05-06     NA
## 2016-05-09     NA
## 2016-05-10     NA
## 2016-05-11     NA
## 2016-05-12     NA
## 2016-05-13     NA
## 2016-05-16     NA
## 2016-05-17     NA
## 2016-05-18     NA
## 2016-05-19     NA
## 2016-05-20     NA
## 2016-05-23     NA
## 2016-05-24     NA
## 2016-05-25     NA
## 2016-05-26     NA
## 2016-05-27     NA
## 2016-05-30     NA
## 2016-05-31     NA
## 2016-06-01     NA
## 2016-06-02     NA
## 2016-06-03     NA
## 2016-06-04     NA
## 2016-06-06     NA
## 2016-06-07     NA
## 2016-06-08     NA
## 2016-06-13     NA
## 2016-06-14     NA
## 2016-06-15     NA
## 2016-06-16     NA
## 2016-06-17     NA
## 2016-06-20     NA
## 2016-06-21     NA
## 2016-06-22     NA
## 2016-06-23     NA
## 2016-06-24     NA
## 2016-06-27     NA
## 2016-06-28     NA
## 2016-06-29     NA
## 2016-06-30     NA
## 2016-07-01     NA
## 2016-07-04     NA
## 2016-07-05     NA
## 2016-07-06     NA
## 2016-07-07     NA
## 2016-07-11     NA
## 2016-07-12     NA
## 2016-07-13     NA
## 2016-07-14     NA
## 2016-07-15     NA
## 2016-07-18     NA
## 2016-07-19     NA
## 2016-07-20     NA
## 2016-07-21     NA
## 2016-07-22     NA
## 2016-07-25     NA
## 2016-07-26     NA
## 2016-07-27     NA
## 2016-07-28     NA
## 2016-07-29     NA
## 2016-08-01     NA
## 2016-08-02     NA
## 2016-08-03     NA
## 2016-08-04     NA
## 2016-08-05     NA
## 2016-08-08     NA
## 2016-08-09     NA
## 2016-08-10     NA
## 2016-08-11     NA
## 2016-08-12     NA
## 2016-08-15     NA
## 2016-08-16     NA
## 2016-08-17     NA
## 2016-08-18     NA
## 2016-08-19     NA
## 2016-08-22     NA
## 2016-08-23     NA
## 2016-08-24     NA
## 2016-08-25     NA
## 2016-08-26     NA
## 2016-08-29     NA
## 2016-08-30     NA
## 2016-08-31     NA
## 2016-09-01     NA
## 2016-09-02     NA
## 2016-09-05     NA
## 2016-09-06     NA
## 2016-09-07     NA
## 2016-09-08     NA
## 2016-09-09     NA
## 2016-09-10     NA
## 2016-09-12     NA
## 2016-09-13     NA
## 2016-09-14     NA
## 2016-09-19     NA
## 2016-09-20     NA
## 2016-09-21     NA
## 2016-09-22     NA
## 2016-09-23     NA
## 2016-09-26     NA
## 2016-09-29     NA
## 2016-09-30     NA
## 2016-10-03     NA
## 2016-10-04     NA
## 2016-10-05     NA
## 2016-10-06     NA
## 2016-10-07     NA
## 2016-10-11     NA
## 2016-10-12     NA
## 2016-10-13     NA
## 2016-10-14     NA
## 2016-10-17     NA
## 2016-10-18     NA
## 2016-10-19     NA
## 2016-10-20     NA
## 2016-10-21     NA
## 2016-10-24     NA
## 2016-10-25     NA
## 2016-10-26     NA
## 2016-10-27     NA
## 2016-10-28     NA
## 2016-10-31     NA
## 2016-11-01     NA
## 2016-11-02     NA
## 2016-11-03     NA
## 2016-11-04     NA
## 2016-11-07     NA
## 2016-11-08     NA
## 2016-11-09     NA
## 2016-11-10     NA
## 2016-11-11     NA
## 2016-11-14     NA
## 2016-11-15     NA
## 2016-11-16     NA
## 2016-11-17     NA
## 2016-11-18     NA
## 2016-11-21     NA
## 2016-11-22     NA
## 2016-11-23     NA
## 2016-11-24     NA
## 2016-11-25     NA
## 2016-11-28     NA
## 2016-11-29     NA
## 2016-11-30     NA
## 2016-12-01     NA
## 2016-12-02     NA
## 2016-12-05     NA
## 2016-12-06     NA
## 2016-12-07     NA
## 2016-12-08     NA
## 2016-12-09     NA
## 2016-12-12     NA
## 2016-12-13     NA
## 2016-12-14     NA
## 2016-12-15     NA
## 2016-12-16     NA
## 2016-12-19     NA
## 2016-12-20     NA
## 2016-12-21     NA
## 2016-12-22     NA
## 2016-12-23     NA
## 2016-12-26     NA
## 2016-12-27     NA
## 2016-12-28     NA
## 2016-12-29     NA
## 2016-12-30     NA
## 2017-01-03     NA
## 2017-01-04     NA
## 2017-01-05     NA
## 2017-01-06     NA
## 2017-01-09     NA
## 2017-01-10     NA
## 2017-01-11     NA
## 2017-01-12     NA
## 2017-01-13     NA
## 2017-01-16     NA
## 2017-01-17     NA
## 2017-01-18     NA
## 2017-01-19     NA
## 2017-01-20     NA
## 2017-01-23     NA
## 2017-01-24     NA
## 2017-02-02     NA
## 2017-02-03     NA
## 2017-02-06     NA
## 2017-02-07     NA
## 2017-02-08     NA
## 2017-02-09     NA
## 2017-02-10     NA
## 2017-02-13     NA
## 2017-02-14     NA
## 2017-02-15     NA
## 2017-02-16     NA
## 2017-02-17     NA
## 2017-02-18     NA
## 2017-02-20     NA
## 2017-02-21     NA
## 2017-02-22     NA
## 2017-02-23     NA
## 2017-02-24     NA
## 2017-03-01     NA
## 2017-03-02     NA
## 2017-03-03     NA
## 2017-03-06     NA
## 2017-03-07     NA
## 2017-03-08     NA
## 2017-03-09     NA
## 2017-03-10     NA
## 2017-03-13     NA
## 2017-03-14     NA
## 2017-03-15     NA
## 2017-03-16     NA
## 2017-03-17     NA
## 2017-03-20     NA
## 2017-03-21     NA
## 2017-03-22     NA
## 2017-03-23     NA
## 2017-03-24     NA
## 2017-03-27     NA
## 2017-03-28     NA
## 2017-03-29     NA
## 2017-03-30     NA
## 2017-03-31     NA
## 2017-04-05     NA
## 2017-04-06     NA
## 2017-04-07     NA
## 2017-04-10     NA
## 2017-04-11     NA
## 2017-04-12     NA
## 2017-04-13     NA
## 2017-04-14     NA
## 2017-04-17     NA
## 2017-04-18     NA
## 2017-04-19     NA
## 2017-04-20     NA
## 2017-04-21     NA
## 2017-04-24     NA
## 2017-04-25     NA
## 2017-04-26     NA
## 2017-04-27     NA
## 2017-04-28     NA
## 2017-05-02     NA
## 2017-05-03     NA
## 2017-05-04     NA
## 2017-05-05     NA
## 2017-05-08     NA
## 2017-05-09     NA
## 2017-05-10     NA
## 2017-05-11     NA
## 2017-05-12     NA
## 2017-05-15     NA
## 2017-05-16     NA
## 2017-05-17     NA
## 2017-05-18     NA
## 2017-05-19     NA
## 2017-05-22     NA
## 2017-05-23     NA
## 2017-05-24     NA
## 2017-05-25     NA
## 2017-05-26     NA
## 2017-05-31     NA
## 2017-06-01     NA
## 2017-06-02     NA
## 2017-06-03     NA
## 2017-06-05     NA
## 2017-06-06     NA
## 2017-06-07     NA
## 2017-06-08     NA
## 2017-06-09     NA
## 2017-06-12     NA
## 2017-06-13     NA
## 2017-06-14     NA
## 2017-06-15     NA
## 2017-06-16     NA
## 2017-06-19     NA
## 2017-06-20     NA
## 2017-06-21     NA
## 2017-06-22     NA
## 2017-06-23     NA
## 2017-06-26     NA
## 2017-06-27     NA
## 2017-06-28     NA
## 2017-06-29     NA
## 2017-06-30     NA
## 2017-07-03     NA
## 2017-07-04     NA
## 2017-07-05     NA
## 2017-07-06     NA
## 2017-07-07     NA
## 2017-07-10     NA
## 2017-07-11     NA
## 2017-07-12     NA
## 2017-07-13     NA
## 2017-07-14     NA
## 2017-07-17     NA
## 2017-07-18     NA
## 2017-07-19     NA
## 2017-07-20     NA
## 2017-07-21     NA
## 2017-07-24     NA
## 2017-07-25     NA
## 2017-07-26     NA
## 2017-07-27     NA
## 2017-07-28     NA
## 2017-07-31     NA
## 2017-08-01     NA
## 2017-08-02     NA
## 2017-08-03     NA
## 2017-08-04     NA
## 2017-08-07     NA
## 2017-08-08     NA
## 2017-08-09     NA
## 2017-08-10     NA
## 2017-08-11     NA
## 2017-08-14     NA
## 2017-08-15     NA
## 2017-08-16     NA
## 2017-08-17     NA
## 2017-08-18     NA
## 2017-08-21     NA
## 2017-08-22     NA
## 2017-08-23     NA
## 2017-08-24     NA
## 2017-08-25     NA
## 2017-08-28     NA
## 2017-08-29     NA
## 2017-08-30     NA
## 2017-08-31     NA
## 2017-09-01     NA
## 2017-09-04     NA
## 2017-09-05     NA
## 2017-09-06     NA
## 2017-09-07     NA
## 2017-09-08     NA
## 2017-09-11     NA
## 2017-09-12     NA
## 2017-09-13     NA
## 2017-09-14     NA
## 2017-09-15     NA
## 2017-09-18     NA
## 2017-09-19     NA
## 2017-09-20     NA
## 2017-09-21     NA
## 2017-09-22     NA
## 2017-09-25     NA
## 2017-09-26     NA
## 2017-09-27     NA
## 2017-09-28     NA
## 2017-09-29     NA
## 2017-09-30     NA
## 2017-10-02     NA
## 2017-10-03     NA
## 2017-10-05     NA
## 2017-10-06     NA
## 2017-10-11     NA
## 2017-10-12     NA
## 2017-10-13     NA
## 2017-10-16     NA
## 2017-10-17     NA
## 2017-10-18     NA
## 2017-10-19     NA
## 2017-10-20     NA
## 2017-10-23     NA
## 2017-10-24     NA
## 2017-10-25     NA
## 2017-10-26     NA
## 2017-10-27     NA
## 2017-10-30     NA
## 2017-10-31     NA
## 2017-11-01     NA
## 2017-11-02     NA
## 2017-11-03     NA
## 2017-11-06     NA
## 2017-11-07     NA
## 2017-11-08     NA
## 2017-11-09     NA
## 2017-11-10     NA
## 2017-11-13     NA
## 2017-11-14     NA
## 2017-11-15     NA
## 2017-11-16     NA
## 2017-11-17     NA
## 2017-11-20     NA
## 2017-11-21     NA
## 2017-11-22     NA
## 2017-11-23     NA
## 2017-11-24     NA
## 2017-11-27     NA
## 2017-11-28     NA
## 2017-11-29     NA
## 2017-11-30     NA
## 2017-12-01     NA
## 2017-12-04     NA
## 2017-12-05     NA
## 2017-12-06     NA
## 2017-12-07     NA
## 2017-12-08     NA
## 2017-12-11     NA
## 2017-12-12     NA
## 2017-12-13     NA
## 2017-12-14     NA
## 2017-12-15     NA
## 2017-12-18     NA
## 2017-12-19     NA
## 2017-12-20     NA
## 2017-12-21     NA
## 2017-12-22     NA
## 2017-12-25     NA
## 2017-12-26     NA
## 2017-12-27     NA
## 2017-12-28     NA
## 2017-12-29     NA
## 2018-01-02     NA
## 2018-01-03     NA
## 2018-01-04     NA
## 2018-01-05     NA
## 2018-01-08     NA
## 2018-01-09     NA
## 2018-01-10     NA
## 2018-01-11     NA
## 2018-01-12     NA
## 2018-01-15     NA
## 2018-01-16     NA
## 2018-01-17     NA
## 2018-01-18     NA
## 2018-01-19     NA
## 2018-01-22     NA
## 2018-01-23     NA
## 2018-01-24     NA
## 2018-01-25     NA
## 2018-01-26     NA
## 2018-01-29     NA
## 2018-01-30     NA
## 2018-01-31     NA
## 2018-02-01     NA
## 2018-02-02     NA
## 2018-02-05     NA
## 2018-02-06     NA
## 2018-02-07     NA
## 2018-02-08     NA
## 2018-02-09     NA
## 2018-02-12     NA
## 2018-02-21     NA
## 2018-02-22     NA
## 2018-02-23     NA
## 2018-02-26     NA
## 2018-02-27     NA
## 2018-03-01     NA
## 2018-03-02     NA
## 2018-03-05     NA
## 2018-03-06     NA
## 2018-03-07     NA
## 2018-03-08     NA
## 2018-03-09     NA
## 2018-03-12     NA
## 2018-03-13     NA
## 2018-03-14     NA
## 2018-03-15     NA
## 2018-03-16     NA
## 2018-03-19     NA
## 2018-03-20     NA
## 2018-03-21     NA
## 2018-03-22     NA
## 2018-03-23     NA
## 2018-03-26     NA
## 2018-03-27     NA
## 2018-03-28     NA
## 2018-03-29     NA
## 2018-03-30     NA
## 2018-03-31     NA
## 2018-04-02     NA
## 2018-04-03     NA
## 2018-04-09     NA
## 2018-04-10     NA
## 2018-04-11     NA
## 2018-04-12     NA
## 2018-04-13     NA
## 2018-04-16     NA
## 2018-04-17     NA
## 2018-04-18     NA
## 2018-04-19     NA
## 2018-04-20     NA
## 2018-04-23     NA
## 2018-04-24     NA
## 2018-04-25     NA
## 2018-04-26     NA
## 2018-04-27     NA
## 2018-04-30     NA
## 2018-05-02     NA
## 2018-05-03     NA
## 2018-05-04     NA
## 2018-05-07     NA
## 2018-05-08     NA
## 2018-05-09     NA
## 2018-05-10     NA
## 2018-05-11     NA
## 2018-05-14     NA
## 2018-05-15     NA
## 2018-05-16     NA
## 2018-05-17     NA
## 2018-05-18     NA
## 2018-05-21     NA
## 2018-05-22     NA
## 2018-05-23     NA
## 2018-05-24     NA
## 2018-05-25     NA
## 2018-05-28     NA
## 2018-05-29     NA
## 2018-05-30     NA
## 2018-05-31     NA
## 2018-06-01     NA
## 2018-06-04     NA
## 2018-06-05     NA
## 2018-06-06     NA
## 2018-06-07     NA
## 2018-06-08     NA
## 2018-06-11     NA
## 2018-06-12     NA
## 2018-06-13     NA
## 2018-06-14     NA
## 2018-06-15     NA
## 2018-06-19     NA
## 2018-06-20     NA
## 2018-06-21     NA
## 2018-06-22     NA
## 2018-06-25     NA
## 2018-06-26     NA
## 2018-06-27     NA
## 2018-06-28     NA
## 2018-06-29     NA
## 2018-07-02     NA
## 2018-07-03     NA
## 2018-07-04     NA
## 2018-07-05     NA
## 2018-07-06     NA
## 2018-07-09     NA
## 2018-07-10     NA
## 2018-07-11     NA
## 2018-07-12     NA
## 2018-07-13     NA
## 2018-07-16     NA
## 2018-07-17     NA
## 2018-07-18     NA
## 2018-07-19     NA
## 2018-07-20     NA
## 2018-07-23     NA
## 2018-07-24     NA
## 2018-07-25     NA
## 2018-07-26     NA
## 2018-07-27     NA
## 2018-07-30     NA
## 2018-07-31     NA
## 2018-08-01     NA
## 2018-08-02     NA
## 2018-08-03     NA
## 2018-08-06     NA
## 2018-08-07     NA
## 2018-08-08     NA
## 2018-08-09     NA
## 2018-08-10     NA
## 2018-08-13     NA
## 2018-08-14     NA
## 2018-08-15     NA
## 2018-08-16     NA
## 2018-08-17     NA
## 2018-08-20     NA
## 2018-08-21     NA
## 2018-08-22     NA
## 2018-08-23     NA
## 2018-08-24     NA
## 2018-08-27     NA
## 2018-08-28     NA
## 2018-08-29     NA
## 2018-08-30     NA
## 2018-08-31     NA
## 2018-09-03     NA
## 2018-09-04     NA
## 2018-09-05     NA
## 2018-09-06     NA
## 2018-09-07     NA
## 2018-09-10     NA
## 2018-09-11     NA
## 2018-09-12     NA
## 2018-09-13     NA
## 2018-09-14     NA
## 2018-09-17     NA
## 2018-09-18     NA
## 2018-09-19     NA
## 2018-09-20     NA
## 2018-09-21     NA
## 2018-09-25     NA
## 2018-09-26     NA
## 2018-09-27     NA
## 2018-09-28     NA
## 2018-10-01     NA
## 2018-10-02     NA
## 2018-10-03     NA
## 2018-10-04     NA
## 2018-10-05     NA
## 2018-10-08     NA
## 2018-10-09     NA
## 2018-10-11     NA
## 2018-10-12     NA
## 2018-10-15     NA
## 2018-10-16     NA
## 2018-10-17     NA
## 2018-10-18     NA
## 2018-10-19     NA
## 2018-10-22     NA
## 2018-10-23     NA
## 2018-10-24     NA
## 2018-10-25     NA
## 2018-10-26     NA
## 2018-10-29     NA
## 2018-10-30     NA
## 2018-10-31     NA
## 2018-11-01     NA
## 2018-11-02     NA
## 2018-11-05     NA
## 2018-11-06     NA
## 2018-11-07     NA
## 2018-11-08     NA
## 2018-11-09     NA
## 2018-11-12     NA
## 2018-11-13     NA
## 2018-11-14     NA
## 2018-11-15     NA
## 2018-11-16     NA
## 2018-11-19     NA
## 2018-11-20     NA
## 2018-11-21     NA
## 2018-11-22     NA
## 2018-11-23     NA
## 2018-11-26     NA
## 2018-11-27     NA
## 2018-11-28     NA
## 2018-11-29     NA
## 2018-11-30     NA
## 2018-12-03     NA
## 2018-12-04     NA
## 2018-12-05     NA
## 2018-12-06     NA
## 2018-12-07     NA
## 2018-12-10     NA
## 2018-12-11     NA
## 2018-12-12     NA
## 2018-12-13     NA
## 2018-12-14     NA
## 2018-12-17     NA
## 2018-12-18     NA
## 2018-12-19     NA
## 2018-12-20     NA
## 2018-12-21     NA
## 2018-12-22     NA
## 2018-12-24     NA
## 2018-12-25     NA
## 2018-12-26     NA
## 2018-12-27     NA
## 2018-12-28     NA

data1$prices<-prices

class(data1$dates)

## [1] "Date"

data1$execution.price = prices
data1$weight[] = 1
buy.hold.0050 <- bt.run.share(data1, clean.signal=F, trade.summary = TRUE)

## Latest weights :
##            prices
## 2018-12-28    100
## 
## Performance summary :
##  CAGR    Best    Worst   
##  8.1 2.3 -5.4    

buy.hold.0050 <-bt.run(data1)

## Latest weights :
##            prices
## 2018-12-28    100
## 
## Performance summary :
##  CAGR    Best    Worst   
##  8.1 2.3 -5.4    

讀取sma 200天的資料。

prices<-data1$prices
sma200<-SMA(prices, 200)
head(sma200, 201)

##                 SMA
## 2015-12-14       NA
## 2015-12-15       NA
## 2015-12-16       NA
## 2015-12-17       NA
## 2015-12-18       NA
## 2015-12-21       NA
## 2015-12-22       NA
## 2015-12-23       NA
## 2015-12-24       NA
## 2015-12-25       NA
## 2015-12-28       NA
## 2015-12-29       NA
## 2015-12-30       NA
## 2015-12-31       NA
## 2016-01-04       NA
## 2016-01-05       NA
## 2016-01-06       NA
## 2016-01-07       NA
## 2016-01-08       NA
## 2016-01-11       NA
## 2016-01-12       NA
## 2016-01-13       NA
## 2016-01-14       NA
## 2016-01-15       NA
## 2016-01-18       NA
## 2016-01-19       NA
## 2016-01-20       NA
## 2016-01-21       NA
## 2016-01-22       NA
## 2016-01-25       NA
## 2016-01-26       NA
## 2016-01-27       NA
## 2016-01-28       NA
## 2016-01-29       NA
## 2016-01-30       NA
## 2016-02-01       NA
## 2016-02-02       NA
## 2016-02-03       NA
## 2016-02-15       NA
## 2016-02-16       NA
## 2016-02-17       NA
## 2016-02-18       NA
## 2016-02-19       NA
## 2016-02-22       NA
## 2016-02-23       NA
## 2016-02-24       NA
## 2016-02-25       NA
## 2016-02-26       NA
## 2016-03-01       NA
## 2016-03-02       NA
## 2016-03-03       NA
## 2016-03-04       NA
## 2016-03-07       NA
## 2016-03-08       NA
## 2016-03-09       NA
## 2016-03-10       NA
## 2016-03-11       NA
## 2016-03-14       NA
## 2016-03-15       NA
## 2016-03-16       NA
## 2016-03-17       NA
## 2016-03-18       NA
## 2016-03-21       NA
## 2016-03-22       NA
## 2016-03-23       NA
## 2016-03-24       NA
## 2016-03-25       NA
## 2016-03-28       NA
## 2016-03-29       NA
## 2016-03-30       NA
## 2016-03-31       NA
## 2016-04-01       NA
## 2016-04-06       NA
## 2016-04-07       NA
## 2016-04-08       NA
## 2016-04-11       NA
## 2016-04-12       NA
## 2016-04-13       NA
## 2016-04-14       NA
## 2016-04-15       NA
## 2016-04-18       NA
## 2016-04-19       NA
## 2016-04-20       NA
## 2016-04-21       NA
## 2016-04-22       NA
## 2016-04-25       NA
## 2016-04-26       NA
## 2016-04-27       NA
## 2016-04-28       NA
## 2016-04-29       NA
## 2016-05-03       NA
## 2016-05-04       NA
## 2016-05-05       NA
## 2016-05-06       NA
## 2016-05-09       NA
## 2016-05-10       NA
## 2016-05-11       NA
## 2016-05-12       NA
## 2016-05-13       NA
## 2016-05-16       NA
## 2016-05-17       NA
## 2016-05-18       NA
## 2016-05-19       NA
## 2016-05-20       NA
## 2016-05-23       NA
## 2016-05-24       NA
## 2016-05-25       NA
## 2016-05-26       NA
## 2016-05-27       NA
## 2016-05-30       NA
## 2016-05-31       NA
## 2016-06-01       NA
## 2016-06-02       NA
## 2016-06-03       NA
## 2016-06-04       NA
## 2016-06-06       NA
## 2016-06-07       NA
## 2016-06-08       NA
## 2016-06-13       NA
## 2016-06-14       NA
## 2016-06-15       NA
## 2016-06-16       NA
## 2016-06-17       NA
## 2016-06-20       NA
## 2016-06-21       NA
## 2016-06-22       NA
## 2016-06-23       NA
## 2016-06-24       NA
## 2016-06-27       NA
## 2016-06-28       NA
## 2016-06-29       NA
## 2016-06-30       NA
## 2016-07-01       NA
## 2016-07-04       NA
## 2016-07-05       NA
## 2016-07-06       NA
## 2016-07-07       NA
## 2016-07-11       NA
## 2016-07-12       NA
## 2016-07-13       NA
## 2016-07-14       NA
## 2016-07-15       NA
## 2016-07-18       NA
## 2016-07-19       NA
## 2016-07-20       NA
## 2016-07-21       NA
## 2016-07-22       NA
## 2016-07-25       NA
## 2016-07-26       NA
## 2016-07-27       NA
## 2016-07-28       NA
## 2016-07-29       NA
## 2016-08-01       NA
## 2016-08-02       NA
## 2016-08-03       NA
## 2016-08-04       NA
## 2016-08-05       NA
## 2016-08-08       NA
## 2016-08-09       NA
## 2016-08-10       NA
## 2016-08-11       NA
## 2016-08-12       NA
## 2016-08-15       NA
## 2016-08-16       NA
## 2016-08-17       NA
## 2016-08-18       NA
## 2016-08-19       NA
## 2016-08-22       NA
## 2016-08-23       NA
## 2016-08-24       NA
## 2016-08-25       NA
## 2016-08-26       NA
## 2016-08-29       NA
## 2016-08-30       NA
## 2016-08-31       NA
## 2016-09-01       NA
## 2016-09-02       NA
## 2016-09-05       NA
## 2016-09-06       NA
## 2016-09-07       NA
## 2016-09-08       NA
## 2016-09-09       NA
## 2016-09-10       NA
## 2016-09-12       NA
## 2016-09-13       NA
## 2016-09-14       NA
## 2016-09-19       NA
## 2016-09-20       NA
## 2016-09-21       NA
## 2016-09-22       NA
## 2016-09-23       NA
## 2016-09-26       NA
## 2016-09-29       NA
## 2016-09-30       NA
## 2016-10-03       NA
## 2016-10-04       NA
## 2016-10-05       NA
## 2016-10-06       NA
## 2016-10-07       NA
## 2016-10-11 64.26940
## 2016-10-12 64.33245

data1$weight[] <- iif(prices >= sma200, 1, 0)
sma200.0050 <- bt.run(data1, trade.summary=T)   

## Latest weights :
##            prices
## 2018-12-28      0
## 
## Performance summary :
##  CAGR    Best    Worst   
##  2.2 1.6 -4  

讀取sma 50天的資料。

sma50<-SMA(prices, 50)
head(sma50, 51)

##                SMA
## 2015-12-14      NA
## 2015-12-15      NA
## 2015-12-16      NA
## 2015-12-17      NA
## 2015-12-18      NA
## 2015-12-21      NA
## 2015-12-22      NA
## 2015-12-23      NA
## 2015-12-24      NA
## 2015-12-25      NA
## 2015-12-28      NA
## 2015-12-29      NA
## 2015-12-30      NA
## 2015-12-31      NA
## 2016-01-04      NA
## 2016-01-05      NA
## 2016-01-06      NA
## 2016-01-07      NA
## 2016-01-08      NA
## 2016-01-11      NA
## 2016-01-12      NA
## 2016-01-13      NA
## 2016-01-14      NA
## 2016-01-15      NA
## 2016-01-18      NA
## 2016-01-19      NA
## 2016-01-20      NA
## 2016-01-21      NA
## 2016-01-22      NA
## 2016-01-25      NA
## 2016-01-26      NA
## 2016-01-27      NA
## 2016-01-28      NA
## 2016-01-29      NA
## 2016-01-30      NA
## 2016-02-01      NA
## 2016-02-02      NA
## 2016-02-03      NA
## 2016-02-15      NA
## 2016-02-16      NA
## 2016-02-17      NA
## 2016-02-18      NA
## 2016-02-19      NA
## 2016-02-22      NA
## 2016-02-23      NA
## 2016-02-24      NA
## 2016-02-25      NA
## 2016-02-26      NA
## 2016-03-01      NA
## 2016-03-02 59.2194
## 2016-03-03 59.2900

data1$weight[] <- iif(prices >= sma50, 1, 0)
sma50.0050 <- bt.run(data1, trade.summary=T)

## Latest weights :
##            prices
## 2018-12-28      0
## 
## Performance summary :
##  CAGR    Best    Worst   
##  3.3 2.2 -2.4    

data1$weight[] <- iif(prices >= sma50, 1, -1)
sma50.0050.short <- bt.run(data1, trade.summary=T)

## Latest weights :
##            prices
## 2018-12-28   -100
## 
## Performance summary :
##  CAGR    Best    Worst   
##  -2.2    5.4 -2.4    

第一、二張圖：

黑色線為SMA50 1.10，紅色線為SMA200 1.07，綠色線為SMA50_short 0.94，藍色線為BH 0050 1.27。並顯示出表格。

第三張圖：

顯示出Sharpe、DVR、Cagr、MaxDD四個的長條圖。

第四張圖：

顯示為表格。

models<-list("SMA50"= sma50.0050, 
             "SMA200"= sma200.0050, 
             "SMA50_short" = sma50.0050.short, 
             "BH 0050" = buy.hold.0050)
strategy.performance.snapshoot(models, T)

## NULL

strategy.performance.snapshoot(models, control=list(comparison=T), sort.performance=T)

plotbt.strategy.sidebyside(models, return.table=T)

##            SMA50                     SMA200                   
## Period     "十二月2015 - 十二月2018" "十二月2015 - 十二月2018"
## Cagr       "3.27"                    "2.22"                   
## Sharpe     "0.43"                    "0.33"                   
## DVR        "0.15"                    "0.15"                   
## Volatility "8.57"                    "7.75"                   
## MaxDD      "-14.16"                  "-13.15"                 
## AvgDD      "-2.49"                   "-1.87"                  
## VaR        "-0.9"                    "-0.76"                  
## CVaR       "-1.44"                   "-1.3"                   
## Exposure   "64.31"                   "54.99"                  
##            SMA50_short               BH 0050                  
## Period     "十二月2015 - 十二月2018" "十二月2015 - 十二月2018"
## Cagr       "-2.16"                   "8.1"                    
## Sharpe     "-0.11"                   "0.7"                    
## DVR        "-0.04"                   "0.51"                   
## Volatility "12.56"                   "12.55"                  
## MaxDD      "-26.17"                  "-16.56"                 
## AvgDD      "-5.45"                   "-2.19"                  
## VaR        "-1.3"                    "-1.33"                  
## CVaR       "-1.75"                   "-1.94"                  
## Exposure   "99.87"                   "99.87"

library(ggplot2)
all.0050<-merge.xts(sma50.0050$equity, 
            sma50.0050.short$equity, 
            sma200.0050$equity, 
            buy.hold.0050$equity)
colnames(all.0050)<-c("sma50", "sma50 short", "sma200", "BH")
head(all.0050)

##            sma50 sma50 short sma200       BH
## 2015-12-14     1   1.0000000      1 1.000000
## 2015-12-15     1   0.9959562      1 1.004044
## 2015-12-16     1   0.9872652      1 1.012805
## 2015-12-17     1   0.9762609      1 1.024094
## 2015-12-18     1   0.9762609      1 1.024094
## 2015-12-21     1   0.9838101      1 1.016175

all.0050.long<-fortify(all.0050, melt=T)
head(all.0050.long)

##        Index Series Value
## 1 2015-12-14  sma50     1
## 2 2015-12-15  sma50     1
## 3 2015-12-16  sma50     1
## 4 2015-12-17  sma50     1
## 5 2015-12-18  sma50     1
## 6 2015-12-21  sma50     1

圖的標題為Cumulative returns of 0050s。

X軸為year，Y軸為cumulative returns。

橘色線為sma50，綠色線為sma50 short，藍色線為sma200，紫色線為BH。

title = "Cumulative returns of 0050s"
p = ggplot(all.0050.long, aes(x = Index, y = Value)) +
  geom_line(aes(linetype = Series, color = Series)) +
  #geom_point(aes(shape = Series))+
  xlab("year") + ylab("cumulative returns")+
  ggtitle(title)
p

0056

讀取0056的資料。

library(xts)
data1<-new.env()
data1$prices<-etf4.all.1$'0056'
prices<-data1$prices

sma56<-SMA(prices, 50)
head(sma56, 51)

##                SMA
## 2015-12-14      NA
## 2015-12-15      NA
## 2015-12-16      NA
## 2015-12-17      NA
## 2015-12-18      NA
## 2015-12-21      NA
## 2015-12-22      NA
## 2015-12-23      NA
## 2015-12-24      NA
## 2015-12-25      NA
## 2015-12-28      NA
## 2015-12-29      NA
## 2015-12-30      NA
## 2015-12-31      NA
## 2016-01-04      NA
## 2016-01-05      NA
## 2016-01-06      NA
## 2016-01-07      NA
## 2016-01-08      NA
## 2016-01-11      NA
## 2016-01-12      NA
## 2016-01-13      NA
## 2016-01-14      NA
## 2016-01-15      NA
## 2016-01-18      NA
## 2016-01-19      NA
## 2016-01-20      NA
## 2016-01-21      NA
## 2016-01-22      NA
## 2016-01-25      NA
## 2016-01-26      NA
## 2016-01-27      NA
## 2016-01-28      NA
## 2016-01-29      NA
## 2016-01-30      NA
## 2016-02-01      NA
## 2016-02-02      NA
## 2016-02-03      NA
## 2016-02-15      NA
## 2016-02-16      NA
## 2016-02-17      NA
## 2016-02-18      NA
## 2016-02-19      NA
## 2016-02-22      NA
## 2016-02-23      NA
## 2016-02-24      NA
## 2016-02-25      NA
## 2016-02-26      NA
## 2016-03-01      NA
## 2016-03-02 21.4786
## 2016-03-03 21.5132

分別看日期、價錢。

bt.prep(data1, align='keep.all')
names(data1)

## [1] "prices"          "dates"           "weight"          "symbolnames"    
## [5] "execution.price"

data1$dates

##   [1] "2015-12-14" "2015-12-15" "2015-12-16" "2015-12-17" "2015-12-18"
##   [6] "2015-12-21" "2015-12-22" "2015-12-23" "2015-12-24" "2015-12-25"
##  [11] "2015-12-28" "2015-12-29" "2015-12-30" "2015-12-31" "2016-01-04"
##  [16] "2016-01-05" "2016-01-06" "2016-01-07" "2016-01-08" "2016-01-11"
##  [21] "2016-01-12" "2016-01-13" "2016-01-14" "2016-01-15" "2016-01-18"
##  [26] "2016-01-19" "2016-01-20" "2016-01-21" "2016-01-22" "2016-01-25"
##  [31] "2016-01-26" "2016-01-27" "2016-01-28" "2016-01-29" "2016-01-30"
##  [36] "2016-02-01" "2016-02-02" "2016-02-03" "2016-02-15" "2016-02-16"
##  [41] "2016-02-17" "2016-02-18" "2016-02-19" "2016-02-22" "2016-02-23"
##  [46] "2016-02-24" "2016-02-25" "2016-02-26" "2016-03-01" "2016-03-02"
##  [51] "2016-03-03" "2016-03-04" "2016-03-07" "2016-03-08" "2016-03-09"
##  [56] "2016-03-10" "2016-03-11" "2016-03-14" "2016-03-15" "2016-03-16"
##  [61] "2016-03-17" "2016-03-18" "2016-03-21" "2016-03-22" "2016-03-23"
##  [66] "2016-03-24" "2016-03-25" "2016-03-28" "2016-03-29" "2016-03-30"
##  [71] "2016-03-31" "2016-04-01" "2016-04-06" "2016-04-07" "2016-04-08"
##  [76] "2016-04-11" "2016-04-12" "2016-04-13" "2016-04-14" "2016-04-15"
##  [81] "2016-04-18" "2016-04-19" "2016-04-20" "2016-04-21" "2016-04-22"
##  [86] "2016-04-25" "2016-04-26" "2016-04-27" "2016-04-28" "2016-04-29"
##  [91] "2016-05-03" "2016-05-04" "2016-05-05" "2016-05-06" "2016-05-09"
##  [96] "2016-05-10" "2016-05-11" "2016-05-12" "2016-05-13" "2016-05-16"
## [101] "2016-05-17" "2016-05-18" "2016-05-19" "2016-05-20" "2016-05-23"
## [106] "2016-05-24" "2016-05-25" "2016-05-26" "2016-05-27" "2016-05-30"
## [111] "2016-05-31" "2016-06-01" "2016-06-02" "2016-06-03" "2016-06-04"
## [116] "2016-06-06" "2016-06-07" "2016-06-08" "2016-06-13" "2016-06-14"
## [121] "2016-06-15" "2016-06-16" "2016-06-17" "2016-06-20" "2016-06-21"
## [126] "2016-06-22" "2016-06-23" "2016-06-24" "2016-06-27" "2016-06-28"
## [131] "2016-06-29" "2016-06-30" "2016-07-01" "2016-07-04" "2016-07-05"
## [136] "2016-07-06" "2016-07-07" "2016-07-11" "2016-07-12" "2016-07-13"
## [141] "2016-07-14" "2016-07-15" "2016-07-18" "2016-07-19" "2016-07-20"
## [146] "2016-07-21" "2016-07-22" "2016-07-25" "2016-07-26" "2016-07-27"
## [151] "2016-07-28" "2016-07-29" "2016-08-01" "2016-08-02" "2016-08-03"
## [156] "2016-08-04" "2016-08-05" "2016-08-08" "2016-08-09" "2016-08-10"
## [161] "2016-08-11" "2016-08-12" "2016-08-15" "2016-08-16" "2016-08-17"
## [166] "2016-08-18" "2016-08-19" "2016-08-22" "2016-08-23" "2016-08-24"
## [171] "2016-08-25" "2016-08-26" "2016-08-29" "2016-08-30" "2016-08-31"
## [176] "2016-09-01" "2016-09-02" "2016-09-05" "2016-09-06" "2016-09-07"
## [181] "2016-09-08" "2016-09-09" "2016-09-10" "2016-09-12" "2016-09-13"
## [186] "2016-09-14" "2016-09-19" "2016-09-20" "2016-09-21" "2016-09-22"
## [191] "2016-09-23" "2016-09-26" "2016-09-29" "2016-09-30" "2016-10-03"
## [196] "2016-10-04" "2016-10-05" "2016-10-06" "2016-10-07" "2016-10-11"
## [201] "2016-10-12" "2016-10-13" "2016-10-14" "2016-10-17" "2016-10-18"
## [206] "2016-10-19" "2016-10-20" "2016-10-21" "2016-10-24" "2016-10-25"
## [211] "2016-10-26" "2016-10-27" "2016-10-28" "2016-10-31" "2016-11-01"
## [216] "2016-11-02" "2016-11-03" "2016-11-04" "2016-11-07" "2016-11-08"
## [221] "2016-11-09" "2016-11-10" "2016-11-11" "2016-11-14" "2016-11-15"
## [226] "2016-11-16" "2016-11-17" "2016-11-18" "2016-11-21" "2016-11-22"
## [231] "2016-11-23" "2016-11-24" "2016-11-25" "2016-11-28" "2016-11-29"
## [236] "2016-11-30" "2016-12-01" "2016-12-02" "2016-12-05" "2016-12-06"
## [241] "2016-12-07" "2016-12-08" "2016-12-09" "2016-12-12" "2016-12-13"
## [246] "2016-12-14" "2016-12-15" "2016-12-16" "2016-12-19" "2016-12-20"
## [251] "2016-12-21" "2016-12-22" "2016-12-23" "2016-12-26" "2016-12-27"
## [256] "2016-12-28" "2016-12-29" "2016-12-30" "2017-01-03" "2017-01-04"
## [261] "2017-01-05" "2017-01-06" "2017-01-09" "2017-01-10" "2017-01-11"
## [266] "2017-01-12" "2017-01-13" "2017-01-16" "2017-01-17" "2017-01-18"
## [271] "2017-01-19" "2017-01-20" "2017-01-23" "2017-01-24" "2017-02-02"
## [276] "2017-02-03" "2017-02-06" "2017-02-07" "2017-02-08" "2017-02-09"
## [281] "2017-02-10" "2017-02-13" "2017-02-14" "2017-02-15" "2017-02-16"
## [286] "2017-02-17" "2017-02-18" "2017-02-20" "2017-02-21" "2017-02-22"
## [291] "2017-02-23" "2017-02-24" "2017-03-01" "2017-03-02" "2017-03-03"
## [296] "2017-03-06" "2017-03-07" "2017-03-08" "2017-03-09" "2017-03-10"
## [301] "2017-03-13" "2017-03-14" "2017-03-15" "2017-03-16" "2017-03-17"
## [306] "2017-03-20" "2017-03-21" "2017-03-22" "2017-03-23" "2017-03-24"
## [311] "2017-03-27" "2017-03-28" "2017-03-29" "2017-03-30" "2017-03-31"
## [316] "2017-04-05" "2017-04-06" "2017-04-07" "2017-04-10" "2017-04-11"
## [321] "2017-04-12" "2017-04-13" "2017-04-14" "2017-04-17" "2017-04-18"
## [326] "2017-04-19" "2017-04-20" "2017-04-21" "2017-04-24" "2017-04-25"
## [331] "2017-04-26" "2017-04-27" "2017-04-28" "2017-05-02" "2017-05-03"
## [336] "2017-05-04" "2017-05-05" "2017-05-08" "2017-05-09" "2017-05-10"
## [341] "2017-05-11" "2017-05-12" "2017-05-15" "2017-05-16" "2017-05-17"
## [346] "2017-05-18" "2017-05-19" "2017-05-22" "2017-05-23" "2017-05-24"
## [351] "2017-05-25" "2017-05-26" "2017-05-31" "2017-06-01" "2017-06-02"
## [356] "2017-06-03" "2017-06-05" "2017-06-06" "2017-06-07" "2017-06-08"
## [361] "2017-06-09" "2017-06-12" "2017-06-13" "2017-06-14" "2017-06-15"
## [366] "2017-06-16" "2017-06-19" "2017-06-20" "2017-06-21" "2017-06-22"
## [371] "2017-06-23" "2017-06-26" "2017-06-27" "2017-06-28" "2017-06-29"
## [376] "2017-06-30" "2017-07-03" "2017-07-04" "2017-07-05" "2017-07-06"
## [381] "2017-07-07" "2017-07-10" "2017-07-11" "2017-07-12" "2017-07-13"
## [386] "2017-07-14" "2017-07-17" "2017-07-18" "2017-07-19" "2017-07-20"
## [391] "2017-07-21" "2017-07-24" "2017-07-25" "2017-07-26" "2017-07-27"
## [396] "2017-07-28" "2017-07-31" "2017-08-01" "2017-08-02" "2017-08-03"
## [401] "2017-08-04" "2017-08-07" "2017-08-08" "2017-08-09" "2017-08-10"
## [406] "2017-08-11" "2017-08-14" "2017-08-15" "2017-08-16" "2017-08-17"
## [411] "2017-08-18" "2017-08-21" "2017-08-22" "2017-08-23" "2017-08-24"
## [416] "2017-08-25" "2017-08-28" "2017-08-29" "2017-08-30" "2017-08-31"
## [421] "2017-09-01" "2017-09-04" "2017-09-05" "2017-09-06" "2017-09-07"
## [426] "2017-09-08" "2017-09-11" "2017-09-12" "2017-09-13" "2017-09-14"
## [431] "2017-09-15" "2017-09-18" "2017-09-19" "2017-09-20" "2017-09-21"
## [436] "2017-09-22" "2017-09-25" "2017-09-26" "2017-09-27" "2017-09-28"
## [441] "2017-09-29" "2017-09-30" "2017-10-02" "2017-10-03" "2017-10-05"
## [446] "2017-10-06" "2017-10-11" "2017-10-12" "2017-10-13" "2017-10-16"
## [451] "2017-10-17" "2017-10-18" "2017-10-19" "2017-10-20" "2017-10-23"
## [456] "2017-10-24" "2017-10-25" "2017-10-26" "2017-10-27" "2017-10-30"
## [461] "2017-10-31" "2017-11-01" "2017-11-02" "2017-11-03" "2017-11-06"
## [466] "2017-11-07" "2017-11-08" "2017-11-09" "2017-11-10" "2017-11-13"
## [471] "2017-11-14" "2017-11-15" "2017-11-16" "2017-11-17" "2017-11-20"
## [476] "2017-11-21" "2017-11-22" "2017-11-23" "2017-11-24" "2017-11-27"
## [481] "2017-11-28" "2017-11-29" "2017-11-30" "2017-12-01" "2017-12-04"
## [486] "2017-12-05" "2017-12-06" "2017-12-07" "2017-12-08" "2017-12-11"
## [491] "2017-12-12" "2017-12-13" "2017-12-14" "2017-12-15" "2017-12-18"
## [496] "2017-12-19" "2017-12-20" "2017-12-21" "2017-12-22" "2017-12-25"
## [501] "2017-12-26" "2017-12-27" "2017-12-28" "2017-12-29" "2018-01-02"
## [506] "2018-01-03" "2018-01-04" "2018-01-05" "2018-01-08" "2018-01-09"
## [511] "2018-01-10" "2018-01-11" "2018-01-12" "2018-01-15" "2018-01-16"
## [516] "2018-01-17" "2018-01-18" "2018-01-19" "2018-01-22" "2018-01-23"
## [521] "2018-01-24" "2018-01-25" "2018-01-26" "2018-01-29" "2018-01-30"
## [526] "2018-01-31" "2018-02-01" "2018-02-02" "2018-02-05" "2018-02-06"
## [531] "2018-02-07" "2018-02-08" "2018-02-09" "2018-02-12" "2018-02-21"
## [536] "2018-02-22" "2018-02-23" "2018-02-26" "2018-02-27" "2018-03-01"
## [541] "2018-03-02" "2018-03-05" "2018-03-06" "2018-03-07" "2018-03-08"
## [546] "2018-03-09" "2018-03-12" "2018-03-13" "2018-03-14" "2018-03-15"
## [551] "2018-03-16" "2018-03-19" "2018-03-20" "2018-03-21" "2018-03-22"
## [556] "2018-03-23" "2018-03-26" "2018-03-27" "2018-03-28" "2018-03-29"
## [561] "2018-03-30" "2018-03-31" "2018-04-02" "2018-04-03" "2018-04-09"
## [566] "2018-04-10" "2018-04-11" "2018-04-12" "2018-04-13" "2018-04-16"
## [571] "2018-04-17" "2018-04-18" "2018-04-19" "2018-04-20" "2018-04-23"
## [576] "2018-04-24" "2018-04-25" "2018-04-26" "2018-04-27" "2018-04-30"
## [581] "2018-05-02" "2018-05-03" "2018-05-04" "2018-05-07" "2018-05-08"
## [586] "2018-05-09" "2018-05-10" "2018-05-11" "2018-05-14" "2018-05-15"
## [591] "2018-05-16" "2018-05-17" "2018-05-18" "2018-05-21" "2018-05-22"
## [596] "2018-05-23" "2018-05-24" "2018-05-25" "2018-05-28" "2018-05-29"
## [601] "2018-05-30" "2018-05-31" "2018-06-01" "2018-06-04" "2018-06-05"
## [606] "2018-06-06" "2018-06-07" "2018-06-08" "2018-06-11" "2018-06-12"
## [611] "2018-06-13" "2018-06-14" "2018-06-15" "2018-06-19" "2018-06-20"
## [616] "2018-06-21" "2018-06-22" "2018-06-25" "2018-06-26" "2018-06-27"
## [621] "2018-06-28" "2018-06-29" "2018-07-02" "2018-07-03" "2018-07-04"
## [626] "2018-07-05" "2018-07-06" "2018-07-09" "2018-07-10" "2018-07-11"
## [631] "2018-07-12" "2018-07-13" "2018-07-16" "2018-07-17" "2018-07-18"
## [636] "2018-07-19" "2018-07-20" "2018-07-23" "2018-07-24" "2018-07-25"
## [641] "2018-07-26" "2018-07-27" "2018-07-30" "2018-07-31" "2018-08-01"
## [646] "2018-08-02" "2018-08-03" "2018-08-06" "2018-08-07" "2018-08-08"
## [651] "2018-08-09" "2018-08-10" "2018-08-13" "2018-08-14" "2018-08-15"
## [656] "2018-08-16" "2018-08-17" "2018-08-20" "2018-08-21" "2018-08-22"
## [661] "2018-08-23" "2018-08-24" "2018-08-27" "2018-08-28" "2018-08-29"
## [666] "2018-08-30" "2018-08-31" "2018-09-03" "2018-09-04" "2018-09-05"
## [671] "2018-09-06" "2018-09-07" "2018-09-10" "2018-09-11" "2018-09-12"
## [676] "2018-09-13" "2018-09-14" "2018-09-17" "2018-09-18" "2018-09-19"
## [681] "2018-09-20" "2018-09-21" "2018-09-25" "2018-09-26" "2018-09-27"
## [686] "2018-09-28" "2018-10-01" "2018-10-02" "2018-10-03" "2018-10-04"
## [691] "2018-10-05" "2018-10-08" "2018-10-09" "2018-10-11" "2018-10-12"
## [696] "2018-10-15" "2018-10-16" "2018-10-17" "2018-10-18" "2018-10-19"
## [701] "2018-10-22" "2018-10-23" "2018-10-24" "2018-10-25" "2018-10-26"
## [706] "2018-10-29" "2018-10-30" "2018-10-31" "2018-11-01" "2018-11-02"
## [711] "2018-11-05" "2018-11-06" "2018-11-07" "2018-11-08" "2018-11-09"
## [716] "2018-11-12" "2018-11-13" "2018-11-14" "2018-11-15" "2018-11-16"
## [721] "2018-11-19" "2018-11-20" "2018-11-21" "2018-11-22" "2018-11-23"
## [726] "2018-11-26" "2018-11-27" "2018-11-28" "2018-11-29" "2018-11-30"
## [731] "2018-12-03" "2018-12-04" "2018-12-05" "2018-12-06" "2018-12-07"
## [736] "2018-12-10" "2018-12-11" "2018-12-12" "2018-12-13" "2018-12-14"
## [741] "2018-12-17" "2018-12-18" "2018-12-19" "2018-12-20" "2018-12-21"
## [746] "2018-12-22" "2018-12-24" "2018-12-25" "2018-12-26" "2018-12-27"
## [751] "2018-12-28"

data1$prices

##            prices
## 2015-12-14     NA
## 2015-12-15     NA
## 2015-12-16     NA
## 2015-12-17     NA
## 2015-12-18     NA
## 2015-12-21     NA
## 2015-12-22     NA
## 2015-12-23     NA
## 2015-12-24     NA
## 2015-12-25     NA
## 2015-12-28     NA
## 2015-12-29     NA
## 2015-12-30     NA
## 2015-12-31     NA
## 2016-01-04     NA
## 2016-01-05     NA
## 2016-01-06     NA
## 2016-01-07     NA
## 2016-01-08     NA
## 2016-01-11     NA
## 2016-01-12     NA
## 2016-01-13     NA
## 2016-01-14     NA
## 2016-01-15     NA
## 2016-01-18     NA
## 2016-01-19     NA
## 2016-01-20     NA
## 2016-01-21     NA
## 2016-01-22     NA
## 2016-01-25     NA
## 2016-01-26     NA
## 2016-01-27     NA
## 2016-01-28     NA
## 2016-01-29     NA
## 2016-01-30     NA
## 2016-02-01     NA
## 2016-02-02     NA
## 2016-02-03     NA
## 2016-02-15     NA
## 2016-02-16     NA
## 2016-02-17     NA
## 2016-02-18     NA
## 2016-02-19     NA
## 2016-02-22     NA
## 2016-02-23     NA
## 2016-02-24     NA
## 2016-02-25     NA
## 2016-02-26     NA
## 2016-03-01     NA
## 2016-03-02     NA
## 2016-03-03     NA
## 2016-03-04     NA
## 2016-03-07     NA
## 2016-03-08     NA
## 2016-03-09     NA
## 2016-03-10     NA
## 2016-03-11     NA
## 2016-03-14     NA
## 2016-03-15     NA
## 2016-03-16     NA
## 2016-03-17     NA
## 2016-03-18     NA
## 2016-03-21     NA
## 2016-03-22     NA
## 2016-03-23     NA
## 2016-03-24     NA
## 2016-03-25     NA
## 2016-03-28     NA
## 2016-03-29     NA
## 2016-03-30     NA
## 2016-03-31     NA
## 2016-04-01     NA
## 2016-04-06     NA
## 2016-04-07     NA
## 2016-04-08     NA
## 2016-04-11     NA
## 2016-04-12     NA
## 2016-04-13     NA
## 2016-04-14     NA
## 2016-04-15     NA
## 2016-04-18     NA
## 2016-04-19     NA
## 2016-04-20     NA
## 2016-04-21     NA
## 2016-04-22     NA
## 2016-04-25     NA
## 2016-04-26     NA
## 2016-04-27     NA
## 2016-04-28     NA
## 2016-04-29     NA
## 2016-05-03     NA
## 2016-05-04     NA
## 2016-05-05     NA
## 2016-05-06     NA
## 2016-05-09     NA
## 2016-05-10     NA
## 2016-05-11     NA
## 2016-05-12     NA
## 2016-05-13     NA
## 2016-05-16     NA
## 2016-05-17     NA
## 2016-05-18     NA
## 2016-05-19     NA
## 2016-05-20     NA
## 2016-05-23     NA
## 2016-05-24     NA
## 2016-05-25     NA
## 2016-05-26     NA
## 2016-05-27     NA
## 2016-05-30     NA
## 2016-05-31     NA
## 2016-06-01     NA
## 2016-06-02     NA
## 2016-06-03     NA
## 2016-06-04     NA
## 2016-06-06     NA
## 2016-06-07     NA
## 2016-06-08     NA
## 2016-06-13     NA
## 2016-06-14     NA
## 2016-06-15     NA
## 2016-06-16     NA
## 2016-06-17     NA
## 2016-06-20     NA
## 2016-06-21     NA
## 2016-06-22     NA
## 2016-06-23     NA
## 2016-06-24     NA
## 2016-06-27     NA
## 2016-06-28     NA
## 2016-06-29     NA
## 2016-06-30     NA
## 2016-07-01     NA
## 2016-07-04     NA
## 2016-07-05     NA
## 2016-07-06     NA
## 2016-07-07     NA
## 2016-07-11     NA
## 2016-07-12     NA
## 2016-07-13     NA
## 2016-07-14     NA
## 2016-07-15     NA
## 2016-07-18     NA
## 2016-07-19     NA
## 2016-07-20     NA
## 2016-07-21     NA
## 2016-07-22     NA
## 2016-07-25     NA
## 2016-07-26     NA
## 2016-07-27     NA
## 2016-07-28     NA
## 2016-07-29     NA
## 2016-08-01     NA
## 2016-08-02     NA
## 2016-08-03     NA
## 2016-08-04     NA
## 2016-08-05     NA
## 2016-08-08     NA
## 2016-08-09     NA
## 2016-08-10     NA
## 2016-08-11     NA
## 2016-08-12     NA
## 2016-08-15     NA
## 2016-08-16     NA
## 2016-08-17     NA
## 2016-08-18     NA
## 2016-08-19     NA
## 2016-08-22     NA
## 2016-08-23     NA
## 2016-08-24     NA
## 2016-08-25     NA
## 2016-08-26     NA
## 2016-08-29     NA
## 2016-08-30     NA
## 2016-08-31     NA
## 2016-09-01     NA
## 2016-09-02     NA
## 2016-09-05     NA
## 2016-09-06     NA
## 2016-09-07     NA
## 2016-09-08     NA
## 2016-09-09     NA
## 2016-09-10     NA
## 2016-09-12     NA
## 2016-09-13     NA
## 2016-09-14     NA
## 2016-09-19     NA
## 2016-09-20     NA
## 2016-09-21     NA
## 2016-09-22     NA
## 2016-09-23     NA
## 2016-09-26     NA
## 2016-09-29     NA
## 2016-09-30     NA
## 2016-10-03     NA
## 2016-10-04     NA
## 2016-10-05     NA
## 2016-10-06     NA
## 2016-10-07     NA
## 2016-10-11     NA
## 2016-10-12     NA
## 2016-10-13     NA
## 2016-10-14     NA
## 2016-10-17     NA
## 2016-10-18     NA
## 2016-10-19     NA
## 2016-10-20     NA
## 2016-10-21     NA
## 2016-10-24     NA
## 2016-10-25     NA
## 2016-10-26     NA
## 2016-10-27     NA
## 2016-10-28     NA
## 2016-10-31     NA
## 2016-11-01     NA
## 2016-11-02     NA
## 2016-11-03     NA
## 2016-11-04     NA
## 2016-11-07     NA
## 2016-11-08     NA
## 2016-11-09     NA
## 2016-11-10     NA
## 2016-11-11     NA
## 2016-11-14     NA
## 2016-11-15     NA
## 2016-11-16     NA
## 2016-11-17     NA
## 2016-11-18     NA
## 2016-11-21     NA
## 2016-11-22     NA
## 2016-11-23     NA
## 2016-11-24     NA
## 2016-11-25     NA
## 2016-11-28     NA
## 2016-11-29     NA
## 2016-11-30     NA
## 2016-12-01     NA
## 2016-12-02     NA
## 2016-12-05     NA
## 2016-12-06     NA
## 2016-12-07     NA
## 2016-12-08     NA
## 2016-12-09     NA
## 2016-12-12     NA
## 2016-12-13     NA
## 2016-12-14     NA
## 2016-12-15     NA
## 2016-12-16     NA
## 2016-12-19     NA
## 2016-12-20     NA
## 2016-12-21     NA
## 2016-12-22     NA
## 2016-12-23     NA
## 2016-12-26     NA
## 2016-12-27     NA
## 2016-12-28     NA
## 2016-12-29     NA
## 2016-12-30     NA
## 2017-01-03     NA
## 2017-01-04     NA
## 2017-01-05     NA
## 2017-01-06     NA
## 2017-01-09     NA
## 2017-01-10     NA
## 2017-01-11     NA
## 2017-01-12     NA
## 2017-01-13     NA
## 2017-01-16     NA
## 2017-01-17     NA
## 2017-01-18     NA
## 2017-01-19     NA
## 2017-01-20     NA
## 2017-01-23     NA
## 2017-01-24     NA
## 2017-02-02     NA
## 2017-02-03     NA
## 2017-02-06     NA
## 2017-02-07     NA
## 2017-02-08     NA
## 2017-02-09     NA
## 2017-02-10     NA
## 2017-02-13     NA
## 2017-02-14     NA
## 2017-02-15     NA
## 2017-02-16     NA
## 2017-02-17     NA
## 2017-02-18     NA
## 2017-02-20     NA
## 2017-02-21     NA
## 2017-02-22     NA
## 2017-02-23     NA
## 2017-02-24     NA
## 2017-03-01     NA
## 2017-03-02     NA
## 2017-03-03     NA
## 2017-03-06     NA
## 2017-03-07     NA
## 2017-03-08     NA
## 2017-03-09     NA
## 2017-03-10     NA
## 2017-03-13     NA
## 2017-03-14     NA
## 2017-03-15     NA
## 2017-03-16     NA
## 2017-03-17     NA
## 2017-03-20     NA
## 2017-03-21     NA
## 2017-03-22     NA
## 2017-03-23     NA
## 2017-03-24     NA
## 2017-03-27     NA
## 2017-03-28     NA
## 2017-03-29     NA
## 2017-03-30     NA
## 2017-03-31     NA
## 2017-04-05     NA
## 2017-04-06     NA
## 2017-04-07     NA
## 2017-04-10     NA
## 2017-04-11     NA
## 2017-04-12     NA
## 2017-04-13     NA
## 2017-04-14     NA
## 2017-04-17     NA
## 2017-04-18     NA
## 2017-04-19     NA
## 2017-04-20     NA
## 2017-04-21     NA
## 2017-04-24     NA
## 2017-04-25     NA
## 2017-04-26     NA
## 2017-04-27     NA
## 2017-04-28     NA
## 2017-05-02     NA
## 2017-05-03     NA
## 2017-05-04     NA
## 2017-05-05     NA
## 2017-05-08     NA
## 2017-05-09     NA
## 2017-05-10     NA
## 2017-05-11     NA
## 2017-05-12     NA
## 2017-05-15     NA
## 2017-05-16     NA
## 2017-05-17     NA
## 2017-05-18     NA
## 2017-05-19     NA
## 2017-05-22     NA
## 2017-05-23     NA
## 2017-05-24     NA
## 2017-05-25     NA
## 2017-05-26     NA
## 2017-05-31     NA
## 2017-06-01     NA
## 2017-06-02     NA
## 2017-06-03     NA
## 2017-06-05     NA
## 2017-06-06     NA
## 2017-06-07     NA
## 2017-06-08     NA
## 2017-06-09     NA
## 2017-06-12     NA
## 2017-06-13     NA
## 2017-06-14     NA
## 2017-06-15     NA
## 2017-06-16     NA
## 2017-06-19     NA
## 2017-06-20     NA
## 2017-06-21     NA
## 2017-06-22     NA
## 2017-06-23     NA
## 2017-06-26     NA
## 2017-06-27     NA
## 2017-06-28     NA
## 2017-06-29     NA
## 2017-06-30     NA
## 2017-07-03     NA
## 2017-07-04     NA
## 2017-07-05     NA
## 2017-07-06     NA
## 2017-07-07     NA
## 2017-07-10     NA
## 2017-07-11     NA
## 2017-07-12     NA
## 2017-07-13     NA
## 2017-07-14     NA
## 2017-07-17     NA
## 2017-07-18     NA
## 2017-07-19     NA
## 2017-07-20     NA
## 2017-07-21     NA
## 2017-07-24     NA
## 2017-07-25     NA
## 2017-07-26     NA
## 2017-07-27     NA
## 2017-07-28     NA
## 2017-07-31     NA
## 2017-08-01     NA
## 2017-08-02     NA
## 2017-08-03     NA
## 2017-08-04     NA
## 2017-08-07     NA
## 2017-08-08     NA
## 2017-08-09     NA
## 2017-08-10     NA
## 2017-08-11     NA
## 2017-08-14     NA
## 2017-08-15     NA
## 2017-08-16     NA
## 2017-08-17     NA
## 2017-08-18     NA
## 2017-08-21     NA
## 2017-08-22     NA
## 2017-08-23     NA
## 2017-08-24     NA
## 2017-08-25     NA
## 2017-08-28     NA
## 2017-08-29     NA
## 2017-08-30     NA
## 2017-08-31     NA
## 2017-09-01     NA
## 2017-09-04     NA
## 2017-09-05     NA
## 2017-09-06     NA
## 2017-09-07     NA
## 2017-09-08     NA
## 2017-09-11     NA
## 2017-09-12     NA
## 2017-09-13     NA
## 2017-09-14     NA
## 2017-09-15     NA
## 2017-09-18     NA
## 2017-09-19     NA
## 2017-09-20     NA
## 2017-09-21     NA
## 2017-09-22     NA
## 2017-09-25     NA
## 2017-09-26     NA
## 2017-09-27     NA
## 2017-09-28     NA
## 2017-09-29     NA
## 2017-09-30     NA
## 2017-10-02     NA
## 2017-10-03     NA
## 2017-10-05     NA
## 2017-10-06     NA
## 2017-10-11     NA
## 2017-10-12     NA
## 2017-10-13     NA
## 2017-10-16     NA
## 2017-10-17     NA
## 2017-10-18     NA
## 2017-10-19     NA
## 2017-10-20     NA
## 2017-10-23     NA
## 2017-10-24     NA
## 2017-10-25     NA
## 2017-10-26     NA
## 2017-10-27     NA
## 2017-10-30     NA
## 2017-10-31     NA
## 2017-11-01     NA
## 2017-11-02     NA
## 2017-11-03     NA
## 2017-11-06     NA
## 2017-11-07     NA
## 2017-11-08     NA
## 2017-11-09     NA
## 2017-11-10     NA
## 2017-11-13     NA
## 2017-11-14     NA
## 2017-11-15     NA
## 2017-11-16     NA
## 2017-11-17     NA
## 2017-11-20     NA
## 2017-11-21     NA
## 2017-11-22     NA
## 2017-11-23     NA
## 2017-11-24     NA
## 2017-11-27     NA
## 2017-11-28     NA
## 2017-11-29     NA
## 2017-11-30     NA
## 2017-12-01     NA
## 2017-12-04     NA
## 2017-12-05     NA
## 2017-12-06     NA
## 2017-12-07     NA
## 2017-12-08     NA
## 2017-12-11     NA
## 2017-12-12     NA
## 2017-12-13     NA
## 2017-12-14     NA
## 2017-12-15     NA
## 2017-12-18     NA
## 2017-12-19     NA
## 2017-12-20     NA
## 2017-12-21     NA
## 2017-12-22     NA
## 2017-12-25     NA
## 2017-12-26     NA
## 2017-12-27     NA
## 2017-12-28     NA
## 2017-12-29     NA
## 2018-01-02     NA
## 2018-01-03     NA
## 2018-01-04     NA
## 2018-01-05     NA
## 2018-01-08     NA
## 2018-01-09     NA
## 2018-01-10     NA
## 2018-01-11     NA
## 2018-01-12     NA
## 2018-01-15     NA
## 2018-01-16     NA
## 2018-01-17     NA
## 2018-01-18     NA
## 2018-01-19     NA
## 2018-01-22     NA
## 2018-01-23     NA
## 2018-01-24     NA
## 2018-01-25     NA
## 2018-01-26     NA
## 2018-01-29     NA
## 2018-01-30     NA
## 2018-01-31     NA
## 2018-02-01     NA
## 2018-02-02     NA
## 2018-02-05     NA
## 2018-02-06     NA
## 2018-02-07     NA
## 2018-02-08     NA
## 2018-02-09     NA
## 2018-02-12     NA
## 2018-02-21     NA
## 2018-02-22     NA
## 2018-02-23     NA
## 2018-02-26     NA
## 2018-02-27     NA
## 2018-03-01     NA
## 2018-03-02     NA
## 2018-03-05     NA
## 2018-03-06     NA
## 2018-03-07     NA
## 2018-03-08     NA
## 2018-03-09     NA
## 2018-03-12     NA
## 2018-03-13     NA
## 2018-03-14     NA
## 2018-03-15     NA
## 2018-03-16     NA
## 2018-03-19     NA
## 2018-03-20     NA
## 2018-03-21     NA
## 2018-03-22     NA
## 2018-03-23     NA
## 2018-03-26     NA
## 2018-03-27     NA
## 2018-03-28     NA
## 2018-03-29     NA
## 2018-03-30     NA
## 2018-03-31     NA
## 2018-04-02     NA
## 2018-04-03     NA
## 2018-04-09     NA
## 2018-04-10     NA
## 2018-04-11     NA
## 2018-04-12     NA
## 2018-04-13     NA
## 2018-04-16     NA
## 2018-04-17     NA
## 2018-04-18     NA
## 2018-04-19     NA
## 2018-04-20     NA
## 2018-04-23     NA
## 2018-04-24     NA
## 2018-04-25     NA
## 2018-04-26     NA
## 2018-04-27     NA
## 2018-04-30     NA
## 2018-05-02     NA
## 2018-05-03     NA
## 2018-05-04     NA
## 2018-05-07     NA
## 2018-05-08     NA
## 2018-05-09     NA
## 2018-05-10     NA
## 2018-05-11     NA
## 2018-05-14     NA
## 2018-05-15     NA
## 2018-05-16     NA
## 2018-05-17     NA
## 2018-05-18     NA
## 2018-05-21     NA
## 2018-05-22     NA
## 2018-05-23     NA
## 2018-05-24     NA
## 2018-05-25     NA
## 2018-05-28     NA
## 2018-05-29     NA
## 2018-05-30     NA
## 2018-05-31     NA
## 2018-06-01     NA
## 2018-06-04     NA
## 2018-06-05     NA
## 2018-06-06     NA
## 2018-06-07     NA
## 2018-06-08     NA
## 2018-06-11     NA
## 2018-06-12     NA
## 2018-06-13     NA
## 2018-06-14     NA
## 2018-06-15     NA
## 2018-06-19     NA
## 2018-06-20     NA
## 2018-06-21     NA
## 2018-06-22     NA
## 2018-06-25     NA
## 2018-06-26     NA
## 2018-06-27     NA
## 2018-06-28     NA
## 2018-06-29     NA
## 2018-07-02     NA
## 2018-07-03     NA
## 2018-07-04     NA
## 2018-07-05     NA
## 2018-07-06     NA
## 2018-07-09     NA
## 2018-07-10     NA
## 2018-07-11     NA
## 2018-07-12     NA
## 2018-07-13     NA
## 2018-07-16     NA
## 2018-07-17     NA
## 2018-07-18     NA
## 2018-07-19     NA
## 2018-07-20     NA
## 2018-07-23     NA
## 2018-07-24     NA
## 2018-07-25     NA
## 2018-07-26     NA
## 2018-07-27     NA
## 2018-07-30     NA
## 2018-07-31     NA
## 2018-08-01     NA
## 2018-08-02     NA
## 2018-08-03     NA
## 2018-08-06     NA
## 2018-08-07     NA
## 2018-08-08     NA
## 2018-08-09     NA
## 2018-08-10     NA
## 2018-08-13     NA
## 2018-08-14     NA
## 2018-08-15     NA
## 2018-08-16     NA
## 2018-08-17     NA
## 2018-08-20     NA
## 2018-08-21     NA
## 2018-08-22     NA
## 2018-08-23     NA
## 2018-08-24     NA
## 2018-08-27     NA
## 2018-08-28     NA
## 2018-08-29     NA
## 2018-08-30     NA
## 2018-08-31     NA
## 2018-09-03     NA
## 2018-09-04     NA
## 2018-09-05     NA
## 2018-09-06     NA
## 2018-09-07     NA
## 2018-09-10     NA
## 2018-09-11     NA
## 2018-09-12     NA
## 2018-09-13     NA
## 2018-09-14     NA
## 2018-09-17     NA
## 2018-09-18     NA
## 2018-09-19     NA
## 2018-09-20     NA
## 2018-09-21     NA
## 2018-09-25     NA
## 2018-09-26     NA
## 2018-09-27     NA
## 2018-09-28     NA
## 2018-10-01     NA
## 2018-10-02     NA
## 2018-10-03     NA
## 2018-10-04     NA
## 2018-10-05     NA
## 2018-10-08     NA
## 2018-10-09     NA
## 2018-10-11     NA
## 2018-10-12     NA
## 2018-10-15     NA
## 2018-10-16     NA
## 2018-10-17     NA
## 2018-10-18     NA
## 2018-10-19     NA
## 2018-10-22     NA
## 2018-10-23     NA
## 2018-10-24     NA
## 2018-10-25     NA
## 2018-10-26     NA
## 2018-10-29     NA
## 2018-10-30     NA
## 2018-10-31     NA
## 2018-11-01     NA
## 2018-11-02     NA
## 2018-11-05     NA
## 2018-11-06     NA
## 2018-11-07     NA
## 2018-11-08     NA
## 2018-11-09     NA
## 2018-11-12     NA
## 2018-11-13     NA
## 2018-11-14     NA
## 2018-11-15     NA
## 2018-11-16     NA
## 2018-11-19     NA
## 2018-11-20     NA
## 2018-11-21     NA
## 2018-11-22     NA
## 2018-11-23     NA
## 2018-11-26     NA
## 2018-11-27     NA
## 2018-11-28     NA
## 2018-11-29     NA
## 2018-11-30     NA
## 2018-12-03     NA
## 2018-12-04     NA
## 2018-12-05     NA
## 2018-12-06     NA
## 2018-12-07     NA
## 2018-12-10     NA
## 2018-12-11     NA
## 2018-12-12     NA
## 2018-12-13     NA
## 2018-12-14     NA
## 2018-12-17     NA
## 2018-12-18     NA
## 2018-12-19     NA
## 2018-12-20     NA
## 2018-12-21     NA
## 2018-12-22     NA
## 2018-12-24     NA
## 2018-12-25     NA
## 2018-12-26     NA
## 2018-12-27     NA
## 2018-12-28     NA

data1$prices<-prices

class(data1$dates)

## [1] "Date"

data1$execution.price = prices
data1$weight[] = 1
buy.hold.0056 <- bt.run.share(data1, clean.signal=F, trade.summary = TRUE)

## Latest weights :
##            prices
## 2018-12-28    100
## 
## Performance summary :
##  CAGR    Best    Worst   
##  4.3 2.2 -6  

buy.hold.0056 <-bt.run(data1)

## Latest weights :
##            prices
## 2018-12-28    100
## 
## Performance summary :
##  CAGR    Best    Worst   
##  4.3 2.2 -6  

讀取sma 200天的資料。

prices<-data1$prices
sma200_56<-SMA(prices, 200)
head(sma200_56, 201)

##                SMA
## 2015-12-14      NA
## 2015-12-15      NA
## 2015-12-16      NA
## 2015-12-17      NA
## 2015-12-18      NA
## 2015-12-21      NA
## 2015-12-22      NA
## 2015-12-23      NA
## 2015-12-24      NA
## 2015-12-25      NA
## 2015-12-28      NA
## 2015-12-29      NA
## 2015-12-30      NA
## 2015-12-31      NA
## 2016-01-04      NA
## 2016-01-05      NA
## 2016-01-06      NA
## 2016-01-07      NA
## 2016-01-08      NA
## 2016-01-11      NA
## 2016-01-12      NA
## 2016-01-13      NA
## 2016-01-14      NA
## 2016-01-15      NA
## 2016-01-18      NA
## 2016-01-19      NA
## 2016-01-20      NA
## 2016-01-21      NA
## 2016-01-22      NA
## 2016-01-25      NA
## 2016-01-26      NA
## 2016-01-27      NA
## 2016-01-28      NA
## 2016-01-29      NA
## 2016-01-30      NA
## 2016-02-01      NA
## 2016-02-02      NA
## 2016-02-03      NA
## 2016-02-15      NA
## 2016-02-16      NA
## 2016-02-17      NA
## 2016-02-18      NA
## 2016-02-19      NA
## 2016-02-22      NA
## 2016-02-23      NA
## 2016-02-24      NA
## 2016-02-25      NA
## 2016-02-26      NA
## 2016-03-01      NA
## 2016-03-02      NA
## 2016-03-03      NA
## 2016-03-04      NA
## 2016-03-07      NA
## 2016-03-08      NA
## 2016-03-09      NA
## 2016-03-10      NA
## 2016-03-11      NA
## 2016-03-14      NA
## 2016-03-15      NA
## 2016-03-16      NA
## 2016-03-17      NA
## 2016-03-18      NA
## 2016-03-21      NA
## 2016-03-22      NA
## 2016-03-23      NA
## 2016-03-24      NA
## 2016-03-25      NA
## 2016-03-28      NA
## 2016-03-29      NA
## 2016-03-30      NA
## 2016-03-31      NA
## 2016-04-01      NA
## 2016-04-06      NA
## 2016-04-07      NA
## 2016-04-08      NA
## 2016-04-11      NA
## 2016-04-12      NA
## 2016-04-13      NA
## 2016-04-14      NA
## 2016-04-15      NA
## 2016-04-18      NA
## 2016-04-19      NA
## 2016-04-20      NA
## 2016-04-21      NA
## 2016-04-22      NA
## 2016-04-25      NA
## 2016-04-26      NA
## 2016-04-27      NA
## 2016-04-28      NA
## 2016-04-29      NA
## 2016-05-03      NA
## 2016-05-04      NA
## 2016-05-05      NA
## 2016-05-06      NA
## 2016-05-09      NA
## 2016-05-10      NA
## 2016-05-11      NA
## 2016-05-12      NA
## 2016-05-13      NA
## 2016-05-16      NA
## 2016-05-17      NA
## 2016-05-18      NA
## 2016-05-19      NA
## 2016-05-20      NA
## 2016-05-23      NA
## 2016-05-24      NA
## 2016-05-25      NA
## 2016-05-26      NA
## 2016-05-27      NA
## 2016-05-30      NA
## 2016-05-31      NA
## 2016-06-01      NA
## 2016-06-02      NA
## 2016-06-03      NA
## 2016-06-04      NA
## 2016-06-06      NA
## 2016-06-07      NA
## 2016-06-08      NA
## 2016-06-13      NA
## 2016-06-14      NA
## 2016-06-15      NA
## 2016-06-16      NA
## 2016-06-17      NA
## 2016-06-20      NA
## 2016-06-21      NA
## 2016-06-22      NA
## 2016-06-23      NA
## 2016-06-24      NA
## 2016-06-27      NA
## 2016-06-28      NA
## 2016-06-29      NA
## 2016-06-30      NA
## 2016-07-01      NA
## 2016-07-04      NA
## 2016-07-05      NA
## 2016-07-06      NA
## 2016-07-07      NA
## 2016-07-11      NA
## 2016-07-12      NA
## 2016-07-13      NA
## 2016-07-14      NA
## 2016-07-15      NA
## 2016-07-18      NA
## 2016-07-19      NA
## 2016-07-20      NA
## 2016-07-21      NA
## 2016-07-22      NA
## 2016-07-25      NA
## 2016-07-26      NA
## 2016-07-27      NA
## 2016-07-28      NA
## 2016-07-29      NA
## 2016-08-01      NA
## 2016-08-02      NA
## 2016-08-03      NA
## 2016-08-04      NA
## 2016-08-05      NA
## 2016-08-08      NA
## 2016-08-09      NA
## 2016-08-10      NA
## 2016-08-11      NA
## 2016-08-12      NA
## 2016-08-15      NA
## 2016-08-16      NA
## 2016-08-17      NA
## 2016-08-18      NA
## 2016-08-19      NA
## 2016-08-22      NA
## 2016-08-23      NA
## 2016-08-24      NA
## 2016-08-25      NA
## 2016-08-26      NA
## 2016-08-29      NA
## 2016-08-30      NA
## 2016-08-31      NA
## 2016-09-01      NA
## 2016-09-02      NA
## 2016-09-05      NA
## 2016-09-06      NA
## 2016-09-07      NA
## 2016-09-08      NA
## 2016-09-09      NA
## 2016-09-10      NA
## 2016-09-12      NA
## 2016-09-13      NA
## 2016-09-14      NA
## 2016-09-19      NA
## 2016-09-20      NA
## 2016-09-21      NA
## 2016-09-22      NA
## 2016-09-23      NA
## 2016-09-26      NA
## 2016-09-29      NA
## 2016-09-30      NA
## 2016-10-03      NA
## 2016-10-04      NA
## 2016-10-05      NA
## 2016-10-06      NA
## 2016-10-07      NA
## 2016-10-11 22.6871
## 2016-10-12 22.7065

data1$weight[] <- iif(prices >= sma200_56, 1, 0)
sma200_56.0056 <- bt.run(data1, trade.summary=T)   

## Latest weights :
##            prices
## 2018-12-28      0
## 
## Performance summary :
##  CAGR    Best    Worst   
##  -3.1    1.5 -5.6    

讀取sma 50天的資料。

sma56<-SMA(prices, 50)
head(sma56, 51)

##                SMA
## 2015-12-14      NA
## 2015-12-15      NA
## 2015-12-16      NA
## 2015-12-17      NA
## 2015-12-18      NA
## 2015-12-21      NA
## 2015-12-22      NA
## 2015-12-23      NA
## 2015-12-24      NA
## 2015-12-25      NA
## 2015-12-28      NA
## 2015-12-29      NA
## 2015-12-30      NA
## 2015-12-31      NA
## 2016-01-04      NA
## 2016-01-05      NA
## 2016-01-06      NA
## 2016-01-07      NA
## 2016-01-08      NA
## 2016-01-11      NA
## 2016-01-12      NA
## 2016-01-13      NA
## 2016-01-14      NA
## 2016-01-15      NA
## 2016-01-18      NA
## 2016-01-19      NA
## 2016-01-20      NA
## 2016-01-21      NA
## 2016-01-22      NA
## 2016-01-25      NA
## 2016-01-26      NA
## 2016-01-27      NA
## 2016-01-28      NA
## 2016-01-29      NA
## 2016-01-30      NA
## 2016-02-01      NA
## 2016-02-02      NA
## 2016-02-03      NA
## 2016-02-15      NA
## 2016-02-16      NA
## 2016-02-17      NA
## 2016-02-18      NA
## 2016-02-19      NA
## 2016-02-22      NA
## 2016-02-23      NA
## 2016-02-24      NA
## 2016-02-25      NA
## 2016-02-26      NA
## 2016-03-01      NA
## 2016-03-02 21.4786
## 2016-03-03 21.5132

data1$weight[] <- iif(prices >= sma56, 1, 0)
sma56.0056 <- bt.run(data1, trade.summary=T)

## Latest weights :
##            prices
## 2018-12-28      0
## 
## Performance summary :
##  CAGR    Best    Worst   
##  3.7 2.2 -5.6    

data1$weight[] <- iif(prices >= sma56, 1, -1)
sma56.0056.short <- bt.run(data1, trade.summary=T)

## Latest weights :
##            prices
## 2018-12-28   -100
## 
## Performance summary :
##  CAGR    Best    Worst   
##  2.5 6   -5.6    

第一、二張圖：

黑色線為SMA56 1.12，紅色線為SMA200_56 0.91，綠色線為SMA56_short 1.08，藍色線為BH 0056 1.14。並顯示出表格。

第三張圖：

顯示出Sharpe、DVR、Cagr、MaxDD四個的長條圖。

第四張圖：

顯示為表格。

models_1<-list("SMA56"= sma56.0056, 
             "sma200_56"= sma200_56.0056, 
             "SMA56_short" = sma56.0056.short, 
             "BH 0056" = buy.hold.0056)
strategy.performance.snapshoot(models_1, T)

## NULL

strategy.performance.snapshoot(models_1, control=list(comparison=T), sort.performance=T)

plotbt.strategy.sidebyside(models_1, return.table=T)

##            SMA56                     sma200_56                
## Period     "十二月2015 - 十二月2018" "十二月2015 - 十二月2018"
## Cagr       "3.71"                    "-3.14"                  
## Sharpe     "0.53"                    "-0.38"                  
## DVR        "0.29"                    "-0.06"                  
## Volatility "7.61"                    "7.84"                   
## MaxDD      "-7.49"                   "-12.25"                 
## AvgDD      "-1.84"                   "-6.23"                  
## VaR        "-0.6"                    "-0.63"                  
## CVaR       "-1.3"                    "-1.4"                   
## Exposure   "56.86"                   "52.46"                  
##            SMA56_short               BH 0056                  
## Period     "十二月2015 - 十二月2018" "十二月2015 - 十二月2018"
## Cagr       "2.45"                    "4.28"                   
## Sharpe     "0.28"                    "0.44"                   
## DVR        "0.04"                    "0.25"                   
## Volatility "11.22"                   "11.22"                  
## MaxDD      "-14.92"                  "-15.9"                  
## AvgDD      "-3.59"                   "-3.08"                  
## VaR        "-1.1"                    "-1.1"                   
## CVaR       "-1.59"                   "-1.87"                  
## Exposure   "99.87"                   "99.87"

library(ggplot2)
all.0056<-merge.xts(sma56.0056$equity, 
                    sma56.0056.short$equity, 
                    sma200_56.0056$equity, 
                    buy.hold.0056$equity)
colnames(all.0056)<-c("sma56", "sma56 short", "sma200_56", "BH")
head(all.0056)

##            sma56 sma56 short sma200_56       BH
## 2015-12-14     1   1.0000000         1 1.000000
## 2015-12-15     1   0.9909782         1 1.009022
## 2015-12-16     1   0.9793196         1 1.020893
## 2015-12-17     1   0.9674767         1 1.033238
## 2015-12-18     1   0.9581398         1 1.043210
## 2015-12-21     1   0.9572676         1 1.044160

all.0056.long<-fortify(all.0056, melt=T)
head(all.0056.long)

##        Index Series Value
## 1 2015-12-14  sma56     1
## 2 2015-12-15  sma56     1
## 3 2015-12-16  sma56     1
## 4 2015-12-17  sma56     1
## 5 2015-12-18  sma56     1
## 6 2015-12-21  sma56     1

圖的標題為Cumulative returns of 0056s。

X軸為year，Y軸為cumulative returns。

橘色線為sma56，綠色線為sma56 short，藍色線為sma200_56，紫色線為BH。

title = "Cumulative returns of 0056s"
p1 = ggplot(all.0056.long, aes(x = Index, y = Value)) +
  geom_line(aes(linetype = Series, color = Series)) +
  #geom_point(aes(shape = Series))+
  xlab("year") + ylab("cumulative returns")+
  ggtitle(title)
p1

006205

讀取006205的資料。

library(xts)
data1<-new.env()
data1$prices<-etf4.all.1$'006205'
prices<-data1$prices

sma6205<-SMA(prices, 50)
head(sma6205, 51)

##                SMA
## 2015-12-14      NA
## 2015-12-15      NA
## 2015-12-16      NA
## 2015-12-17      NA
## 2015-12-18      NA
## 2015-12-21      NA
## 2015-12-22      NA
## 2015-12-23      NA
## 2015-12-24      NA
## 2015-12-25      NA
## 2015-12-28      NA
## 2015-12-29      NA
## 2015-12-30      NA
## 2015-12-31      NA
## 2016-01-04      NA
## 2016-01-05      NA
## 2016-01-06      NA
## 2016-01-07      NA
## 2016-01-08      NA
## 2016-01-11      NA
## 2016-01-12      NA
## 2016-01-13      NA
## 2016-01-14      NA
## 2016-01-15      NA
## 2016-01-18      NA
## 2016-01-19      NA
## 2016-01-20      NA
## 2016-01-21      NA
## 2016-01-22      NA
## 2016-01-25      NA
## 2016-01-26      NA
## 2016-01-27      NA
## 2016-01-28      NA
## 2016-01-29      NA
## 2016-01-30      NA
## 2016-02-01      NA
## 2016-02-02      NA
## 2016-02-03      NA
## 2016-02-15      NA
## 2016-02-16      NA
## 2016-02-17      NA
## 2016-02-18      NA
## 2016-02-19      NA
## 2016-02-22      NA
## 2016-02-23      NA
## 2016-02-24      NA
## 2016-02-25      NA
## 2016-02-26      NA
## 2016-03-01      NA
## 2016-03-02 28.5936
## 2016-03-03 28.5080

分別看日期、價錢。

bt.prep(data1, align='keep.all')
names(data1)

## [1] "prices"          "dates"           "weight"          "symbolnames"    
## [5] "execution.price"

data1$dates

##   [1] "2015-12-14" "2015-12-15" "2015-12-16" "2015-12-17" "2015-12-18"
##   [6] "2015-12-21" "2015-12-22" "2015-12-23" "2015-12-24" "2015-12-25"
##  [11] "2015-12-28" "2015-12-29" "2015-12-30" "2015-12-31" "2016-01-04"
##  [16] "2016-01-05" "2016-01-06" "2016-01-07" "2016-01-08" "2016-01-11"
##  [21] "2016-01-12" "2016-01-13" "2016-01-14" "2016-01-15" "2016-01-18"
##  [26] "2016-01-19" "2016-01-20" "2016-01-21" "2016-01-22" "2016-01-25"
##  [31] "2016-01-26" "2016-01-27" "2016-01-28" "2016-01-29" "2016-01-30"
##  [36] "2016-02-01" "2016-02-02" "2016-02-03" "2016-02-15" "2016-02-16"
##  [41] "2016-02-17" "2016-02-18" "2016-02-19" "2016-02-22" "2016-02-23"
##  [46] "2016-02-24" "2016-02-25" "2016-02-26" "2016-03-01" "2016-03-02"
##  [51] "2016-03-03" "2016-03-04" "2016-03-07" "2016-03-08" "2016-03-09"
##  [56] "2016-03-10" "2016-03-11" "2016-03-14" "2016-03-15" "2016-03-16"
##  [61] "2016-03-17" "2016-03-18" "2016-03-21" "2016-03-22" "2016-03-23"
##  [66] "2016-03-24" "2016-03-25" "2016-03-28" "2016-03-29" "2016-03-30"
##  [71] "2016-03-31" "2016-04-01" "2016-04-06" "2016-04-07" "2016-04-08"
##  [76] "2016-04-11" "2016-04-12" "2016-04-13" "2016-04-14" "2016-04-15"
##  [81] "2016-04-18" "2016-04-19" "2016-04-20" "2016-04-21" "2016-04-22"
##  [86] "2016-04-25" "2016-04-26" "2016-04-27" "2016-04-28" "2016-04-29"
##  [91] "2016-05-03" "2016-05-04" "2016-05-05" "2016-05-06" "2016-05-09"
##  [96] "2016-05-10" "2016-05-11" "2016-05-12" "2016-05-13" "2016-05-16"
## [101] "2016-05-17" "2016-05-18" "2016-05-19" "2016-05-20" "2016-05-23"
## [106] "2016-05-24" "2016-05-25" "2016-05-26" "2016-05-27" "2016-05-30"
## [111] "2016-05-31" "2016-06-01" "2016-06-02" "2016-06-03" "2016-06-04"
## [116] "2016-06-06" "2016-06-07" "2016-06-08" "2016-06-13" "2016-06-14"
## [121] "2016-06-15" "2016-06-16" "2016-06-17" "2016-06-20" "2016-06-21"
## [126] "2016-06-22" "2016-06-23" "2016-06-24" "2016-06-27" "2016-06-28"
## [131] "2016-06-29" "2016-06-30" "2016-07-01" "2016-07-04" "2016-07-05"
## [136] "2016-07-06" "2016-07-07" "2016-07-11" "2016-07-12" "2016-07-13"
## [141] "2016-07-14" "2016-07-15" "2016-07-18" "2016-07-19" "2016-07-20"
## [146] "2016-07-21" "2016-07-22" "2016-07-25" "2016-07-26" "2016-07-27"
## [151] "2016-07-28" "2016-07-29" "2016-08-01" "2016-08-02" "2016-08-03"
## [156] "2016-08-04" "2016-08-05" "2016-08-08" "2016-08-09" "2016-08-10"
## [161] "2016-08-11" "2016-08-12" "2016-08-15" "2016-08-16" "2016-08-17"
## [166] "2016-08-18" "2016-08-19" "2016-08-22" "2016-08-23" "2016-08-24"
## [171] "2016-08-25" "2016-08-26" "2016-08-29" "2016-08-30" "2016-08-31"
## [176] "2016-09-01" "2016-09-02" "2016-09-05" "2016-09-06" "2016-09-07"
## [181] "2016-09-08" "2016-09-09" "2016-09-10" "2016-09-12" "2016-09-13"
## [186] "2016-09-14" "2016-09-19" "2016-09-20" "2016-09-21" "2016-09-22"
## [191] "2016-09-23" "2016-09-26" "2016-09-29" "2016-09-30" "2016-10-03"
## [196] "2016-10-04" "2016-10-05" "2016-10-06" "2016-10-07" "2016-10-11"
## [201] "2016-10-12" "2016-10-13" "2016-10-14" "2016-10-17" "2016-10-18"
## [206] "2016-10-19" "2016-10-20" "2016-10-21" "2016-10-24" "2016-10-25"
## [211] "2016-10-26" "2016-10-27" "2016-10-28" "2016-10-31" "2016-11-01"
## [216] "2016-11-02" "2016-11-03" "2016-11-04" "2016-11-07" "2016-11-08"
## [221] "2016-11-09" "2016-11-10" "2016-11-11" "2016-11-14" "2016-11-15"
## [226] "2016-11-16" "2016-11-17" "2016-11-18" "2016-11-21" "2016-11-22"
## [231] "2016-11-23" "2016-11-24" "2016-11-25" "2016-11-28" "2016-11-29"
## [236] "2016-11-30" "2016-12-01" "2016-12-02" "2016-12-05" "2016-12-06"
## [241] "2016-12-07" "2016-12-08" "2016-12-09" "2016-12-12" "2016-12-13"
## [246] "2016-12-14" "2016-12-15" "2016-12-16" "2016-12-19" "2016-12-20"
## [251] "2016-12-21" "2016-12-22" "2016-12-23" "2016-12-26" "2016-12-27"
## [256] "2016-12-28" "2016-12-29" "2016-12-30" "2017-01-03" "2017-01-04"
## [261] "2017-01-05" "2017-01-06" "2017-01-09" "2017-01-10" "2017-01-11"
## [266] "2017-01-12" "2017-01-13" "2017-01-16" "2017-01-17" "2017-01-18"
## [271] "2017-01-19" "2017-01-20" "2017-01-23" "2017-01-24" "2017-02-02"
## [276] "2017-02-03" "2017-02-06" "2017-02-07" "2017-02-08" "2017-02-09"
## [281] "2017-02-10" "2017-02-13" "2017-02-14" "2017-02-15" "2017-02-16"
## [286] "2017-02-17" "2017-02-18" "2017-02-20" "2017-02-21" "2017-02-22"
## [291] "2017-02-23" "2017-02-24" "2017-03-01" "2017-03-02" "2017-03-03"
## [296] "2017-03-06" "2017-03-07" "2017-03-08" "2017-03-09" "2017-03-10"
## [301] "2017-03-13" "2017-03-14" "2017-03-15" "2017-03-16" "2017-03-17"
## [306] "2017-03-20" "2017-03-21" "2017-03-22" "2017-03-23" "2017-03-24"
## [311] "2017-03-27" "2017-03-28" "2017-03-29" "2017-03-30" "2017-03-31"
## [316] "2017-04-05" "2017-04-06" "2017-04-07" "2017-04-10" "2017-04-11"
## [321] "2017-04-12" "2017-04-13" "2017-04-14" "2017-04-17" "2017-04-18"
## [326] "2017-04-19" "2017-04-20" "2017-04-21" "2017-04-24" "2017-04-25"
## [331] "2017-04-26" "2017-04-27" "2017-04-28" "2017-05-02" "2017-05-03"
## [336] "2017-05-04" "2017-05-05" "2017-05-08" "2017-05-09" "2017-05-10"
## [341] "2017-05-11" "2017-05-12" "2017-05-15" "2017-05-16" "2017-05-17"
## [346] "2017-05-18" "2017-05-19" "2017-05-22" "2017-05-23" "2017-05-24"
## [351] "2017-05-25" "2017-05-26" "2017-05-31" "2017-06-01" "2017-06-02"
## [356] "2017-06-03" "2017-06-05" "2017-06-06" "2017-06-07" "2017-06-08"
## [361] "2017-06-09" "2017-06-12" "2017-06-13" "2017-06-14" "2017-06-15"
## [366] "2017-06-16" "2017-06-19" "2017-06-20" "2017-06-21" "2017-06-22"
## [371] "2017-06-23" "2017-06-26" "2017-06-27" "2017-06-28" "2017-06-29"
## [376] "2017-06-30" "2017-07-03" "2017-07-04" "2017-07-05" "2017-07-06"
## [381] "2017-07-07" "2017-07-10" "2017-07-11" "2017-07-12" "2017-07-13"
## [386] "2017-07-14" "2017-07-17" "2017-07-18" "2017-07-19" "2017-07-20"
## [391] "2017-07-21" "2017-07-24" "2017-07-25" "2017-07-26" "2017-07-27"
## [396] "2017-07-28" "2017-07-31" "2017-08-01" "2017-08-02" "2017-08-03"
## [401] "2017-08-04" "2017-08-07" "2017-08-08" "2017-08-09" "2017-08-10"
## [406] "2017-08-11" "2017-08-14" "2017-08-15" "2017-08-16" "2017-08-17"
## [411] "2017-08-18" "2017-08-21" "2017-08-22" "2017-08-23" "2017-08-24"
## [416] "2017-08-25" "2017-08-28" "2017-08-29" "2017-08-30" "2017-08-31"
## [421] "2017-09-01" "2017-09-04" "2017-09-05" "2017-09-06" "2017-09-07"
## [426] "2017-09-08" "2017-09-11" "2017-09-12" "2017-09-13" "2017-09-14"
## [431] "2017-09-15" "2017-09-18" "2017-09-19" "2017-09-20" "2017-09-21"
## [436] "2017-09-22" "2017-09-25" "2017-09-26" "2017-09-27" "2017-09-28"
## [441] "2017-09-29" "2017-09-30" "2017-10-02" "2017-10-03" "2017-10-05"
## [446] "2017-10-06" "2017-10-11" "2017-10-12" "2017-10-13" "2017-10-16"
## [451] "2017-10-17" "2017-10-18" "2017-10-19" "2017-10-20" "2017-10-23"
## [456] "2017-10-24" "2017-10-25" "2017-10-26" "2017-10-27" "2017-10-30"
## [461] "2017-10-31" "2017-11-01" "2017-11-02" "2017-11-03" "2017-11-06"
## [466] "2017-11-07" "2017-11-08" "2017-11-09" "2017-11-10" "2017-11-13"
## [471] "2017-11-14" "2017-11-15" "2017-11-16" "2017-11-17" "2017-11-20"
## [476] "2017-11-21" "2017-11-22" "2017-11-23" "2017-11-24" "2017-11-27"
## [481] "2017-11-28" "2017-11-29" "2017-11-30" "2017-12-01" "2017-12-04"
## [486] "2017-12-05" "2017-12-06" "2017-12-07" "2017-12-08" "2017-12-11"
## [491] "2017-12-12" "2017-12-13" "2017-12-14" "2017-12-15" "2017-12-18"
## [496] "2017-12-19" "2017-12-20" "2017-12-21" "2017-12-22" "2017-12-25"
## [501] "2017-12-26" "2017-12-27" "2017-12-28" "2017-12-29" "2018-01-02"
## [506] "2018-01-03" "2018-01-04" "2018-01-05" "2018-01-08" "2018-01-09"
## [511] "2018-01-10" "2018-01-11" "2018-01-12" "2018-01-15" "2018-01-16"
## [516] "2018-01-17" "2018-01-18" "2018-01-19" "2018-01-22" "2018-01-23"
## [521] "2018-01-24" "2018-01-25" "2018-01-26" "2018-01-29" "2018-01-30"
## [526] "2018-01-31" "2018-02-01" "2018-02-02" "2018-02-05" "2018-02-06"
## [531] "2018-02-07" "2018-02-08" "2018-02-09" "2018-02-12" "2018-02-21"
## [536] "2018-02-22" "2018-02-23" "2018-02-26" "2018-02-27" "2018-03-01"
## [541] "2018-03-02" "2018-03-05" "2018-03-06" "2018-03-07" "2018-03-08"
## [546] "2018-03-09" "2018-03-12" "2018-03-13" "2018-03-14" "2018-03-15"
## [551] "2018-03-16" "2018-03-19" "2018-03-20" "2018-03-21" "2018-03-22"
## [556] "2018-03-23" "2018-03-26" "2018-03-27" "2018-03-28" "2018-03-29"
## [561] "2018-03-30" "2018-03-31" "2018-04-02" "2018-04-03" "2018-04-09"
## [566] "2018-04-10" "2018-04-11" "2018-04-12" "2018-04-13" "2018-04-16"
## [571] "2018-04-17" "2018-04-18" "2018-04-19" "2018-04-20" "2018-04-23"
## [576] "2018-04-24" "2018-04-25" "2018-04-26" "2018-04-27" "2018-04-30"
## [581] "2018-05-02" "2018-05-03" "2018-05-04" "2018-05-07" "2018-05-08"
## [586] "2018-05-09" "2018-05-10" "2018-05-11" "2018-05-14" "2018-05-15"
## [591] "2018-05-16" "2018-05-17" "2018-05-18" "2018-05-21" "2018-05-22"
## [596] "2018-05-23" "2018-05-24" "2018-05-25" "2018-05-28" "2018-05-29"
## [601] "2018-05-30" "2018-05-31" "2018-06-01" "2018-06-04" "2018-06-05"
## [606] "2018-06-06" "2018-06-07" "2018-06-08" "2018-06-11" "2018-06-12"
## [611] "2018-06-13" "2018-06-14" "2018-06-15" "2018-06-19" "2018-06-20"
## [616] "2018-06-21" "2018-06-22" "2018-06-25" "2018-06-26" "2018-06-27"
## [621] "2018-06-28" "2018-06-29" "2018-07-02" "2018-07-03" "2018-07-04"
## [626] "2018-07-05" "2018-07-06" "2018-07-09" "2018-07-10" "2018-07-11"
## [631] "2018-07-12" "2018-07-13" "2018-07-16" "2018-07-17" "2018-07-18"
## [636] "2018-07-19" "2018-07-20" "2018-07-23" "2018-07-24" "2018-07-25"
## [641] "2018-07-26" "2018-07-27" "2018-07-30" "2018-07-31" "2018-08-01"
## [646] "2018-08-02" "2018-08-03" "2018-08-06" "2018-08-07" "2018-08-08"
## [651] "2018-08-09" "2018-08-10" "2018-08-13" "2018-08-14" "2018-08-15"
## [656] "2018-08-16" "2018-08-17" "2018-08-20" "2018-08-21" "2018-08-22"
## [661] "2018-08-23" "2018-08-24" "2018-08-27" "2018-08-28" "2018-08-29"
## [666] "2018-08-30" "2018-08-31" "2018-09-03" "2018-09-04" "2018-09-05"
## [671] "2018-09-06" "2018-09-07" "2018-09-10" "2018-09-11" "2018-09-12"
## [676] "2018-09-13" "2018-09-14" "2018-09-17" "2018-09-18" "2018-09-19"
## [681] "2018-09-20" "2018-09-21" "2018-09-25" "2018-09-26" "2018-09-27"
## [686] "2018-09-28" "2018-10-01" "2018-10-02" "2018-10-03" "2018-10-04"
## [691] "2018-10-05" "2018-10-08" "2018-10-09" "2018-10-11" "2018-10-12"
## [696] "2018-10-15" "2018-10-16" "2018-10-17" "2018-10-18" "2018-10-19"
## [701] "2018-10-22" "2018-10-23" "2018-10-24" "2018-10-25" "2018-10-26"
## [706] "2018-10-29" "2018-10-30" "2018-10-31" "2018-11-01" "2018-11-02"
## [711] "2018-11-05" "2018-11-06" "2018-11-07" "2018-11-08" "2018-11-09"
## [716] "2018-11-12" "2018-11-13" "2018-11-14" "2018-11-15" "2018-11-16"
## [721] "2018-11-19" "2018-11-20" "2018-11-21" "2018-11-22" "2018-11-23"
## [726] "2018-11-26" "2018-11-27" "2018-11-28" "2018-11-29" "2018-11-30"
## [731] "2018-12-03" "2018-12-04" "2018-12-05" "2018-12-06" "2018-12-07"
## [736] "2018-12-10" "2018-12-11" "2018-12-12" "2018-12-13" "2018-12-14"
## [741] "2018-12-17" "2018-12-18" "2018-12-19" "2018-12-20" "2018-12-21"
## [746] "2018-12-22" "2018-12-24" "2018-12-25" "2018-12-26" "2018-12-27"
## [751] "2018-12-28"

data1$prices

##            prices
## 2015-12-14     NA
## 2015-12-15     NA
## 2015-12-16     NA
## 2015-12-17     NA
## 2015-12-18     NA
## 2015-12-21     NA
## 2015-12-22     NA
## 2015-12-23     NA
## 2015-12-24     NA
## 2015-12-25     NA
## 2015-12-28     NA
## 2015-12-29     NA
## 2015-12-30     NA
## 2015-12-31     NA
## 2016-01-04     NA
## 2016-01-05     NA
## 2016-01-06     NA
## 2016-01-07     NA
## 2016-01-08     NA
## 2016-01-11     NA
## 2016-01-12     NA
## 2016-01-13     NA
## 2016-01-14     NA
## 2016-01-15     NA
## 2016-01-18     NA
## 2016-01-19     NA
## 2016-01-20     NA
## 2016-01-21     NA
## 2016-01-22     NA
## 2016-01-25     NA
## 2016-01-26     NA
## 2016-01-27     NA
## 2016-01-28     NA
## 2016-01-29     NA
## 2016-01-30     NA
## 2016-02-01     NA
## 2016-02-02     NA
## 2016-02-03     NA
## 2016-02-15     NA
## 2016-02-16     NA
## 2016-02-17     NA
## 2016-02-18     NA
## 2016-02-19     NA
## 2016-02-22     NA
## 2016-02-23     NA
## 2016-02-24     NA
## 2016-02-25     NA
## 2016-02-26     NA
## 2016-03-01     NA
## 2016-03-02     NA
## 2016-03-03     NA
## 2016-03-04     NA
## 2016-03-07     NA
## 2016-03-08     NA
## 2016-03-09     NA
## 2016-03-10     NA
## 2016-03-11     NA
## 2016-03-14     NA
## 2016-03-15     NA
## 2016-03-16     NA
## 2016-03-17     NA
## 2016-03-18     NA
## 2016-03-21     NA
## 2016-03-22     NA
## 2016-03-23     NA
## 2016-03-24     NA
## 2016-03-25     NA
## 2016-03-28     NA
## 2016-03-29     NA
## 2016-03-30     NA
## 2016-03-31     NA
## 2016-04-01     NA
## 2016-04-06     NA
## 2016-04-07     NA
## 2016-04-08     NA
## 2016-04-11     NA
## 2016-04-12     NA
## 2016-04-13     NA
## 2016-04-14     NA
## 2016-04-15     NA
## 2016-04-18     NA
## 2016-04-19     NA
## 2016-04-20     NA
## 2016-04-21     NA
## 2016-04-22     NA
## 2016-04-25     NA
## 2016-04-26     NA
## 2016-04-27     NA
## 2016-04-28     NA
## 2016-04-29     NA
## 2016-05-03     NA
## 2016-05-04     NA
## 2016-05-05     NA
## 2016-05-06     NA
## 2016-05-09     NA
## 2016-05-10     NA
## 2016-05-11     NA
## 2016-05-12     NA
## 2016-05-13     NA
## 2016-05-16     NA
## 2016-05-17     NA
## 2016-05-18     NA
## 2016-05-19     NA
## 2016-05-20     NA
## 2016-05-23     NA
## 2016-05-24     NA
## 2016-05-25     NA
## 2016-05-26     NA
## 2016-05-27     NA
## 2016-05-30     NA
## 2016-05-31     NA
## 2016-06-01     NA
## 2016-06-02     NA
## 2016-06-03     NA
## 2016-06-04     NA
## 2016-06-06     NA
## 2016-06-07     NA
## 2016-06-08     NA
## 2016-06-13     NA
## 2016-06-14     NA
## 2016-06-15     NA
## 2016-06-16     NA
## 2016-06-17     NA
## 2016-06-20     NA
## 2016-06-21     NA
## 2016-06-22     NA
## 2016-06-23     NA
## 2016-06-24     NA
## 2016-06-27     NA
## 2016-06-28     NA
## 2016-06-29     NA
## 2016-06-30     NA
## 2016-07-01     NA
## 2016-07-04     NA
## 2016-07-05     NA
## 2016-07-06     NA
## 2016-07-07     NA
## 2016-07-11     NA
## 2016-07-12     NA
## 2016-07-13     NA
## 2016-07-14     NA
## 2016-07-15     NA
## 2016-07-18     NA
## 2016-07-19     NA
## 2016-07-20     NA
## 2016-07-21     NA
## 2016-07-22     NA
## 2016-07-25     NA
## 2016-07-26     NA
## 2016-07-27     NA
## 2016-07-28     NA
## 2016-07-29     NA
## 2016-08-01     NA
## 2016-08-02     NA
## 2016-08-03     NA
## 2016-08-04     NA
## 2016-08-05     NA
## 2016-08-08     NA
## 2016-08-09     NA
## 2016-08-10     NA
## 2016-08-11     NA
## 2016-08-12     NA
## 2016-08-15     NA
## 2016-08-16     NA
## 2016-08-17     NA
## 2016-08-18     NA
## 2016-08-19     NA
## 2016-08-22     NA
## 2016-08-23     NA
## 2016-08-24     NA
## 2016-08-25     NA
## 2016-08-26     NA
## 2016-08-29     NA
## 2016-08-30     NA
## 2016-08-31     NA
## 2016-09-01     NA
## 2016-09-02     NA
## 2016-09-05     NA
## 2016-09-06     NA
## 2016-09-07     NA
## 2016-09-08     NA
## 2016-09-09     NA
## 2016-09-10     NA
## 2016-09-12     NA
## 2016-09-13     NA
## 2016-09-14     NA
## 2016-09-19     NA
## 2016-09-20     NA
## 2016-09-21     NA
## 2016-09-22     NA
## 2016-09-23     NA
## 2016-09-26     NA
## 2016-09-29     NA
## 2016-09-30     NA
## 2016-10-03     NA
## 2016-10-04     NA
## 2016-10-05     NA
## 2016-10-06     NA
## 2016-10-07     NA
## 2016-10-11     NA
## 2016-10-12     NA
## 2016-10-13     NA
## 2016-10-14     NA
## 2016-10-17     NA
## 2016-10-18     NA
## 2016-10-19     NA
## 2016-10-20     NA
## 2016-10-21     NA
## 2016-10-24     NA
## 2016-10-25     NA
## 2016-10-26     NA
## 2016-10-27     NA
## 2016-10-28     NA
## 2016-10-31     NA
## 2016-11-01     NA
## 2016-11-02     NA
## 2016-11-03     NA
## 2016-11-04     NA
## 2016-11-07     NA
## 2016-11-08     NA
## 2016-11-09     NA
## 2016-11-10     NA
## 2016-11-11     NA
## 2016-11-14     NA
## 2016-11-15     NA
## 2016-11-16     NA
## 2016-11-17     NA
## 2016-11-18     NA
## 2016-11-21     NA
## 2016-11-22     NA
## 2016-11-23     NA
## 2016-11-24     NA
## 2016-11-25     NA
## 2016-11-28     NA
## 2016-11-29     NA
## 2016-11-30     NA
## 2016-12-01     NA
## 2016-12-02     NA
## 2016-12-05     NA
## 2016-12-06     NA
## 2016-12-07     NA
## 2016-12-08     NA
## 2016-12-09     NA
## 2016-12-12     NA
## 2016-12-13     NA
## 2016-12-14     NA
## 2016-12-15     NA
## 2016-12-16     NA
## 2016-12-19     NA
## 2016-12-20     NA
## 2016-12-21     NA
## 2016-12-22     NA
## 2016-12-23     NA
## 2016-12-26     NA
## 2016-12-27     NA
## 2016-12-28     NA
## 2016-12-29     NA
## 2016-12-30     NA
## 2017-01-03     NA
## 2017-01-04     NA
## 2017-01-05     NA
## 2017-01-06     NA
## 2017-01-09     NA
## 2017-01-10     NA
## 2017-01-11     NA
## 2017-01-12     NA
## 2017-01-13     NA
## 2017-01-16     NA
## 2017-01-17     NA
## 2017-01-18     NA
## 2017-01-19     NA
## 2017-01-20     NA
## 2017-01-23     NA
## 2017-01-24     NA
## 2017-02-02     NA
## 2017-02-03     NA
## 2017-02-06     NA
## 2017-02-07     NA
## 2017-02-08     NA
## 2017-02-09     NA
## 2017-02-10     NA
## 2017-02-13     NA
## 2017-02-14     NA
## 2017-02-15     NA
## 2017-02-16     NA
## 2017-02-17     NA
## 2017-02-18     NA
## 2017-02-20     NA
## 2017-02-21     NA
## 2017-02-22     NA
## 2017-02-23     NA
## 2017-02-24     NA
## 2017-03-01     NA
## 2017-03-02     NA
## 2017-03-03     NA
## 2017-03-06     NA
## 2017-03-07     NA
## 2017-03-08     NA
## 2017-03-09     NA
## 2017-03-10     NA
## 2017-03-13     NA
## 2017-03-14     NA
## 2017-03-15     NA
## 2017-03-16     NA
## 2017-03-17     NA
## 2017-03-20     NA
## 2017-03-21     NA
## 2017-03-22     NA
## 2017-03-23     NA
## 2017-03-24     NA
## 2017-03-27     NA
## 2017-03-28     NA
## 2017-03-29     NA
## 2017-03-30     NA
## 2017-03-31     NA
## 2017-04-05     NA
## 2017-04-06     NA
## 2017-04-07     NA
## 2017-04-10     NA
## 2017-04-11     NA
## 2017-04-12     NA
## 2017-04-13     NA
## 2017-04-14     NA
## 2017-04-17     NA
## 2017-04-18     NA
## 2017-04-19     NA
## 2017-04-20     NA
## 2017-04-21     NA
## 2017-04-24     NA
## 2017-04-25     NA
## 2017-04-26     NA
## 2017-04-27     NA
## 2017-04-28     NA
## 2017-05-02     NA
## 2017-05-03     NA
## 2017-05-04     NA
## 2017-05-05     NA
## 2017-05-08     NA
## 2017-05-09     NA
## 2017-05-10     NA
## 2017-05-11     NA
## 2017-05-12     NA
## 2017-05-15     NA
## 2017-05-16     NA
## 2017-05-17     NA
## 2017-05-18     NA
## 2017-05-19     NA
## 2017-05-22     NA
## 2017-05-23     NA
## 2017-05-24     NA
## 2017-05-25     NA
## 2017-05-26     NA
## 2017-05-31     NA
## 2017-06-01     NA
## 2017-06-02     NA
## 2017-06-03     NA
## 2017-06-05     NA
## 2017-06-06     NA
## 2017-06-07     NA
## 2017-06-08     NA
## 2017-06-09     NA
## 2017-06-12     NA
## 2017-06-13     NA
## 2017-06-14     NA
## 2017-06-15     NA
## 2017-06-16     NA
## 2017-06-19     NA
## 2017-06-20     NA
## 2017-06-21     NA
## 2017-06-22     NA
## 2017-06-23     NA
## 2017-06-26     NA
## 2017-06-27     NA
## 2017-06-28     NA
## 2017-06-29     NA
## 2017-06-30     NA
## 2017-07-03     NA
## 2017-07-04     NA
## 2017-07-05     NA
## 2017-07-06     NA
## 2017-07-07     NA
## 2017-07-10     NA
## 2017-07-11     NA
## 2017-07-12     NA
## 2017-07-13     NA
## 2017-07-14     NA
## 2017-07-17     NA
## 2017-07-18     NA
## 2017-07-19     NA
## 2017-07-20     NA
## 2017-07-21     NA
## 2017-07-24     NA
## 2017-07-25     NA
## 2017-07-26     NA
## 2017-07-27     NA
## 2017-07-28     NA
## 2017-07-31     NA
## 2017-08-01     NA
## 2017-08-02     NA
## 2017-08-03     NA
## 2017-08-04     NA
## 2017-08-07     NA
## 2017-08-08     NA
## 2017-08-09     NA
## 2017-08-10     NA
## 2017-08-11     NA
## 2017-08-14     NA
## 2017-08-15     NA
## 2017-08-16     NA
## 2017-08-17     NA
## 2017-08-18     NA
## 2017-08-21     NA
## 2017-08-22     NA
## 2017-08-23     NA
## 2017-08-24     NA
## 2017-08-25     NA
## 2017-08-28     NA
## 2017-08-29     NA
## 2017-08-30     NA
## 2017-08-31     NA
## 2017-09-01     NA
## 2017-09-04     NA
## 2017-09-05     NA
## 2017-09-06     NA
## 2017-09-07     NA
## 2017-09-08     NA
## 2017-09-11     NA
## 2017-09-12     NA
## 2017-09-13     NA
## 2017-09-14     NA
## 2017-09-15     NA
## 2017-09-18     NA
## 2017-09-19     NA
## 2017-09-20     NA
## 2017-09-21     NA
## 2017-09-22     NA
## 2017-09-25     NA
## 2017-09-26     NA
## 2017-09-27     NA
## 2017-09-28     NA
## 2017-09-29     NA
## 2017-09-30     NA
## 2017-10-02     NA
## 2017-10-03     NA
## 2017-10-05     NA
## 2017-10-06     NA
## 2017-10-11     NA
## 2017-10-12     NA
## 2017-10-13     NA
## 2017-10-16     NA
## 2017-10-17     NA
## 2017-10-18     NA
## 2017-10-19     NA
## 2017-10-20     NA
## 2017-10-23     NA
## 2017-10-24     NA
## 2017-10-25     NA
## 2017-10-26     NA
## 2017-10-27     NA
## 2017-10-30     NA
## 2017-10-31     NA
## 2017-11-01     NA
## 2017-11-02     NA
## 2017-11-03     NA
## 2017-11-06     NA
## 2017-11-07     NA
## 2017-11-08     NA
## 2017-11-09     NA
## 2017-11-10     NA
## 2017-11-13     NA
## 2017-11-14     NA
## 2017-11-15     NA
## 2017-11-16     NA
## 2017-11-17     NA
## 2017-11-20     NA
## 2017-11-21     NA
## 2017-11-22     NA
## 2017-11-23     NA
## 2017-11-24     NA
## 2017-11-27     NA
## 2017-11-28     NA
## 2017-11-29     NA
## 2017-11-30     NA
## 2017-12-01     NA
## 2017-12-04     NA
## 2017-12-05     NA
## 2017-12-06     NA
## 2017-12-07     NA
## 2017-12-08     NA
## 2017-12-11     NA
## 2017-12-12     NA
## 2017-12-13     NA
## 2017-12-14     NA
## 2017-12-15     NA
## 2017-12-18     NA
## 2017-12-19     NA
## 2017-12-20     NA
## 2017-12-21     NA
## 2017-12-22     NA
## 2017-12-25     NA
## 2017-12-26     NA
## 2017-12-27     NA
## 2017-12-28     NA
## 2017-12-29     NA
## 2018-01-02     NA
## 2018-01-03     NA
## 2018-01-04     NA
## 2018-01-05     NA
## 2018-01-08     NA
## 2018-01-09     NA
## 2018-01-10     NA
## 2018-01-11     NA
## 2018-01-12     NA
## 2018-01-15     NA
## 2018-01-16     NA
## 2018-01-17     NA
## 2018-01-18     NA
## 2018-01-19     NA
## 2018-01-22     NA
## 2018-01-23     NA
## 2018-01-24     NA
## 2018-01-25     NA
## 2018-01-26     NA
## 2018-01-29     NA
## 2018-01-30     NA
## 2018-01-31     NA
## 2018-02-01     NA
## 2018-02-02     NA
## 2018-02-05     NA
## 2018-02-06     NA
## 2018-02-07     NA
## 2018-02-08     NA
## 2018-02-09     NA
## 2018-02-12     NA
## 2018-02-21     NA
## 2018-02-22     NA
## 2018-02-23     NA
## 2018-02-26     NA
## 2018-02-27     NA
## 2018-03-01     NA
## 2018-03-02     NA
## 2018-03-05     NA
## 2018-03-06     NA
## 2018-03-07     NA
## 2018-03-08     NA
## 2018-03-09     NA
## 2018-03-12     NA
## 2018-03-13     NA
## 2018-03-14     NA
## 2018-03-15     NA
## 2018-03-16     NA
## 2018-03-19     NA
## 2018-03-20     NA
## 2018-03-21     NA
## 2018-03-22     NA
## 2018-03-23     NA
## 2018-03-26     NA
## 2018-03-27     NA
## 2018-03-28     NA
## 2018-03-29     NA
## 2018-03-30     NA
## 2018-03-31     NA
## 2018-04-02     NA
## 2018-04-03     NA
## 2018-04-09     NA
## 2018-04-10     NA
## 2018-04-11     NA
## 2018-04-12     NA
## 2018-04-13     NA
## 2018-04-16     NA
## 2018-04-17     NA
## 2018-04-18     NA
## 2018-04-19     NA
## 2018-04-20     NA
## 2018-04-23     NA
## 2018-04-24     NA
## 2018-04-25     NA
## 2018-04-26     NA
## 2018-04-27     NA
## 2018-04-30     NA
## 2018-05-02     NA
## 2018-05-03     NA
## 2018-05-04     NA
## 2018-05-07     NA
## 2018-05-08     NA
## 2018-05-09     NA
## 2018-05-10     NA
## 2018-05-11     NA
## 2018-05-14     NA
## 2018-05-15     NA
## 2018-05-16     NA
## 2018-05-17     NA
## 2018-05-18     NA
## 2018-05-21     NA
## 2018-05-22     NA
## 2018-05-23     NA
## 2018-05-24     NA
## 2018-05-25     NA
## 2018-05-28     NA
## 2018-05-29     NA
## 2018-05-30     NA
## 2018-05-31     NA
## 2018-06-01     NA
## 2018-06-04     NA
## 2018-06-05     NA
## 2018-06-06     NA
## 2018-06-07     NA
## 2018-06-08     NA
## 2018-06-11     NA
## 2018-06-12     NA
## 2018-06-13     NA
## 2018-06-14     NA
## 2018-06-15     NA
## 2018-06-19     NA
## 2018-06-20     NA
## 2018-06-21     NA
## 2018-06-22     NA
## 2018-06-25     NA
## 2018-06-26     NA
## 2018-06-27     NA
## 2018-06-28     NA
## 2018-06-29     NA
## 2018-07-02     NA
## 2018-07-03     NA
## 2018-07-04     NA
## 2018-07-05     NA
## 2018-07-06     NA
## 2018-07-09     NA
## 2018-07-10     NA
## 2018-07-11     NA
## 2018-07-12     NA
## 2018-07-13     NA
## 2018-07-16     NA
## 2018-07-17     NA
## 2018-07-18     NA
## 2018-07-19     NA
## 2018-07-20     NA
## 2018-07-23     NA
## 2018-07-24     NA
## 2018-07-25     NA
## 2018-07-26     NA
## 2018-07-27     NA
## 2018-07-30     NA
## 2018-07-31     NA
## 2018-08-01     NA
## 2018-08-02     NA
## 2018-08-03     NA
## 2018-08-06     NA
## 2018-08-07     NA
## 2018-08-08     NA
## 2018-08-09     NA
## 2018-08-10     NA
## 2018-08-13     NA
## 2018-08-14     NA
## 2018-08-15     NA
## 2018-08-16     NA
## 2018-08-17     NA
## 2018-08-20     NA
## 2018-08-21     NA
## 2018-08-22     NA
## 2018-08-23     NA
## 2018-08-24     NA
## 2018-08-27     NA
## 2018-08-28     NA
## 2018-08-29     NA
## 2018-08-30     NA
## 2018-08-31     NA
## 2018-09-03     NA
## 2018-09-04     NA
## 2018-09-05     NA
## 2018-09-06     NA
## 2018-09-07     NA
## 2018-09-10     NA
## 2018-09-11     NA
## 2018-09-12     NA
## 2018-09-13     NA
## 2018-09-14     NA
## 2018-09-17     NA
## 2018-09-18     NA
## 2018-09-19     NA
## 2018-09-20     NA
## 2018-09-21     NA
## 2018-09-25     NA
## 2018-09-26     NA
## 2018-09-27     NA
## 2018-09-28     NA
## 2018-10-01     NA
## 2018-10-02     NA
## 2018-10-03     NA
## 2018-10-04     NA
## 2018-10-05     NA
## 2018-10-08     NA
## 2018-10-09     NA
## 2018-10-11     NA
## 2018-10-12     NA
## 2018-10-15     NA
## 2018-10-16     NA
## 2018-10-17     NA
## 2018-10-18     NA
## 2018-10-19     NA
## 2018-10-22     NA
## 2018-10-23     NA
## 2018-10-24     NA
## 2018-10-25     NA
## 2018-10-26     NA
## 2018-10-29     NA
## 2018-10-30     NA
## 2018-10-31     NA
## 2018-11-01     NA
## 2018-11-02     NA
## 2018-11-05     NA
## 2018-11-06     NA
## 2018-11-07     NA
## 2018-11-08     NA
## 2018-11-09     NA
## 2018-11-12     NA
## 2018-11-13     NA
## 2018-11-14     NA
## 2018-11-15     NA
## 2018-11-16     NA
## 2018-11-19     NA
## 2018-11-20     NA
## 2018-11-21     NA
## 2018-11-22     NA
## 2018-11-23     NA
## 2018-11-26     NA
## 2018-11-27     NA
## 2018-11-28     NA
## 2018-11-29     NA
## 2018-11-30     NA
## 2018-12-03     NA
## 2018-12-04     NA
## 2018-12-05     NA
## 2018-12-06     NA
## 2018-12-07     NA
## 2018-12-10     NA
## 2018-12-11     NA
## 2018-12-12     NA
## 2018-12-13     NA
## 2018-12-14     NA
## 2018-12-17     NA
## 2018-12-18     NA
## 2018-12-19     NA
## 2018-12-20     NA
## 2018-12-21     NA
## 2018-12-22     NA
## 2018-12-24     NA
## 2018-12-25     NA
## 2018-12-26     NA
## 2018-12-27     NA
## 2018-12-28     NA

data1$prices<-prices

class(data1$dates)

## [1] "Date"

data1$execution.price = prices
data1$weight[] = 1
buy.hold.006205 <- bt.run.share(data1, clean.signal=F, trade.summary = TRUE)

## Latest weights :
##            prices
## 2018-12-28    100
## 
## Performance summary :
##  CAGR    Best    Worst   
##  -6.5    5   -5.6    

buy.hold.006205 <-bt.run(data1)

## Latest weights :
##            prices
## 2018-12-28    100
## 
## Performance summary :
##  CAGR    Best    Worst   
##  -6.5    5   -5.6    

讀取sma 200天的資料。

prices<-data1$prices
sma200_6205<-SMA(prices, 200)
head(sma200_6205, 201)

##                SMA
## 2015-12-14      NA
## 2015-12-15      NA
## 2015-12-16      NA
## 2015-12-17      NA
## 2015-12-18      NA
## 2015-12-21      NA
## 2015-12-22      NA
## 2015-12-23      NA
## 2015-12-24      NA
## 2015-12-25      NA
## 2015-12-28      NA
## 2015-12-29      NA
## 2015-12-30      NA
## 2015-12-31      NA
## 2016-01-04      NA
## 2016-01-05      NA
## 2016-01-06      NA
## 2016-01-07      NA
## 2016-01-08      NA
## 2016-01-11      NA
## 2016-01-12      NA
## 2016-01-13      NA
## 2016-01-14      NA
## 2016-01-15      NA
## 2016-01-18      NA
## 2016-01-19      NA
## 2016-01-20      NA
## 2016-01-21      NA
## 2016-01-22      NA
## 2016-01-25      NA
## 2016-01-26      NA
## 2016-01-27      NA
## 2016-01-28      NA
## 2016-01-29      NA
## 2016-01-30      NA
## 2016-02-01      NA
## 2016-02-02      NA
## 2016-02-03      NA
## 2016-02-15      NA
## 2016-02-16      NA
## 2016-02-17      NA
## 2016-02-18      NA
## 2016-02-19      NA
## 2016-02-22      NA
## 2016-02-23      NA
## 2016-02-24      NA
## 2016-02-25      NA
## 2016-02-26      NA
## 2016-03-01      NA
## 2016-03-02      NA
## 2016-03-03      NA
## 2016-03-04      NA
## 2016-03-07      NA
## 2016-03-08      NA
## 2016-03-09      NA
## 2016-03-10      NA
## 2016-03-11      NA
## 2016-03-14      NA
## 2016-03-15      NA
## 2016-03-16      NA
## 2016-03-17      NA
## 2016-03-18      NA
## 2016-03-21      NA
## 2016-03-22      NA
## 2016-03-23      NA
## 2016-03-24      NA
## 2016-03-25      NA
## 2016-03-28      NA
## 2016-03-29      NA
## 2016-03-30      NA
## 2016-03-31      NA
## 2016-04-01      NA
## 2016-04-06      NA
## 2016-04-07      NA
## 2016-04-08      NA
## 2016-04-11      NA
## 2016-04-12      NA
## 2016-04-13      NA
## 2016-04-14      NA
## 2016-04-15      NA
## 2016-04-18      NA
## 2016-04-19      NA
## 2016-04-20      NA
## 2016-04-21      NA
## 2016-04-22      NA
## 2016-04-25      NA
## 2016-04-26      NA
## 2016-04-27      NA
## 2016-04-28      NA
## 2016-04-29      NA
## 2016-05-03      NA
## 2016-05-04      NA
## 2016-05-05      NA
## 2016-05-06      NA
## 2016-05-09      NA
## 2016-05-10      NA
## 2016-05-11      NA
## 2016-05-12      NA
## 2016-05-13      NA
## 2016-05-16      NA
## 2016-05-17      NA
## 2016-05-18      NA
## 2016-05-19      NA
## 2016-05-20      NA
## 2016-05-23      NA
## 2016-05-24      NA
## 2016-05-25      NA
## 2016-05-26      NA
## 2016-05-27      NA
## 2016-05-30      NA
## 2016-05-31      NA
## 2016-06-01      NA
## 2016-06-02      NA
## 2016-06-03      NA
## 2016-06-04      NA
## 2016-06-06      NA
## 2016-06-07      NA
## 2016-06-08      NA
## 2016-06-13      NA
## 2016-06-14      NA
## 2016-06-15      NA
## 2016-06-16      NA
## 2016-06-17      NA
## 2016-06-20      NA
## 2016-06-21      NA
## 2016-06-22      NA
## 2016-06-23      NA
## 2016-06-24      NA
## 2016-06-27      NA
## 2016-06-28      NA
## 2016-06-29      NA
## 2016-06-30      NA
## 2016-07-01      NA
## 2016-07-04      NA
## 2016-07-05      NA
## 2016-07-06      NA
## 2016-07-07      NA
## 2016-07-11      NA
## 2016-07-12      NA
## 2016-07-13      NA
## 2016-07-14      NA
## 2016-07-15      NA
## 2016-07-18      NA
## 2016-07-19      NA
## 2016-07-20      NA
## 2016-07-21      NA
## 2016-07-22      NA
## 2016-07-25      NA
## 2016-07-26      NA
## 2016-07-27      NA
## 2016-07-28      NA
## 2016-07-29      NA
## 2016-08-01      NA
## 2016-08-02      NA
## 2016-08-03      NA
## 2016-08-04      NA
## 2016-08-05      NA
## 2016-08-08      NA
## 2016-08-09      NA
## 2016-08-10      NA
## 2016-08-11      NA
## 2016-08-12      NA
## 2016-08-15      NA
## 2016-08-16      NA
## 2016-08-17      NA
## 2016-08-18      NA
## 2016-08-19      NA
## 2016-08-22      NA
## 2016-08-23      NA
## 2016-08-24      NA
## 2016-08-25      NA
## 2016-08-26      NA
## 2016-08-29      NA
## 2016-08-30      NA
## 2016-08-31      NA
## 2016-09-01      NA
## 2016-09-02      NA
## 2016-09-05      NA
## 2016-09-06      NA
## 2016-09-07      NA
## 2016-09-08      NA
## 2016-09-09      NA
## 2016-09-10      NA
## 2016-09-12      NA
## 2016-09-13      NA
## 2016-09-14      NA
## 2016-09-19      NA
## 2016-09-20      NA
## 2016-09-21      NA
## 2016-09-22      NA
## 2016-09-23      NA
## 2016-09-26      NA
## 2016-09-29      NA
## 2016-09-30      NA
## 2016-10-03      NA
## 2016-10-04      NA
## 2016-10-05      NA
## 2016-10-06      NA
## 2016-10-07      NA
## 2016-10-11 27.4799
## 2016-10-12 27.4596

data1$weight[] <- iif(prices >= sma200_6205, 1, 0)
sma200_6205.006205 <- bt.run(data1, trade.summary=T)  

## Latest weights :
##            prices
## 2018-12-28      0
## 
## Performance summary :
##  CAGR    Best    Worst   
##  0.5 3.2 -5.6    

讀取sma 50天的資料。

sma6205<-SMA(prices, 50)
head(sma6205, 51)

##                SMA
## 2015-12-14      NA
## 2015-12-15      NA
## 2015-12-16      NA
## 2015-12-17      NA
## 2015-12-18      NA
## 2015-12-21      NA
## 2015-12-22      NA
## 2015-12-23      NA
## 2015-12-24      NA
## 2015-12-25      NA
## 2015-12-28      NA
## 2015-12-29      NA
## 2015-12-30      NA
## 2015-12-31      NA
## 2016-01-04      NA
## 2016-01-05      NA
## 2016-01-06      NA
## 2016-01-07      NA
## 2016-01-08      NA
## 2016-01-11      NA
## 2016-01-12      NA
## 2016-01-13      NA
## 2016-01-14      NA
## 2016-01-15      NA
## 2016-01-18      NA
## 2016-01-19      NA
## 2016-01-20      NA
## 2016-01-21      NA
## 2016-01-22      NA
## 2016-01-25      NA
## 2016-01-26      NA
## 2016-01-27      NA
## 2016-01-28      NA
## 2016-01-29      NA
## 2016-01-30      NA
## 2016-02-01      NA
## 2016-02-02      NA
## 2016-02-03      NA
## 2016-02-15      NA
## 2016-02-16      NA
## 2016-02-17      NA
## 2016-02-18      NA
## 2016-02-19      NA
## 2016-02-22      NA
## 2016-02-23      NA
## 2016-02-24      NA
## 2016-02-25      NA
## 2016-02-26      NA
## 2016-03-01      NA
## 2016-03-02 28.5936
## 2016-03-03 28.5080

data1$weight[] <- iif(prices >= sma6205, 1, 0)
sma6205.006205 <- bt.run(data1, trade.summary=T)

## Latest weights :
##            prices
## 2018-12-28      0
## 
## Performance summary :
##  CAGR    Best    Worst   
##  -3.4    2.2 -5.6    

data1$weight[] <- iif(prices >= sma6205, 1, -1)
sma6205.006205.short <- bt.run(data1, trade.summary=T)

## Latest weights :
##            prices
## 2018-12-28   -100
## 
## Performance summary :
##  CAGR    Best    Worst   
##  -2.1    5.1 -5.6    

第一、二張圖：

黑色線為SMA6205 0.90，紅色線為SMA200_6205 1.02，綠色線為SMA6205_short 0.94，藍色線為BH 006205 0.81。並顯示出表格。

第三張圖：

顯示出Sharpe、DVR、Cagr、MaxDD四個的長條圖。

第四張圖：

顯示為表格。

models_2<-list("SMA6205"= sma6205.006205, 
               "sma200_6205"= sma200_6205.006205, 
               "SMA6205_short" = sma6205.006205.short, 
               "BH 006205" = buy.hold.006205)
strategy.performance.snapshoot(models_2, T)

## NULL

strategy.performance.snapshoot(models_2, control=list(comparison=T), sort.performance=T)

plotbt.strategy.sidebyside(models_2, return.table=T)

##            SMA6205                   sma200_6205              
## Period     "十二月2015 - 十二月2018" "十二月2015 - 十二月2018"
## Cagr       "-3.44"                   "0.54"                   
## Sharpe     "-0.4"                    "0.11"                   
## DVR        "0"                       "0.02"                   
## Volatility "8.15"                    "7.81"                   
## MaxDD      "-20.07"                  "-17.05"                 
## AvgDD      "-4.58"                   "-3.04"                  
## VaR        "-0.79"                   "-0.57"                  
## CVaR       "-1.38"                   "-1.29"                  
## Exposure   "42.61"                   "38.22"                  
##            SMA6205_short             BH 006205                
## Period     "十二月2015 - 十二月2018" "十二月2015 - 十二月2018"
## Cagr       "-2.11"                   "-6.52"                  
## Sharpe     "-0.06"                   "-0.35"                  
## DVR        "-0.01"                   "-0.03"                  
## Volatility "16.04"                   "16.04"                  
## MaxDD      "-28.18"                  "-29.88"                 
## AvgDD      "-6.96"                   "-14.76"                 
## VaR        "-1.5"                    "-1.62"                  
## CVaR       "-2.4"                    "-2.57"                  
## Exposure   "99.87"                   "99.87"

library(ggplot2)
all.006205<-merge.xts(sma6205.006205$equity, 
                      sma6205.006205.short$equity, 
                      sma200_6205.006205$equity, 
                      buy.hold.006205$equity)
colnames(all.006205)<-c("sma6205", "sma6205 short", "sma200_6205", "BH")
head(all.006205)

##            sma6205 sma6205 short sma200_6205       BH
## 2015-12-14       1     1.0000000           1 1.000000
## 2015-12-15       1     0.9780504           1 1.021950
## 2015-12-16       1     0.9777414           1 1.022272
## 2015-12-17       1     0.9657010           1 1.034861
## 2015-12-18       1     0.9605804           1 1.040349
## 2015-12-21       1     0.9489568           1 1.052937

all.006205.long<-fortify(all.006205, melt=T)
head(all.006205.long)

##        Index  Series Value
## 1 2015-12-14 sma6205     1
## 2 2015-12-15 sma6205     1
## 3 2015-12-16 sma6205     1
## 4 2015-12-17 sma6205     1
## 5 2015-12-18 sma6205     1
## 6 2015-12-21 sma6205     1

圖的標題為Cumulative returns of 006205s。

X軸為year，Y軸為cumulative returns。

橘色線為sma6205，綠色線為sma6205 short，藍色線為sma200_6205，紫色線為BH。

title = "Cumulative returns of 006205s"
p2 = ggplot(all.006205.long, aes(x = Index, y = Value)) +
  geom_line(aes(linetype = Series, color = Series)) +
  #geom_point(aes(shape = Series))+
  xlab("year") + ylab("cumulative returns")+
  ggtitle(title)
p2

00646

讀取00646的資料。

library(xts)
data1<-new.env()
data1$prices<-etf4.all.1$'00646'
prices<-data1$prices

sma646<-SMA(prices, 50)
head(sma646, 51)

##                SMA
## 2015-12-14      NA
## 2015-12-15      NA
## 2015-12-16      NA
## 2015-12-17      NA
## 2015-12-18      NA
## 2015-12-21      NA
## 2015-12-22      NA
## 2015-12-23      NA
## 2015-12-24      NA
## 2015-12-25      NA
## 2015-12-28      NA
## 2015-12-29      NA
## 2015-12-30      NA
## 2015-12-31      NA
## 2016-01-04      NA
## 2016-01-05      NA
## 2016-01-06      NA
## 2016-01-07      NA
## 2016-01-08      NA
## 2016-01-11      NA
## 2016-01-12      NA
## 2016-01-13      NA
## 2016-01-14      NA
## 2016-01-15      NA
## 2016-01-18      NA
## 2016-01-19      NA
## 2016-01-20      NA
## 2016-01-21      NA
## 2016-01-22      NA
## 2016-01-25      NA
## 2016-01-26      NA
## 2016-01-27      NA
## 2016-01-28      NA
## 2016-01-29      NA
## 2016-01-30      NA
## 2016-02-01      NA
## 2016-02-02      NA
## 2016-02-03      NA
## 2016-02-15      NA
## 2016-02-16      NA
## 2016-02-17      NA
## 2016-02-18      NA
## 2016-02-19      NA
## 2016-02-22      NA
## 2016-02-23      NA
## 2016-02-24      NA
## 2016-02-25      NA
## 2016-02-26      NA
## 2016-03-01      NA
## 2016-03-02 19.2538
## 2016-03-03 19.2522

分別看日期、價錢。

bt.prep(data1, align='keep.all')
names(data1)

## [1] "prices"          "dates"           "weight"          "symbolnames"    
## [5] "execution.price"

data1$dates

##   [1] "2015-12-14" "2015-12-15" "2015-12-16" "2015-12-17" "2015-12-18"
##   [6] "2015-12-21" "2015-12-22" "2015-12-23" "2015-12-24" "2015-12-25"
##  [11] "2015-12-28" "2015-12-29" "2015-12-30" "2015-12-31" "2016-01-04"
##  [16] "2016-01-05" "2016-01-06" "2016-01-07" "2016-01-08" "2016-01-11"
##  [21] "2016-01-12" "2016-01-13" "2016-01-14" "2016-01-15" "2016-01-18"
##  [26] "2016-01-19" "2016-01-20" "2016-01-21" "2016-01-22" "2016-01-25"
##  [31] "2016-01-26" "2016-01-27" "2016-01-28" "2016-01-29" "2016-01-30"
##  [36] "2016-02-01" "2016-02-02" "2016-02-03" "2016-02-15" "2016-02-16"
##  [41] "2016-02-17" "2016-02-18" "2016-02-19" "2016-02-22" "2016-02-23"
##  [46] "2016-02-24" "2016-02-25" "2016-02-26" "2016-03-01" "2016-03-02"
##  [51] "2016-03-03" "2016-03-04" "2016-03-07" "2016-03-08" "2016-03-09"
##  [56] "2016-03-10" "2016-03-11" "2016-03-14" "2016-03-15" "2016-03-16"
##  [61] "2016-03-17" "2016-03-18" "2016-03-21" "2016-03-22" "2016-03-23"
##  [66] "2016-03-24" "2016-03-25" "2016-03-28" "2016-03-29" "2016-03-30"
##  [71] "2016-03-31" "2016-04-01" "2016-04-06" "2016-04-07" "2016-04-08"
##  [76] "2016-04-11" "2016-04-12" "2016-04-13" "2016-04-14" "2016-04-15"
##  [81] "2016-04-18" "2016-04-19" "2016-04-20" "2016-04-21" "2016-04-22"
##  [86] "2016-04-25" "2016-04-26" "2016-04-27" "2016-04-28" "2016-04-29"
##  [91] "2016-05-03" "2016-05-04" "2016-05-05" "2016-05-06" "2016-05-09"
##  [96] "2016-05-10" "2016-05-11" "2016-05-12" "2016-05-13" "2016-05-16"
## [101] "2016-05-17" "2016-05-18" "2016-05-19" "2016-05-20" "2016-05-23"
## [106] "2016-05-24" "2016-05-25" "2016-05-26" "2016-05-27" "2016-05-30"
## [111] "2016-05-31" "2016-06-01" "2016-06-02" "2016-06-03" "2016-06-04"
## [116] "2016-06-06" "2016-06-07" "2016-06-08" "2016-06-13" "2016-06-14"
## [121] "2016-06-15" "2016-06-16" "2016-06-17" "2016-06-20" "2016-06-21"
## [126] "2016-06-22" "2016-06-23" "2016-06-24" "2016-06-27" "2016-06-28"
## [131] "2016-06-29" "2016-06-30" "2016-07-01" "2016-07-04" "2016-07-05"
## [136] "2016-07-06" "2016-07-07" "2016-07-11" "2016-07-12" "2016-07-13"
## [141] "2016-07-14" "2016-07-15" "2016-07-18" "2016-07-19" "2016-07-20"
## [146] "2016-07-21" "2016-07-22" "2016-07-25" "2016-07-26" "2016-07-27"
## [151] "2016-07-28" "2016-07-29" "2016-08-01" "2016-08-02" "2016-08-03"
## [156] "2016-08-04" "2016-08-05" "2016-08-08" "2016-08-09" "2016-08-10"
## [161] "2016-08-11" "2016-08-12" "2016-08-15" "2016-08-16" "2016-08-17"
## [166] "2016-08-18" "2016-08-19" "2016-08-22" "2016-08-23" "2016-08-24"
## [171] "2016-08-25" "2016-08-26" "2016-08-29" "2016-08-30" "2016-08-31"
## [176] "2016-09-01" "2016-09-02" "2016-09-05" "2016-09-06" "2016-09-07"
## [181] "2016-09-08" "2016-09-09" "2016-09-10" "2016-09-12" "2016-09-13"
## [186] "2016-09-14" "2016-09-19" "2016-09-20" "2016-09-21" "2016-09-22"
## [191] "2016-09-23" "2016-09-26" "2016-09-29" "2016-09-30" "2016-10-03"
## [196] "2016-10-04" "2016-10-05" "2016-10-06" "2016-10-07" "2016-10-11"
## [201] "2016-10-12" "2016-10-13" "2016-10-14" "2016-10-17" "2016-10-18"
## [206] "2016-10-19" "2016-10-20" "2016-10-21" "2016-10-24" "2016-10-25"
## [211] "2016-10-26" "2016-10-27" "2016-10-28" "2016-10-31" "2016-11-01"
## [216] "2016-11-02" "2016-11-03" "2016-11-04" "2016-11-07" "2016-11-08"
## [221] "2016-11-09" "2016-11-10" "2016-11-11" "2016-11-14" "2016-11-15"
## [226] "2016-11-16" "2016-11-17" "2016-11-18" "2016-11-21" "2016-11-22"
## [231] "2016-11-23" "2016-11-24" "2016-11-25" "2016-11-28" "2016-11-29"
## [236] "2016-11-30" "2016-12-01" "2016-12-02" "2016-12-05" "2016-12-06"
## [241] "2016-12-07" "2016-12-08" "2016-12-09" "2016-12-12" "2016-12-13"
## [246] "2016-12-14" "2016-12-15" "2016-12-16" "2016-12-19" "2016-12-20"
## [251] "2016-12-21" "2016-12-22" "2016-12-23" "2016-12-26" "2016-12-27"
## [256] "2016-12-28" "2016-12-29" "2016-12-30" "2017-01-03" "2017-01-04"
## [261] "2017-01-05" "2017-01-06" "2017-01-09" "2017-01-10" "2017-01-11"
## [266] "2017-01-12" "2017-01-13" "2017-01-16" "2017-01-17" "2017-01-18"
## [271] "2017-01-19" "2017-01-20" "2017-01-23" "2017-01-24" "2017-02-02"
## [276] "2017-02-03" "2017-02-06" "2017-02-07" "2017-02-08" "2017-02-09"
## [281] "2017-02-10" "2017-02-13" "2017-02-14" "2017-02-15" "2017-02-16"
## [286] "2017-02-17" "2017-02-18" "2017-02-20" "2017-02-21" "2017-02-22"
## [291] "2017-02-23" "2017-02-24" "2017-03-01" "2017-03-02" "2017-03-03"
## [296] "2017-03-06" "2017-03-07" "2017-03-08" "2017-03-09" "2017-03-10"
## [301] "2017-03-13" "2017-03-14" "2017-03-15" "2017-03-16" "2017-03-17"
## [306] "2017-03-20" "2017-03-21" "2017-03-22" "2017-03-23" "2017-03-24"
## [311] "2017-03-27" "2017-03-28" "2017-03-29" "2017-03-30" "2017-03-31"
## [316] "2017-04-05" "2017-04-06" "2017-04-07" "2017-04-10" "2017-04-11"
## [321] "2017-04-12" "2017-04-13" "2017-04-14" "2017-04-17" "2017-04-18"
## [326] "2017-04-19" "2017-04-20" "2017-04-21" "2017-04-24" "2017-04-25"
## [331] "2017-04-26" "2017-04-27" "2017-04-28" "2017-05-02" "2017-05-03"
## [336] "2017-05-04" "2017-05-05" "2017-05-08" "2017-05-09" "2017-05-10"
## [341] "2017-05-11" "2017-05-12" "2017-05-15" "2017-05-16" "2017-05-17"
## [346] "2017-05-18" "2017-05-19" "2017-05-22" "2017-05-23" "2017-05-24"
## [351] "2017-05-25" "2017-05-26" "2017-05-31" "2017-06-01" "2017-06-02"
## [356] "2017-06-03" "2017-06-05" "2017-06-06" "2017-06-07" "2017-06-08"
## [361] "2017-06-09" "2017-06-12" "2017-06-13" "2017-06-14" "2017-06-15"
## [366] "2017-06-16" "2017-06-19" "2017-06-20" "2017-06-21" "2017-06-22"
## [371] "2017-06-23" "2017-06-26" "2017-06-27" "2017-06-28" "2017-06-29"
## [376] "2017-06-30" "2017-07-03" "2017-07-04" "2017-07-05" "2017-07-06"
## [381] "2017-07-07" "2017-07-10" "2017-07-11" "2017-07-12" "2017-07-13"
## [386] "2017-07-14" "2017-07-17" "2017-07-18" "2017-07-19" "2017-07-20"
## [391] "2017-07-21" "2017-07-24" "2017-07-25" "2017-07-26" "2017-07-27"
## [396] "2017-07-28" "2017-07-31" "2017-08-01" "2017-08-02" "2017-08-03"
## [401] "2017-08-04" "2017-08-07" "2017-08-08" "2017-08-09" "2017-08-10"
## [406] "2017-08-11" "2017-08-14" "2017-08-15" "2017-08-16" "2017-08-17"
## [411] "2017-08-18" "2017-08-21" "2017-08-22" "2017-08-23" "2017-08-24"
## [416] "2017-08-25" "2017-08-28" "2017-08-29" "2017-08-30" "2017-08-31"
## [421] "2017-09-01" "2017-09-04" "2017-09-05" "2017-09-06" "2017-09-07"
## [426] "2017-09-08" "2017-09-11" "2017-09-12" "2017-09-13" "2017-09-14"
## [431] "2017-09-15" "2017-09-18" "2017-09-19" "2017-09-20" "2017-09-21"
## [436] "2017-09-22" "2017-09-25" "2017-09-26" "2017-09-27" "2017-09-28"
## [441] "2017-09-29" "2017-09-30" "2017-10-02" "2017-10-03" "2017-10-05"
## [446] "2017-10-06" "2017-10-11" "2017-10-12" "2017-10-13" "2017-10-16"
## [451] "2017-10-17" "2017-10-18" "2017-10-19" "2017-10-20" "2017-10-23"
## [456] "2017-10-24" "2017-10-25" "2017-10-26" "2017-10-27" "2017-10-30"
## [461] "2017-10-31" "2017-11-01" "2017-11-02" "2017-11-03" "2017-11-06"
## [466] "2017-11-07" "2017-11-08" "2017-11-09" "2017-11-10" "2017-11-13"
## [471] "2017-11-14" "2017-11-15" "2017-11-16" "2017-11-17" "2017-11-20"
## [476] "2017-11-21" "2017-11-22" "2017-11-23" "2017-11-24" "2017-11-27"
## [481] "2017-11-28" "2017-11-29" "2017-11-30" "2017-12-01" "2017-12-04"
## [486] "2017-12-05" "2017-12-06" "2017-12-07" "2017-12-08" "2017-12-11"
## [491] "2017-12-12" "2017-12-13" "2017-12-14" "2017-12-15" "2017-12-18"
## [496] "2017-12-19" "2017-12-20" "2017-12-21" "2017-12-22" "2017-12-25"
## [501] "2017-12-26" "2017-12-27" "2017-12-28" "2017-12-29" "2018-01-02"
## [506] "2018-01-03" "2018-01-04" "2018-01-05" "2018-01-08" "2018-01-09"
## [511] "2018-01-10" "2018-01-11" "2018-01-12" "2018-01-15" "2018-01-16"
## [516] "2018-01-17" "2018-01-18" "2018-01-19" "2018-01-22" "2018-01-23"
## [521] "2018-01-24" "2018-01-25" "2018-01-26" "2018-01-29" "2018-01-30"
## [526] "2018-01-31" "2018-02-01" "2018-02-02" "2018-02-05" "2018-02-06"
## [531] "2018-02-07" "2018-02-08" "2018-02-09" "2018-02-12" "2018-02-21"
## [536] "2018-02-22" "2018-02-23" "2018-02-26" "2018-02-27" "2018-03-01"
## [541] "2018-03-02" "2018-03-05" "2018-03-06" "2018-03-07" "2018-03-08"
## [546] "2018-03-09" "2018-03-12" "2018-03-13" "2018-03-14" "2018-03-15"
## [551] "2018-03-16" "2018-03-19" "2018-03-20" "2018-03-21" "2018-03-22"
## [556] "2018-03-23" "2018-03-26" "2018-03-27" "2018-03-28" "2018-03-29"
## [561] "2018-03-30" "2018-03-31" "2018-04-02" "2018-04-03" "2018-04-09"
## [566] "2018-04-10" "2018-04-11" "2018-04-12" "2018-04-13" "2018-04-16"
## [571] "2018-04-17" "2018-04-18" "2018-04-19" "2018-04-20" "2018-04-23"
## [576] "2018-04-24" "2018-04-25" "2018-04-26" "2018-04-27" "2018-04-30"
## [581] "2018-05-02" "2018-05-03" "2018-05-04" "2018-05-07" "2018-05-08"
## [586] "2018-05-09" "2018-05-10" "2018-05-11" "2018-05-14" "2018-05-15"
## [591] "2018-05-16" "2018-05-17" "2018-05-18" "2018-05-21" "2018-05-22"
## [596] "2018-05-23" "2018-05-24" "2018-05-25" "2018-05-28" "2018-05-29"
## [601] "2018-05-30" "2018-05-31" "2018-06-01" "2018-06-04" "2018-06-05"
## [606] "2018-06-06" "2018-06-07" "2018-06-08" "2018-06-11" "2018-06-12"
## [611] "2018-06-13" "2018-06-14" "2018-06-15" "2018-06-19" "2018-06-20"
## [616] "2018-06-21" "2018-06-22" "2018-06-25" "2018-06-26" "2018-06-27"
## [621] "2018-06-28" "2018-06-29" "2018-07-02" "2018-07-03" "2018-07-04"
## [626] "2018-07-05" "2018-07-06" "2018-07-09" "2018-07-10" "2018-07-11"
## [631] "2018-07-12" "2018-07-13" "2018-07-16" "2018-07-17" "2018-07-18"
## [636] "2018-07-19" "2018-07-20" "2018-07-23" "2018-07-24" "2018-07-25"
## [641] "2018-07-26" "2018-07-27" "2018-07-30" "2018-07-31" "2018-08-01"
## [646] "2018-08-02" "2018-08-03" "2018-08-06" "2018-08-07" "2018-08-08"
## [651] "2018-08-09" "2018-08-10" "2018-08-13" "2018-08-14" "2018-08-15"
## [656] "2018-08-16" "2018-08-17" "2018-08-20" "2018-08-21" "2018-08-22"
## [661] "2018-08-23" "2018-08-24" "2018-08-27" "2018-08-28" "2018-08-29"
## [666] "2018-08-30" "2018-08-31" "2018-09-03" "2018-09-04" "2018-09-05"
## [671] "2018-09-06" "2018-09-07" "2018-09-10" "2018-09-11" "2018-09-12"
## [676] "2018-09-13" "2018-09-14" "2018-09-17" "2018-09-18" "2018-09-19"
## [681] "2018-09-20" "2018-09-21" "2018-09-25" "2018-09-26" "2018-09-27"
## [686] "2018-09-28" "2018-10-01" "2018-10-02" "2018-10-03" "2018-10-04"
## [691] "2018-10-05" "2018-10-08" "2018-10-09" "2018-10-11" "2018-10-12"
## [696] "2018-10-15" "2018-10-16" "2018-10-17" "2018-10-18" "2018-10-19"
## [701] "2018-10-22" "2018-10-23" "2018-10-24" "2018-10-25" "2018-10-26"
## [706] "2018-10-29" "2018-10-30" "2018-10-31" "2018-11-01" "2018-11-02"
## [711] "2018-11-05" "2018-11-06" "2018-11-07" "2018-11-08" "2018-11-09"
## [716] "2018-11-12" "2018-11-13" "2018-11-14" "2018-11-15" "2018-11-16"
## [721] "2018-11-19" "2018-11-20" "2018-11-21" "2018-11-22" "2018-11-23"
## [726] "2018-11-26" "2018-11-27" "2018-11-28" "2018-11-29" "2018-11-30"
## [731] "2018-12-03" "2018-12-04" "2018-12-05" "2018-12-06" "2018-12-07"
## [736] "2018-12-10" "2018-12-11" "2018-12-12" "2018-12-13" "2018-12-14"
## [741] "2018-12-17" "2018-12-18" "2018-12-19" "2018-12-20" "2018-12-21"
## [746] "2018-12-22" "2018-12-24" "2018-12-25" "2018-12-26" "2018-12-27"
## [751] "2018-12-28"

data1$prices

##            prices
## 2015-12-14     NA
## 2015-12-15     NA
## 2015-12-16     NA
## 2015-12-17     NA
## 2015-12-18     NA
## 2015-12-21     NA
## 2015-12-22     NA
## 2015-12-23     NA
## 2015-12-24     NA
## 2015-12-25     NA
## 2015-12-28     NA
## 2015-12-29     NA
## 2015-12-30     NA
## 2015-12-31     NA
## 2016-01-04     NA
## 2016-01-05     NA
## 2016-01-06     NA
## 2016-01-07     NA
## 2016-01-08     NA
## 2016-01-11     NA
## 2016-01-12     NA
## 2016-01-13     NA
## 2016-01-14     NA
## 2016-01-15     NA
## 2016-01-18     NA
## 2016-01-19     NA
## 2016-01-20     NA
## 2016-01-21     NA
## 2016-01-22     NA
## 2016-01-25     NA
## 2016-01-26     NA
## 2016-01-27     NA
## 2016-01-28     NA
## 2016-01-29     NA
## 2016-01-30     NA
## 2016-02-01     NA
## 2016-02-02     NA
## 2016-02-03     NA
## 2016-02-15     NA
## 2016-02-16     NA
## 2016-02-17     NA
## 2016-02-18     NA
## 2016-02-19     NA
## 2016-02-22     NA
## 2016-02-23     NA
## 2016-02-24     NA
## 2016-02-25     NA
## 2016-02-26     NA
## 2016-03-01     NA
## 2016-03-02     NA
## 2016-03-03     NA
## 2016-03-04     NA
## 2016-03-07     NA
## 2016-03-08     NA
## 2016-03-09     NA
## 2016-03-10     NA
## 2016-03-11     NA
## 2016-03-14     NA
## 2016-03-15     NA
## 2016-03-16     NA
## 2016-03-17     NA
## 2016-03-18     NA
## 2016-03-21     NA
## 2016-03-22     NA
## 2016-03-23     NA
## 2016-03-24     NA
## 2016-03-25     NA
## 2016-03-28     NA
## 2016-03-29     NA
## 2016-03-30     NA
## 2016-03-31     NA
## 2016-04-01     NA
## 2016-04-06     NA
## 2016-04-07     NA
## 2016-04-08     NA
## 2016-04-11     NA
## 2016-04-12     NA
## 2016-04-13     NA
## 2016-04-14     NA
## 2016-04-15     NA
## 2016-04-18     NA
## 2016-04-19     NA
## 2016-04-20     NA
## 2016-04-21     NA
## 2016-04-22     NA
## 2016-04-25     NA
## 2016-04-26     NA
## 2016-04-27     NA
## 2016-04-28     NA
## 2016-04-29     NA
## 2016-05-03     NA
## 2016-05-04     NA
## 2016-05-05     NA
## 2016-05-06     NA
## 2016-05-09     NA
## 2016-05-10     NA
## 2016-05-11     NA
## 2016-05-12     NA
## 2016-05-13     NA
## 2016-05-16     NA
## 2016-05-17     NA
## 2016-05-18     NA
## 2016-05-19     NA
## 2016-05-20     NA
## 2016-05-23     NA
## 2016-05-24     NA
## 2016-05-25     NA
## 2016-05-26     NA
## 2016-05-27     NA
## 2016-05-30     NA
## 2016-05-31     NA
## 2016-06-01     NA
## 2016-06-02     NA
## 2016-06-03     NA
## 2016-06-04     NA
## 2016-06-06     NA
## 2016-06-07     NA
## 2016-06-08     NA
## 2016-06-13     NA
## 2016-06-14     NA
## 2016-06-15     NA
## 2016-06-16     NA
## 2016-06-17     NA
## 2016-06-20     NA
## 2016-06-21     NA
## 2016-06-22     NA
## 2016-06-23     NA
## 2016-06-24     NA
## 2016-06-27     NA
## 2016-06-28     NA
## 2016-06-29     NA
## 2016-06-30     NA
## 2016-07-01     NA
## 2016-07-04     NA
## 2016-07-05     NA
## 2016-07-06     NA
## 2016-07-07     NA
## 2016-07-11     NA
## 2016-07-12     NA
## 2016-07-13     NA
## 2016-07-14     NA
## 2016-07-15     NA
## 2016-07-18     NA
## 2016-07-19     NA
## 2016-07-20     NA
## 2016-07-21     NA
## 2016-07-22     NA
## 2016-07-25     NA
## 2016-07-26     NA
## 2016-07-27     NA
## 2016-07-28     NA
## 2016-07-29     NA
## 2016-08-01     NA
## 2016-08-02     NA
## 2016-08-03     NA
## 2016-08-04     NA
## 2016-08-05     NA
## 2016-08-08     NA
## 2016-08-09     NA
## 2016-08-10     NA
## 2016-08-11     NA
## 2016-08-12     NA
## 2016-08-15     NA
## 2016-08-16     NA
## 2016-08-17     NA
## 2016-08-18     NA
## 2016-08-19     NA
## 2016-08-22     NA
## 2016-08-23     NA
## 2016-08-24     NA
## 2016-08-25     NA
## 2016-08-26     NA
## 2016-08-29     NA
## 2016-08-30     NA
## 2016-08-31     NA
## 2016-09-01     NA
## 2016-09-02     NA
## 2016-09-05     NA
## 2016-09-06     NA
## 2016-09-07     NA
## 2016-09-08     NA
## 2016-09-09     NA
## 2016-09-10     NA
## 2016-09-12     NA
## 2016-09-13     NA
## 2016-09-14     NA
## 2016-09-19     NA
## 2016-09-20     NA
## 2016-09-21     NA
## 2016-09-22     NA
## 2016-09-23     NA
## 2016-09-26     NA
## 2016-09-29     NA
## 2016-09-30     NA
## 2016-10-03     NA
## 2016-10-04     NA
## 2016-10-05     NA
## 2016-10-06     NA
## 2016-10-07     NA
## 2016-10-11     NA
## 2016-10-12     NA
## 2016-10-13     NA
## 2016-10-14     NA
## 2016-10-17     NA
## 2016-10-18     NA
## 2016-10-19     NA
## 2016-10-20     NA
## 2016-10-21     NA
## 2016-10-24     NA
## 2016-10-25     NA
## 2016-10-26     NA
## 2016-10-27     NA
## 2016-10-28     NA
## 2016-10-31     NA
## 2016-11-01     NA
## 2016-11-02     NA
## 2016-11-03     NA
## 2016-11-04     NA
## 2016-11-07     NA
## 2016-11-08     NA
## 2016-11-09     NA
## 2016-11-10     NA
## 2016-11-11     NA
## 2016-11-14     NA
## 2016-11-15     NA
## 2016-11-16     NA
## 2016-11-17     NA
## 2016-11-18     NA
## 2016-11-21     NA
## 2016-11-22     NA
## 2016-11-23     NA
## 2016-11-24     NA
## 2016-11-25     NA
## 2016-11-28     NA
## 2016-11-29     NA
## 2016-11-30     NA
## 2016-12-01     NA
## 2016-12-02     NA
## 2016-12-05     NA
## 2016-12-06     NA
## 2016-12-07     NA
## 2016-12-08     NA
## 2016-12-09     NA
## 2016-12-12     NA
## 2016-12-13     NA
## 2016-12-14     NA
## 2016-12-15     NA
## 2016-12-16     NA
## 2016-12-19     NA
## 2016-12-20     NA
## 2016-12-21     NA
## 2016-12-22     NA
## 2016-12-23     NA
## 2016-12-26     NA
## 2016-12-27     NA
## 2016-12-28     NA
## 2016-12-29     NA
## 2016-12-30     NA
## 2017-01-03     NA
## 2017-01-04     NA
## 2017-01-05     NA
## 2017-01-06     NA
## 2017-01-09     NA
## 2017-01-10     NA
## 2017-01-11     NA
## 2017-01-12     NA
## 2017-01-13     NA
## 2017-01-16     NA
## 2017-01-17     NA
## 2017-01-18     NA
## 2017-01-19     NA
## 2017-01-20     NA
## 2017-01-23     NA
## 2017-01-24     NA
## 2017-02-02     NA
## 2017-02-03     NA
## 2017-02-06     NA
## 2017-02-07     NA
## 2017-02-08     NA
## 2017-02-09     NA
## 2017-02-10     NA
## 2017-02-13     NA
## 2017-02-14     NA
## 2017-02-15     NA
## 2017-02-16     NA
## 2017-02-17     NA
## 2017-02-18     NA
## 2017-02-20     NA
## 2017-02-21     NA
## 2017-02-22     NA
## 2017-02-23     NA
## 2017-02-24     NA
## 2017-03-01     NA
## 2017-03-02     NA
## 2017-03-03     NA
## 2017-03-06     NA
## 2017-03-07     NA
## 2017-03-08     NA
## 2017-03-09     NA
## 2017-03-10     NA
## 2017-03-13     NA
## 2017-03-14     NA
## 2017-03-15     NA
## 2017-03-16     NA
## 2017-03-17     NA
## 2017-03-20     NA
## 2017-03-21     NA
## 2017-03-22     NA
## 2017-03-23     NA
## 2017-03-24     NA
## 2017-03-27     NA
## 2017-03-28     NA
## 2017-03-29     NA
## 2017-03-30     NA
## 2017-03-31     NA
## 2017-04-05     NA
## 2017-04-06     NA
## 2017-04-07     NA
## 2017-04-10     NA
## 2017-04-11     NA
## 2017-04-12     NA
## 2017-04-13     NA
## 2017-04-14     NA
## 2017-04-17     NA
## 2017-04-18     NA
## 2017-04-19     NA
## 2017-04-20     NA
## 2017-04-21     NA
## 2017-04-24     NA
## 2017-04-25     NA
## 2017-04-26     NA
## 2017-04-27     NA
## 2017-04-28     NA
## 2017-05-02     NA
## 2017-05-03     NA
## 2017-05-04     NA
## 2017-05-05     NA
## 2017-05-08     NA
## 2017-05-09     NA
## 2017-05-10     NA
## 2017-05-11     NA
## 2017-05-12     NA
## 2017-05-15     NA
## 2017-05-16     NA
## 2017-05-17     NA
## 2017-05-18     NA
## 2017-05-19     NA
## 2017-05-22     NA
## 2017-05-23     NA
## 2017-05-24     NA
## 2017-05-25     NA
## 2017-05-26     NA
## 2017-05-31     NA
## 2017-06-01     NA
## 2017-06-02     NA
## 2017-06-03     NA
## 2017-06-05     NA
## 2017-06-06     NA
## 2017-06-07     NA
## 2017-06-08     NA
## 2017-06-09     NA
## 2017-06-12     NA
## 2017-06-13     NA
## 2017-06-14     NA
## 2017-06-15     NA
## 2017-06-16     NA
## 2017-06-19     NA
## 2017-06-20     NA
## 2017-06-21     NA
## 2017-06-22     NA
## 2017-06-23     NA
## 2017-06-26     NA
## 2017-06-27     NA
## 2017-06-28     NA
## 2017-06-29     NA
## 2017-06-30     NA
## 2017-07-03     NA
## 2017-07-04     NA
## 2017-07-05     NA
## 2017-07-06     NA
## 2017-07-07     NA
## 2017-07-10     NA
## 2017-07-11     NA
## 2017-07-12     NA
## 2017-07-13     NA
## 2017-07-14     NA
## 2017-07-17     NA
## 2017-07-18     NA
## 2017-07-19     NA
## 2017-07-20     NA
## 2017-07-21     NA
## 2017-07-24     NA
## 2017-07-25     NA
## 2017-07-26     NA
## 2017-07-27     NA
## 2017-07-28     NA
## 2017-07-31     NA
## 2017-08-01     NA
## 2017-08-02     NA
## 2017-08-03     NA
## 2017-08-04     NA
## 2017-08-07     NA
## 2017-08-08     NA
## 2017-08-09     NA
## 2017-08-10     NA
## 2017-08-11     NA
## 2017-08-14     NA
## 2017-08-15     NA
## 2017-08-16     NA
## 2017-08-17     NA
## 2017-08-18     NA
## 2017-08-21     NA
## 2017-08-22     NA
## 2017-08-23     NA
## 2017-08-24     NA
## 2017-08-25     NA
## 2017-08-28     NA
## 2017-08-29     NA
## 2017-08-30     NA
## 2017-08-31     NA
## 2017-09-01     NA
## 2017-09-04     NA
## 2017-09-05     NA
## 2017-09-06     NA
## 2017-09-07     NA
## 2017-09-08     NA
## 2017-09-11     NA
## 2017-09-12     NA
## 2017-09-13     NA
## 2017-09-14     NA
## 2017-09-15     NA
## 2017-09-18     NA
## 2017-09-19     NA
## 2017-09-20     NA
## 2017-09-21     NA
## 2017-09-22     NA
## 2017-09-25     NA
## 2017-09-26     NA
## 2017-09-27     NA
## 2017-09-28     NA
## 2017-09-29     NA
## 2017-09-30     NA
## 2017-10-02     NA
## 2017-10-03     NA
## 2017-10-05     NA
## 2017-10-06     NA
## 2017-10-11     NA
## 2017-10-12     NA
## 2017-10-13     NA
## 2017-10-16     NA
## 2017-10-17     NA
## 2017-10-18     NA
## 2017-10-19     NA
## 2017-10-20     NA
## 2017-10-23     NA
## 2017-10-24     NA
## 2017-10-25     NA
## 2017-10-26     NA
## 2017-10-27     NA
## 2017-10-30     NA
## 2017-10-31     NA
## 2017-11-01     NA
## 2017-11-02     NA
## 2017-11-03     NA
## 2017-11-06     NA
## 2017-11-07     NA
## 2017-11-08     NA
## 2017-11-09     NA
## 2017-11-10     NA
## 2017-11-13     NA
## 2017-11-14     NA
## 2017-11-15     NA
## 2017-11-16     NA
## 2017-11-17     NA
## 2017-11-20     NA
## 2017-11-21     NA
## 2017-11-22     NA
## 2017-11-23     NA
## 2017-11-24     NA
## 2017-11-27     NA
## 2017-11-28     NA
## 2017-11-29     NA
## 2017-11-30     NA
## 2017-12-01     NA
## 2017-12-04     NA
## 2017-12-05     NA
## 2017-12-06     NA
## 2017-12-07     NA
## 2017-12-08     NA
## 2017-12-11     NA
## 2017-12-12     NA
## 2017-12-13     NA
## 2017-12-14     NA
## 2017-12-15     NA
## 2017-12-18     NA
## 2017-12-19     NA
## 2017-12-20     NA
## 2017-12-21     NA
## 2017-12-22     NA
## 2017-12-25     NA
## 2017-12-26     NA
## 2017-12-27     NA
## 2017-12-28     NA
## 2017-12-29     NA
## 2018-01-02     NA
## 2018-01-03     NA
## 2018-01-04     NA
## 2018-01-05     NA
## 2018-01-08     NA
## 2018-01-09     NA
## 2018-01-10     NA
## 2018-01-11     NA
## 2018-01-12     NA
## 2018-01-15     NA
## 2018-01-16     NA
## 2018-01-17     NA
## 2018-01-18     NA
## 2018-01-19     NA
## 2018-01-22     NA
## 2018-01-23     NA
## 2018-01-24     NA
## 2018-01-25     NA
## 2018-01-26     NA
## 2018-01-29     NA
## 2018-01-30     NA
## 2018-01-31     NA
## 2018-02-01     NA
## 2018-02-02     NA
## 2018-02-05     NA
## 2018-02-06     NA
## 2018-02-07     NA
## 2018-02-08     NA
## 2018-02-09     NA
## 2018-02-12     NA
## 2018-02-21     NA
## 2018-02-22     NA
## 2018-02-23     NA
## 2018-02-26     NA
## 2018-02-27     NA
## 2018-03-01     NA
## 2018-03-02     NA
## 2018-03-05     NA
## 2018-03-06     NA
## 2018-03-07     NA
## 2018-03-08     NA
## 2018-03-09     NA
## 2018-03-12     NA
## 2018-03-13     NA
## 2018-03-14     NA
## 2018-03-15     NA
## 2018-03-16     NA
## 2018-03-19     NA
## 2018-03-20     NA
## 2018-03-21     NA
## 2018-03-22     NA
## 2018-03-23     NA
## 2018-03-26     NA
## 2018-03-27     NA
## 2018-03-28     NA
## 2018-03-29     NA
## 2018-03-30     NA
## 2018-03-31     NA
## 2018-04-02     NA
## 2018-04-03     NA
## 2018-04-09     NA
## 2018-04-10     NA
## 2018-04-11     NA
## 2018-04-12     NA
## 2018-04-13     NA
## 2018-04-16     NA
## 2018-04-17     NA
## 2018-04-18     NA
## 2018-04-19     NA
## 2018-04-20     NA
## 2018-04-23     NA
## 2018-04-24     NA
## 2018-04-25     NA
## 2018-04-26     NA
## 2018-04-27     NA
## 2018-04-30     NA
## 2018-05-02     NA
## 2018-05-03     NA
## 2018-05-04     NA
## 2018-05-07     NA
## 2018-05-08     NA
## 2018-05-09     NA
## 2018-05-10     NA
## 2018-05-11     NA
## 2018-05-14     NA
## 2018-05-15     NA
## 2018-05-16     NA
## 2018-05-17     NA
## 2018-05-18     NA
## 2018-05-21     NA
## 2018-05-22     NA
## 2018-05-23     NA
## 2018-05-24     NA
## 2018-05-25     NA
## 2018-05-28     NA
## 2018-05-29     NA
## 2018-05-30     NA
## 2018-05-31     NA
## 2018-06-01     NA
## 2018-06-04     NA
## 2018-06-05     NA
## 2018-06-06     NA
## 2018-06-07     NA
## 2018-06-08     NA
## 2018-06-11     NA
## 2018-06-12     NA
## 2018-06-13     NA
## 2018-06-14     NA
## 2018-06-15     NA
## 2018-06-19     NA
## 2018-06-20     NA
## 2018-06-21     NA
## 2018-06-22     NA
## 2018-06-25     NA
## 2018-06-26     NA
## 2018-06-27     NA
## 2018-06-28     NA
## 2018-06-29     NA
## 2018-07-02     NA
## 2018-07-03     NA
## 2018-07-04     NA
## 2018-07-05     NA
## 2018-07-06     NA
## 2018-07-09     NA
## 2018-07-10     NA
## 2018-07-11     NA
## 2018-07-12     NA
## 2018-07-13     NA
## 2018-07-16     NA
## 2018-07-17     NA
## 2018-07-18     NA
## 2018-07-19     NA
## 2018-07-20     NA
## 2018-07-23     NA
## 2018-07-24     NA
## 2018-07-25     NA
## 2018-07-26     NA
## 2018-07-27     NA
## 2018-07-30     NA
## 2018-07-31     NA
## 2018-08-01     NA
## 2018-08-02     NA
## 2018-08-03     NA
## 2018-08-06     NA
## 2018-08-07     NA
## 2018-08-08     NA
## 2018-08-09     NA
## 2018-08-10     NA
## 2018-08-13     NA
## 2018-08-14     NA
## 2018-08-15     NA
## 2018-08-16     NA
## 2018-08-17     NA
## 2018-08-20     NA
## 2018-08-21     NA
## 2018-08-22     NA
## 2018-08-23     NA
## 2018-08-24     NA
## 2018-08-27     NA
## 2018-08-28     NA
## 2018-08-29     NA
## 2018-08-30     NA
## 2018-08-31     NA
## 2018-09-03     NA
## 2018-09-04     NA
## 2018-09-05     NA
## 2018-09-06     NA
## 2018-09-07     NA
## 2018-09-10     NA
## 2018-09-11     NA
## 2018-09-12     NA
## 2018-09-13     NA
## 2018-09-14     NA
## 2018-09-17     NA
## 2018-09-18     NA
## 2018-09-19     NA
## 2018-09-20     NA
## 2018-09-21     NA
## 2018-09-25     NA
## 2018-09-26     NA
## 2018-09-27     NA
## 2018-09-28     NA
## 2018-10-01     NA
## 2018-10-02     NA
## 2018-10-03     NA
## 2018-10-04     NA
## 2018-10-05     NA
## 2018-10-08     NA
## 2018-10-09     NA
## 2018-10-11     NA
## 2018-10-12     NA
## 2018-10-15     NA
## 2018-10-16     NA
## 2018-10-17     NA
## 2018-10-18     NA
## 2018-10-19     NA
## 2018-10-22     NA
## 2018-10-23     NA
## 2018-10-24     NA
## 2018-10-25     NA
## 2018-10-26     NA
## 2018-10-29     NA
## 2018-10-30     NA
## 2018-10-31     NA
## 2018-11-01     NA
## 2018-11-02     NA
## 2018-11-05     NA
## 2018-11-06     NA
## 2018-11-07     NA
## 2018-11-08     NA
## 2018-11-09     NA
## 2018-11-12     NA
## 2018-11-13     NA
## 2018-11-14     NA
## 2018-11-15     NA
## 2018-11-16     NA
## 2018-11-19     NA
## 2018-11-20     NA
## 2018-11-21     NA
## 2018-11-22     NA
## 2018-11-23     NA
## 2018-11-26     NA
## 2018-11-27     NA
## 2018-11-28     NA
## 2018-11-29     NA
## 2018-11-30     NA
## 2018-12-03     NA
## 2018-12-04     NA
## 2018-12-05     NA
## 2018-12-06     NA
## 2018-12-07     NA
## 2018-12-10     NA
## 2018-12-11     NA
## 2018-12-12     NA
## 2018-12-13     NA
## 2018-12-14     NA
## 2018-12-17     NA
## 2018-12-18     NA
## 2018-12-19     NA
## 2018-12-20     NA
## 2018-12-21     NA
## 2018-12-22     NA
## 2018-12-24     NA
## 2018-12-25     NA
## 2018-12-26     NA
## 2018-12-27     NA
## 2018-12-28     NA

data1$prices<-prices

class(data1$dates)

## [1] "Date"

data1$execution.price = prices
data1$weight[] = 1
buy.hold.00646 <- bt.run.share(data1, clean.signal=F, trade.summary = TRUE)

## Latest weights :
##            prices
## 2018-12-28    100
## 
## Performance summary :
##  CAGR    Best    Worst   
##  5.7 3.7 -3.8    

buy.hold.00646 <-bt.run(data1)

## Latest weights :
##            prices
## 2018-12-28    100
## 
## Performance summary :
##  CAGR    Best    Worst   
##  5.7 3.7 -3.8    

讀取sma 200天的資料。

prices<-data1$prices
sma200_646<-SMA(prices, 200)
head(sma200_646, 201)

##                SMA
## 2015-12-14      NA
## 2015-12-15      NA
## 2015-12-16      NA
## 2015-12-17      NA
## 2015-12-18      NA
## 2015-12-21      NA
## 2015-12-22      NA
## 2015-12-23      NA
## 2015-12-24      NA
## 2015-12-25      NA
## 2015-12-28      NA
## 2015-12-29      NA
## 2015-12-30      NA
## 2015-12-31      NA
## 2016-01-04      NA
## 2016-01-05      NA
## 2016-01-06      NA
## 2016-01-07      NA
## 2016-01-08      NA
## 2016-01-11      NA
## 2016-01-12      NA
## 2016-01-13      NA
## 2016-01-14      NA
## 2016-01-15      NA
## 2016-01-18      NA
## 2016-01-19      NA
## 2016-01-20      NA
## 2016-01-21      NA
## 2016-01-22      NA
## 2016-01-25      NA
## 2016-01-26      NA
## 2016-01-27      NA
## 2016-01-28      NA
## 2016-01-29      NA
## 2016-01-30      NA
## 2016-02-01      NA
## 2016-02-02      NA
## 2016-02-03      NA
## 2016-02-15      NA
## 2016-02-16      NA
## 2016-02-17      NA
## 2016-02-18      NA
## 2016-02-19      NA
## 2016-02-22      NA
## 2016-02-23      NA
## 2016-02-24      NA
## 2016-02-25      NA
## 2016-02-26      NA
## 2016-03-01      NA
## 2016-03-02      NA
## 2016-03-03      NA
## 2016-03-04      NA
## 2016-03-07      NA
## 2016-03-08      NA
## 2016-03-09      NA
## 2016-03-10      NA
## 2016-03-11      NA
## 2016-03-14      NA
## 2016-03-15      NA
## 2016-03-16      NA
## 2016-03-17      NA
## 2016-03-18      NA
## 2016-03-21      NA
## 2016-03-22      NA
## 2016-03-23      NA
## 2016-03-24      NA
## 2016-03-25      NA
## 2016-03-28      NA
## 2016-03-29      NA
## 2016-03-30      NA
## 2016-03-31      NA
## 2016-04-01      NA
## 2016-04-06      NA
## 2016-04-07      NA
## 2016-04-08      NA
## 2016-04-11      NA
## 2016-04-12      NA
## 2016-04-13      NA
## 2016-04-14      NA
## 2016-04-15      NA
## 2016-04-18      NA
## 2016-04-19      NA
## 2016-04-20      NA
## 2016-04-21      NA
## 2016-04-22      NA
## 2016-04-25      NA
## 2016-04-26      NA
## 2016-04-27      NA
## 2016-04-28      NA
## 2016-04-29      NA
## 2016-05-03      NA
## 2016-05-04      NA
## 2016-05-05      NA
## 2016-05-06      NA
## 2016-05-09      NA
## 2016-05-10      NA
## 2016-05-11      NA
## 2016-05-12      NA
## 2016-05-13      NA
## 2016-05-16      NA
## 2016-05-17      NA
## 2016-05-18      NA
## 2016-05-19      NA
## 2016-05-20      NA
## 2016-05-23      NA
## 2016-05-24      NA
## 2016-05-25      NA
## 2016-05-26      NA
## 2016-05-27      NA
## 2016-05-30      NA
## 2016-05-31      NA
## 2016-06-01      NA
## 2016-06-02      NA
## 2016-06-03      NA
## 2016-06-04      NA
## 2016-06-06      NA
## 2016-06-07      NA
## 2016-06-08      NA
## 2016-06-13      NA
## 2016-06-14      NA
## 2016-06-15      NA
## 2016-06-16      NA
## 2016-06-17      NA
## 2016-06-20      NA
## 2016-06-21      NA
## 2016-06-22      NA
## 2016-06-23      NA
## 2016-06-24      NA
## 2016-06-27      NA
## 2016-06-28      NA
## 2016-06-29      NA
## 2016-06-30      NA
## 2016-07-01      NA
## 2016-07-04      NA
## 2016-07-05      NA
## 2016-07-06      NA
## 2016-07-07      NA
## 2016-07-11      NA
## 2016-07-12      NA
## 2016-07-13      NA
## 2016-07-14      NA
## 2016-07-15      NA
## 2016-07-18      NA
## 2016-07-19      NA
## 2016-07-20      NA
## 2016-07-21      NA
## 2016-07-22      NA
## 2016-07-25      NA
## 2016-07-26      NA
## 2016-07-27      NA
## 2016-07-28      NA
## 2016-07-29      NA
## 2016-08-01      NA
## 2016-08-02      NA
## 2016-08-03      NA
## 2016-08-04      NA
## 2016-08-05      NA
## 2016-08-08      NA
## 2016-08-09      NA
## 2016-08-10      NA
## 2016-08-11      NA
## 2016-08-12      NA
## 2016-08-15      NA
## 2016-08-16      NA
## 2016-08-17      NA
## 2016-08-18      NA
## 2016-08-19      NA
## 2016-08-22      NA
## 2016-08-23      NA
## 2016-08-24      NA
## 2016-08-25      NA
## 2016-08-26      NA
## 2016-08-29      NA
## 2016-08-30      NA
## 2016-08-31      NA
## 2016-09-01      NA
## 2016-09-02      NA
## 2016-09-05      NA
## 2016-09-06      NA
## 2016-09-07      NA
## 2016-09-08      NA
## 2016-09-09      NA
## 2016-09-10      NA
## 2016-09-12      NA
## 2016-09-13      NA
## 2016-09-14      NA
## 2016-09-19      NA
## 2016-09-20      NA
## 2016-09-21      NA
## 2016-09-22      NA
## 2016-09-23      NA
## 2016-09-26      NA
## 2016-09-29      NA
## 2016-09-30      NA
## 2016-10-03      NA
## 2016-10-04      NA
## 2016-10-05      NA
## 2016-10-06      NA
## 2016-10-07      NA
## 2016-10-11 19.8460
## 2016-10-12 19.8486

data1$weight[] <- iif(prices >= sma200_646, 1, 0)
sma200_646.00646 <- bt.run(data1, trade.summary=T) 

## Latest weights :
##            prices
## 2018-12-28      0
## 
## Performance summary :
##  CAGR    Best    Worst   
##  3.5 2.7 -3.8    

讀取sma 50天的資料。

sma646<-SMA(prices, 50)
head(sma646, 51)

##                SMA
## 2015-12-14      NA
## 2015-12-15      NA
## 2015-12-16      NA
## 2015-12-17      NA
## 2015-12-18      NA
## 2015-12-21      NA
## 2015-12-22      NA
## 2015-12-23      NA
## 2015-12-24      NA
## 2015-12-25      NA
## 2015-12-28      NA
## 2015-12-29      NA
## 2015-12-30      NA
## 2015-12-31      NA
## 2016-01-04      NA
## 2016-01-05      NA
## 2016-01-06      NA
## 2016-01-07      NA
## 2016-01-08      NA
## 2016-01-11      NA
## 2016-01-12      NA
## 2016-01-13      NA
## 2016-01-14      NA
## 2016-01-15      NA
## 2016-01-18      NA
## 2016-01-19      NA
## 2016-01-20      NA
## 2016-01-21      NA
## 2016-01-22      NA
## 2016-01-25      NA
## 2016-01-26      NA
## 2016-01-27      NA
## 2016-01-28      NA
## 2016-01-29      NA
## 2016-01-30      NA
## 2016-02-01      NA
## 2016-02-02      NA
## 2016-02-03      NA
## 2016-02-15      NA
## 2016-02-16      NA
## 2016-02-17      NA
## 2016-02-18      NA
## 2016-02-19      NA
## 2016-02-22      NA
## 2016-02-23      NA
## 2016-02-24      NA
## 2016-02-25      NA
## 2016-02-26      NA
## 2016-03-01      NA
## 2016-03-02 19.2538
## 2016-03-03 19.2522

data1$weight[] <- iif(prices >= sma646, 1, 0)
sma646.00646 <- bt.run(data1, trade.summary=T)

## Latest weights :
##            prices
## 2018-12-28      0
## 
## Performance summary :
##  CAGR    Best    Worst   
##  3.6 1.7 -3.8    

data1$weight[] <- iif(prices >= sma646, 1, -1)
sma646.00646.short <- bt.run(data1, trade.summary=T)

## Latest weights :
##            prices
## 2018-12-28   -100
## 
## Performance summary :
##  CAGR    Best    Worst   
##  0.8 3   -3.8    

第一、二張圖：

黑色線為SMA646 1.11，紅色線為SMA200_646 1.11，綠色線為SMA646_short 1.02，藍色線為BH 00646 1.19。並顯示出表格。

第三張圖：

顯示出Sharpe、DVR、Cagr、MaxDD四個的長條圖。

第四張圖：

顯示為表格。

models_3<-list("SMA646"= sma646.00646, 
               "sma200_646"= sma200_646.00646, 
               "SMA646_short" = sma646.00646.short, 
               "BH 00646" = buy.hold.00646)
strategy.performance.snapshoot(models_3, T)

## NULL

strategy.performance.snapshoot(models_3, control=list(comparison=T), sort.performance=T)

plotbt.strategy.sidebyside(models_3, return.table=T)

##            SMA646                    sma200_646               
## Period     "十二月2015 - 十二月2018" "十二月2015 - 十二月2018"
## Cagr       "3.64"                    "3.51"                   
## Sharpe     "0.57"                    "0.45"                   
## DVR        "0.41"                    "0.35"                   
## Volatility "6.78"                    "8.55"                   
## MaxDD      "-11.85"                  "-11.53"                 
## AvgDD      "-1.52"                   "-1.56"                  
## VaR        "-0.6"                    "-0.73"                  
## CVaR       "-1.07"                   "-1.48"                  
## Exposure   "65.78"                   "68.31"                  
##            SMA646_short              BH 00646                 
## Period     "十二月2015 - 十二月2018" "十二月2015 - 十二月2018"
## Cagr       "0.79"                    "5.75"                   
## Sharpe     "0.13"                    "0.57"                   
## DVR        "0.03"                    "0.51"                   
## Volatility "11.21"                   "11.2"                   
## MaxDD      "-18.9"                   "-18.67"                 
## AvgDD      "-4.52"                   "-1.64"                  
## VaR        "-1.04"                   "-1.09"                  
## CVaR       "-1.73"                   "-1.82"                  
## Exposure   "99.87"                   "99.87"

library(ggplot2)
all.00646<-merge.xts(sma646.00646$equity, 
                      sma646.00646.short$equity, 
                      sma200_646.00646$equity, 
                      buy.hold.00646$equity)
colnames(all.00646)<-c("sma646", "sma646 short", "sma200_646", "BH")
head(all.00646)

##            sma646 sma646 short sma200_646       BH
## 2015-12-14      1    1.0000000          1 1.000000
## 2015-12-15      1    0.9918117          1 1.008188
## 2015-12-16      1    0.9867771          1 1.013306
## 2015-12-17      1    0.9743178          1 1.026100
## 2015-12-18      1    0.9830648          1 1.016888
## 2015-12-21      1    0.9944440          1 1.005118

all.00646.long<-fortify(all.00646, melt=T)
head(all.00646.long)

##        Index Series Value
## 1 2015-12-14 sma646     1
## 2 2015-12-15 sma646     1
## 3 2015-12-16 sma646     1
## 4 2015-12-17 sma646     1
## 5 2015-12-18 sma646     1
## 6 2015-12-21 sma646     1

圖的標題為Cumulative returns of 00646s。

X軸為year，Y軸為cumulative returns。

橘色線為sma646，綠色線為sma646 short，藍色線為sma200_646，紫色線為BH。

title = "Cumulative returns of 00646s"
p3 = ggplot(all.00646.long, aes(x = Index, y = Value)) +
  geom_line(aes(linetype = Series, color = Series)) +
  #geom_point(aes(shape = Series))+
  xlab("year") + ylab("cumulative returns")+
  ggtitle(title)
p3