title: “Last Exam Work” author: “Sean Birchall” date: “5/3/2017” output: html_document
library(quantmod)## Loading required package: xts## Loading required package: zoo##
## Attaching package: 'zoo'## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric## Loading required package: TTR## Version 0.4-0 included new data defaults. See ?getSymbols.library(xts)
data.AMZN <- getSymbols("AMZN", from = "2010-12-31", to = "2013-12-31", auto.assign = FALSE)## As of 0.4-0, 'getSymbols' uses env=parent.frame() and
## auto.assign=TRUE by default.
##
## This behavior will be phased out in 0.5-0 when the call will
## default to use auto.assign=FALSE. getOption("getSymbols.env") and
## getOptions("getSymbols.auto.assign") are now checked for alternate defaults
##
## This message is shown once per session and may be disabled by setting
## options("getSymbols.warning4.0"=FALSE). See ?getSymbols for more details.data.YHOO <- getSymbols("YHOO", from = "2010-12-31", to = "2013-12-31", auto.assign = FALSE)
data.IBM <- getSymbols("IBM", from = "2010-12-31", to = "2013-12-31", auto.assign = FALSE)
data.GSPC <- getSymbols("^GSPC", from = "2010-12-31", to = "2013-12-31", auto.assign = FALSE)
multi <- data.AMZN[, 6] # Need to create a new data object before cbinding
multi <- cbind(multi, data.GSPC[, 6], data.YHOO[, 6], data.IBM[, 6])
period.ret<-multi[c(1,nrow(multi)),]
period.ret## AMZN.Adjusted GSPC.Adjusted YHOO.Adjusted IBM.Adjusted
## 2010-12-31 180.00 1257.64 16.63 125.8031
## 2013-12-31 398.79 1848.36 40.44 169.4835rets<-lapply(period.ret,Delt)
rets## $AMZN.Adjusted
## Delt.1.arithmetic
## 2010-12-31 NA
## 2013-12-31 1.2155
##
## $GSPC.Adjusted
## Delt.1.arithmetic
## 2010-12-31 NA
## 2013-12-31 0.4697051
##
## $YHOO.Adjusted
## Delt.1.arithmetic
## 2010-12-31 NA
## 2013-12-31 1.43175
##
## $IBM.Adjusted
## Delt.1.arithmetic
## 2010-12-31 NA
## 2013-12-31 0.3472126rets<-data.frame(rets)
rets## Delt.1.arithmetic Delt.1.arithmetic.1 Delt.1.arithmetic.2
## 2010-12-31 NA NA NA
## 2013-12-31 1.2155 0.4697051 1.43175
## Delt.1.arithmetic.3
## 2010-12-31 NA
## 2013-12-31 0.3472126rets<-rets[2,]*100
names(rets)<-paste(c("AMZN","GSPC","YHOO","IBM"))
rets## AMZN GSPC YHOO IBM
## 2013-12-31 121.55 46.97051 143.175 34.72126i.AMZN<-50000
i.GSPC<-10000
i.YHOO<-30000
i.IBM<-10000
w.AMZN<-i.AMZN/(i.AMZN+i.GSPC+i.YHOO+i.IBM)
w.AMZN## [1] 0.5w.GSPC<-i.GSPC/(i.AMZN+i.GSPC+i.YHOO+i.IBM)
w.GSPC## [1] 0.1w.YHOO<-i.YHOO/(i.AMZN+i.GSPC+i.YHOO+i.IBM)
w.YHOO## [1] 0.3w.IBM<-i.IBM/(i.AMZN+i.GSPC+i.YHOO+i.IBM)
w.IBM## [1] 0.1port.ret.4asset<-w.AMZN*rets$AMZN+w.GSPC*rets$GSPC+
w.YHOO*rets$YHOO+w.IBM*rets$IBM
port.ret.4asset## [1] 111.8967wgt<-c(0.5,0.1,0.3,0.1)
mat.wgt<-matrix(wgt,1)
mat.wgt## [,1] [,2] [,3] [,4]
## [1,] 0.5 0.1 0.3 0.1ret<-c(rets$AMZN,rets$GSPC,rets$YHOO,rets$IBM)
mat.ret<-matrix(ret,4)
mat.ret## [,1]
## [1,] 121.55001
## [2,] 46.97051
## [3,] 143.17499
## [4,] 34.72126port.ret<-mat.wgt%*%mat.ret
port.ret## [,1]
## [1,] 111.8967data.AMZN[c(1:3,nrow(data.AMZN)),]## AMZN.Open AMZN.High AMZN.Low AMZN.Close AMZN.Volume
## 2010-12-31 181.96 182.30 179.51 180.00 3451900
## 2011-01-03 181.37 186.00 181.21 184.22 5331400
## 2011-01-04 186.15 187.70 183.78 185.01 5031800
## 2013-12-31 394.58 398.83 393.80 398.79 1996500
## AMZN.Adjusted
## 2010-12-31 180.00
## 2011-01-03 184.22
## 2011-01-04 185.01
## 2013-12-31 398.79data.YHOO[c(1:3,nrow(data.YHOO)),]## YHOO.Open YHOO.High YHOO.Low YHOO.Close YHOO.Volume
## 2010-12-31 16.74 16.76 16.47 16.63 7754500
## 2011-01-03 16.81 16.94 16.67 16.75 17684000
## 2011-01-04 16.71 16.83 16.57 16.59 11092800
## 2013-12-31 40.17 40.50 40.00 40.44 8291400
## YHOO.Adjusted
## 2010-12-31 16.63
## 2011-01-03 16.75
## 2011-01-04 16.59
## 2013-12-31 40.44data.IBM[c(1:3,nrow(data.IBM)),]## IBM.Open IBM.High IBM.Low IBM.Close IBM.Volume IBM.Adjusted
## 2010-12-31 146.73 147.07 145.96 146.76 2969800 125.8031
## 2011-01-03 147.21 148.20 147.14 147.48 4603800 126.4203
## 2011-01-04 147.56 148.22 146.64 147.64 5060100 126.5574
## 2013-12-31 186.49 187.79 186.30 187.57 3619700 169.4835port<-data.AMZN[,c(4,6)]
port<-merge(port,data.YHOO[,c(4,6)])
port<-merge(port,data.IBM[,c(4,6)])
port[c(1:3,nrow(port)),]## AMZN.Close AMZN.Adjusted YHOO.Close YHOO.Adjusted IBM.Close
## 2010-12-31 180.00 180.00 16.63 16.63 146.76
## 2011-01-03 184.22 184.22 16.75 16.75 147.48
## 2011-01-04 185.01 185.01 16.59 16.59 147.64
## 2013-12-31 398.79 398.79 40.44 40.44 187.57
## IBM.Adjusted
## 2010-12-31 125.8031
## 2011-01-03 126.4203
## 2011-01-04 126.5574
## 2013-12-31 169.4835port$AMZN.ret<-Delt(port$AMZN.Adjusted)
port$YHOO.ret<-Delt(port$YHOO.Adjusted)
port$IBM.ret<-Delt(port$IBM.Adjusted)
port[c(1:3,nrow(port)),]## AMZN.Close AMZN.Adjusted YHOO.Close YHOO.Adjusted IBM.Close
## 2010-12-31 180.00 180.00 16.63 16.63 146.76
## 2011-01-03 184.22 184.22 16.75 16.75 147.48
## 2011-01-04 185.01 185.01 16.59 16.59 147.64
## 2013-12-31 398.79 398.79 40.44 40.44 187.57
## IBM.Adjusted AMZN.ret YHOO.ret IBM.ret
## 2010-12-31 125.8031 NA NA NA
## 2011-01-03 126.4203 0.023444450 0.007215935 0.004905977
## 2011-01-04 126.5574 0.004288318 -0.009552239 0.001084913
## 2013-12-31 169.4835 0.013778412 0.005970099 0.006222858port<-cbind(data.frame(index(port)),
data.frame(port))
names(port)[1]<-paste("date")
port[c(1:3,nrow(port)),]## date AMZN.Close AMZN.Adjusted YHOO.Close YHOO.Adjusted
## 2010-12-31 2010-12-31 180.00 180.00 16.63 16.63
## 2011-01-03 2011-01-03 184.22 184.22 16.75 16.75
## 2011-01-04 2011-01-04 185.01 185.01 16.59 16.59
## 2013-12-31 2013-12-31 398.79 398.79 40.44 40.44
## IBM.Close IBM.Adjusted AMZN.ret YHOO.ret IBM.ret
## 2010-12-31 146.76 125.8031 NA NA NA
## 2011-01-03 147.48 126.4203 0.023444450 0.007215935 0.004905977
## 2011-01-04 147.64 126.5574 0.004288318 -0.009552239 0.001084913
## 2013-12-31 187.57 169.4835 0.013778412 0.005970099 0.006222858port<-subset(port,
port$date>="2012-12-31" &
port$date<="2013-12-31")
port[c(1:3,nrow(port)),]## date AMZN.Close AMZN.Adjusted YHOO.Close YHOO.Adjusted
## 2012-12-31 2012-12-31 250.87 250.87 19.90 19.90
## 2013-01-02 2013-01-02 257.31 257.31 20.08 20.08
## 2013-01-03 2013-01-03 258.48 258.48 19.78 19.78
## 2013-12-31 2013-12-31 398.79 398.79 40.44 40.44
## IBM.Close IBM.Adjusted AMZN.ret YHOO.ret IBM.ret
## 2012-12-31 191.55 169.7850 0.023207448 0.020512821 0.009060744
## 2013-01-02 196.35 174.0396 0.025670679 0.009045226 0.025058746
## 2013-01-03 195.27 173.0823 0.004547095 -0.014940189 -0.005500391
## 2013-12-31 187.57 169.4835 0.013778412 0.005970099 0.006222858ewport<-port[c(1,8:10)]
ewport[c(1:3,nrow(ewport)),]## date AMZN.ret YHOO.ret IBM.ret
## 2012-12-31 2012-12-31 0.023207448 0.020512821 0.009060744
## 2013-01-02 2013-01-02 0.025670679 0.009045226 0.025058746
## 2013-01-03 2013-01-03 0.004547095 -0.014940189 -0.005500391
## 2013-12-31 2013-12-31 0.013778412 0.005970099 0.006222858names(ewport)<-paste(c("date","AMZN","YHOO","IBM"))
rownames(ewport)<-seq(1:nrow(ewport))
ewport[c(1:3,nrow(ewport)),]## date AMZN YHOO IBM
## 1 2012-12-31 0.023207448 0.020512821 0.009060744
## 2 2013-01-02 0.025670679 0.009045226 0.025058746
## 3 2013-01-03 0.004547095 -0.014940189 -0.005500391
## 253 2013-12-31 0.013778412 0.005970099 0.006222858ewport$AMZN<-1+ewport$AMZN
ewport$YHOO<-1+ewport$YHOO
ewport$IBM<-1+ewport$IBM
ewport[c(1:3,nrow(ewport)),]## date AMZN YHOO IBM
## 1 2012-12-31 1.023207 1.0205128 1.0090607
## 2 2013-01-02 1.025671 1.0090452 1.0250587
## 3 2013-01-03 1.004547 0.9850598 0.9944996
## 253 2013-12-31 1.013778 1.0059701 1.0062229ew.q1<-subset(ewport,
ewport$date>=as.Date("2012-12-31")&
ewport$date<=as.Date("2013-03-31"))
ew.q1[c(1:3,nrow(ew.q1)),]## date AMZN YHOO IBM
## 1 2012-12-31 1.023207 1.0205128 1.0090607
## 2 2013-01-02 1.025671 1.0090452 1.0250587
## 3 2013-01-03 1.004547 0.9850598 0.9944996
## 61 2013-03-28 1.004485 0.9974566 1.0114278ew.q1[1,2:4]<-1
ew.q1$AMZN<-cumprod(ew.q1$AMZN)
ew.q1$YHOO<-cumprod(ew.q1$YHOO)
ew.q1$IBM<-cumprod(ew.q1$IBM)
ew.q1[c(1:3,nrow(ew.q1)),]## date AMZN YHOO IBM
## 1 2012-12-31 1.000000 1.0000000 1.000000
## 2 2013-01-02 1.025671 1.0090452 1.025059
## 3 2013-01-03 1.030335 0.9939699 1.019421
## 61 2013-03-28 1.062263 1.1824121 1.118235num.sec<-3
ew.q1$AMZN.idx<-(1/num.sec)*ew.q1$AMZN
ew.q1$YHOO.idx<-(1/num.sec)*ew.q1$YHOO
ew.q1$IBM.idx<-(1/num.sec)*ew.q1$IBM
ew.q1[c(1:3,nrow(ew.q1)),]## date AMZN YHOO IBM AMZN.idx YHOO.idx IBM.idx
## 1 2012-12-31 1.000000 1.0000000 1.000000 0.3333333 0.3333333 0.3333333
## 2 2013-01-02 1.025671 1.0090452 1.025059 0.3418902 0.3363484 0.3416862
## 3 2013-01-03 1.030335 0.9939699 1.019421 0.3434448 0.3313233 0.3398068
## 61 2013-03-28 1.062263 1.1824121 1.118235 0.3540878 0.3941374 0.3727449q1.val<-data.frame(rowSums(ew.q1[,5:7]))
q1.val[c(1:3,nrow(q1.val)),]## [1] 1.000000 1.019925 1.014575 1.120970names(q1.val)<-paste("port.val")
q1.val$date<-ew.q1$date
q1.val[c(1:3,nrow(q1.val)),]## port.val date
## 1 1.000000 2012-12-31
## 2 1.019925 2013-01-02
## 3 1.014575 2013-01-03
## 61 1.120970 2013-03-28q2.inv<-q1.val[nrow(q1.val),1]
q2.inv## [1] 1.12097ew.q2<-subset(ewport,
ewport$date>=as.Date("2013-04-01")&
ewport$date<=as.Date("2013-06-30"))
ew.q2[c(1:3,nrow(ew.q2)),]## date AMZN YHOO IBM
## 62 2013-04-01 0.9816878 0.9987250 0.9956868
## 63 2013-04-02 1.0065365 1.0119149 1.0093229
## 64 2013-04-03 0.9837080 0.9831791 0.9920694
## 125 2013-06-28 1.0005045 0.9866510 0.9767953ew.q2$AMZN<-cumprod(ew.q2$AMZN)
ew.q2$YHOO<-cumprod(ew.q2$YHOO)
ew.q2$IBM<-cumprod(ew.q2$IBM)
ew.q2[c(1:3,nrow(ew.q2)),]## date AMZN YHOO IBM
## 62 2013-04-01 0.9816878 0.9987250 0.9956868
## 63 2013-04-02 0.9881047 1.0106247 1.0049695
## 64 2013-04-03 0.9720065 0.9936251 0.9969995
## 125 2013-06-28 1.0420279 1.0679982 0.9001677ew.q2$AMZN.idx<-(q2.inv/num.sec)*ew.q2$AMZN
ew.q2$YHOO.idx<-(q2.inv/num.sec)*ew.q2$YHOO
ew.q2$IBM.idx<-(q2.inv/num.sec)*ew.q2$IBM
ew.q2[c(1:3,nrow(ew.q2)),]## date AMZN YHOO IBM AMZN.idx YHOO.idx IBM.idx
## 62 2013-04-01 0.9816878 0.9987250 0.9956868 0.3668142 0.3731802 0.3720450
## 63 2013-04-02 0.9881047 1.0106247 1.0049695 0.3692119 0.3776267 0.3755136
## 64 2013-04-03 0.9720065 0.9936251 0.9969995 0.3631967 0.3712746 0.3725355
## 125 2013-06-28 1.0420279 1.0679982 0.9001677 0.3893607 0.3990646 0.3363537q2.val<-data.frame(rowSums(ew.q2[,5:7]))
q2.val[c(1:3,nrow(q2.val)),]## [1] 1.112039 1.122352 1.107007 1.124779names(q2.val)<-paste("port.val")
q2.val$date<-ew.q2$date
q2.val[c(1:3,nrow(q2.val)),]## port.val date
## 62 1.112039 2013-04-01
## 63 1.122352 2013-04-02
## 64 1.107007 2013-04-03
## 125 1.124779 2013-06-28#
q3.inv<-q2.val[nrow(q2.val),1]
q3.inv## [1] 1.124779ew.q3<-subset(ewport,
ewport$date>=as.Date("2013-07-01")&
ewport$date<=as.Date("2013-09-30"))
ew.q3[c(1:3,nrow(ew.q3)),]## date AMZN YHOO IBM
## 126 2013-07-01 1.0158810 1.0043773 1.0008895
## 127 2013-07-02 1.0057781 0.9900951 1.0011502
## 128 2013-07-03 1.0010573 1.0240096 1.0091384
## 189 2013-09-30 0.9893358 0.9886736 0.9906912ew.q3$AMZN<-cumprod(ew.q3$AMZN)
ew.q3$YHOO<-cumprod(ew.q3$YHOO)
ew.q3$IBM<-cumprod(ew.q3$IBM)
ew.q3[c(1:3,nrow(ew.q3)),]## date AMZN YHOO IBM
## 126 2013-07-01 1.015881 1.004377 1.0008895
## 127 2013-07-02 1.021751 0.994429 1.0020407
## 128 2013-07-03 1.022831 1.018305 1.0111977
## 189 2013-09-30 1.125860 1.319936 0.9738145ew.q3$AMZN.idx<-(q3.inv/num.sec)*ew.q3$AMZN
ew.q3$YHOO.idx<-(q3.inv/num.sec)*ew.q3$YHOO
ew.q3$IBM.idx<-(q3.inv/num.sec)*ew.q3$IBM
ew.q3[c(1:3,nrow(ew.q3)),]## date AMZN YHOO IBM AMZN.idx YHOO.idx IBM.idx
## 126 2013-07-01 1.015881 1.004377 1.0008895 0.3808805 0.3765675 0.3752598
## 127 2013-07-02 1.021751 0.994429 1.0020407 0.3830813 0.3728376 0.3756914
## 128 2013-07-03 1.022831 1.018305 1.0111977 0.3834863 0.3817893 0.3791246
## 189 2013-09-30 1.125860 1.319936 0.9738145 0.4221145 0.4948789 0.3651087q3.val<-data.frame(rowSums(ew.q3[,5:7]))
q3.val[c(1:3,nrow(q3.val)),]## [1] 1.132708 1.131610 1.144400 1.282102names(q3.val)<-paste("port.val")
q3.val$date<-ew.q3$date
q3.val[c(1:3,nrow(q3.val)),]## port.val date
## 126 1.132708 2013-07-01
## 127 1.131610 2013-07-02
## 128 1.144400 2013-07-03
## 189 1.282102 2013-09-30#
q4.inv<-q3.val[nrow(q3.val),1]
q4.inv## [1] 1.282102ew.q4<-subset(ewport,
ewport$date>=as.Date("2013-10-01")&
ewport$date<=as.Date("2013-12-31"))
ew.q4[c(1:3,nrow(ew.q4)),]## date AMZN YHOO IBM
## 190 2013-10-01 1.0265801 1.0343685 1.0064803
## 191 2013-10-02 0.9986291 0.9950451 0.9923812
## 192 2013-10-03 0.9820598 0.9923844 0.9940527
## 253 2013-12-31 1.0137784 1.0059701 1.0062229ew.q4$AMZN<-cumprod(ew.q4$AMZN)
ew.q4$YHOO<-cumprod(ew.q4$YHOO)
ew.q4$IBM<-cumprod(ew.q4$IBM)
ew.q4[c(1:3,nrow(ew.q4)),]## date AMZN YHOO IBM
## 190 2013-10-01 1.026580 1.034368 1.0064803
## 191 2013-10-02 1.025173 1.029243 0.9988120
## 192 2013-10-03 1.006781 1.021405 0.9928718
## 253 2013-12-31 1.275557 1.219174 1.0183461ew.q4$AMZN.idx<-(q4.inv/num.sec)*ew.q4$AMZN
ew.q4$YHOO.idx<-(q4.inv/num.sec)*ew.q4$YHOO
ew.q4$IBM.idx<-(q4.inv/num.sec)*ew.q4$IBM
ew.q4[c(1:3,nrow(ew.q4)),]## date AMZN YHOO IBM AMZN.idx YHOO.idx IBM.idx
## 190 2013-10-01 1.026580 1.034368 1.0064803 0.4387268 0.4420553 0.4301368
## 191 2013-10-02 1.025173 1.029243 0.9988120 0.4381253 0.4398650 0.4268597
## 192 2013-10-03 1.006781 1.021405 0.9928718 0.4302653 0.4365151 0.4243210
## 253 2013-12-31 1.275557 1.219174 1.0183461 0.5451312 0.5210352 0.4352078q4.val<-data.frame(rowSums(ew.q4[,5:7]))
q4.val[c(1:3,nrow(q4.val)),]## [1] 1.310919 1.304850 1.291101 1.501374names(q4.val)<-paste("port.val")
q4.val$date<-ew.q4$date
q4.val[c(1:3,nrow(q4.val)),]## port.val date
## 190 1.310919 2013-10-01
## 191 1.304850 2013-10-02
## 192 1.291101 2013-10-03
## 253 1.501374 2013-12-31ew.portval<-rbind(q1.val,q2.val,q3.val,q4.val)
ew.portval[c(1:3,nrow(ew.portval)),]## port.val date
## 1 1.000000 2012-12-31
## 2 1.019925 2013-01-02
## 3 1.014575 2013-01-03
## 253 1.501374 2013-12-31