'Homework 1-1'
## [1] "Homework 1-1"
data= read.table("homework1-1.txt",header = T)
str(data)
## 'data.frame': 2535 obs. of 5 variables:
## $ date: int 20010904 20010905 20010906 20010907 20010910 20010917 20010918 20010919 20010920 20010921 ...
## $ axp : num 0.000824 0.007682 -0.039477 -0.019274 0.01185 ...
## $ vw : num -0.00166 -0.00324 -0.02073 -0.01777 0.00351 ...
## $ ew : num -0.00571 -0.00893 -0.01419 -0.01148 -0.00737 ...
## $ sp : num -0.000565 -0.001059 -0.02239 -0.018637 0.006226 ...
library(fBasics)
## Loading required package: timeDate
## Loading required package: timeSeries
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:timeSeries':
##
## filter, lag
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
stats=basicStats(data)
stats
## date axp vw ew sp
## nobs 2.535000e+03 2535.000000 2535.000000 2535.000000 2535.000000
## NAs 0.000000e+00 0.000000 0.000000 0.000000 0.000000
## Minimum 2.001090e+07 -0.175949 -0.089762 -0.078240 -0.090350
## Maximum 2.011093e+07 0.206485 0.114889 0.107422 0.115800
## 1. Quartile 2.004032e+07 -0.009672 -0.005473 -0.004630 -0.005798
## 3. Quartile 2.009033e+07 0.010540 0.006212 0.006402 0.006117
## Mean 2.006285e+07 0.000534 0.000224 0.000626 0.000094
## Median 2.006092e+07 0.000000 0.000848 0.001429 0.000700
## Sum 5.085931e+10 1.353560 0.567996 1.586462 0.238869
## SE Mean 5.805029e+02 0.000524 0.000271 0.000240 0.000274
## LCL Mean 2.006171e+07 -0.000493 -0.000308 0.000155 -0.000442
## UCL Mean 2.006398e+07 0.001561 0.000756 0.001096 0.000631
## Variance 8.542535e+08 0.000695 0.000186 0.000146 0.000190
## Stdev 2.922762e+04 0.026368 0.013652 0.012080 0.013779
## Skewness -5.731000e-03 0.459773 -0.098318 -0.247410 0.008152
## Kurtosis -1.176804e+00 9.592053 7.982134 8.108428 8.532667
'homework 1-5'
## [1] "homework 1-5"
us.jp= read.table("d-fx-usjp-0711.txt", header = T)
uk.us= read.table("d-fx-ukus-0711.txt", header = T)
usjp=diff(log(us.jp$rate))
ukus=diff(log(uk.us$rate))
head(usjp)
## [1] 0.0062917032 -0.0025119330 -0.0042848207 -0.0023602810 0.0080693049
## [6] 0.0005858476
head(ukus)
## [1] -0.0121324830 -0.0028247881 -0.0071229784 0.0041354414 0.0007734949
## [6] -0.0034078620
basicStats(us.jp$rate)
## X..us.jp.rate
## nobs 1238.000000
## NAs 0.000000
## Minimum 75.720000
## Maximum 124.090000
## 1. Quartile 84.982500
## 3. Quartile 107.597500
## Mean 96.841397
## Median 93.840000
## Sum 119889.650000
## SE Mean 0.388126
## LCL Mean 96.079939
## UCL Mean 97.602856
## Variance 186.494854
## Stdev 13.656312
## Skewness 0.371610
## Kurtosis -1.025067
basicStats(uk.us$rate)
## X..uk.us.rate
## nobs 1238.000000
## NAs 0.000000
## Minimum 1.365800
## Maximum 2.110400
## 1. Quartile 1.562800
## 3. Quartile 1.966800
## Mean 1.717889
## Median 1.629950
## Sum 2126.747100
## SE Mean 0.005863
## LCL Mean 1.706386
## UCL Mean 1.729392
## Variance 0.042559
## Stdev 0.206299
## Skewness 0.416221
## Kurtosis -1.399183
usjp.log=log(us.jp$rate)
ukus.log=log(uk.us$rate)
rt=cbind(usjp.log, ukus.log)
m1=apply(rt,2,mean)
v1=cov(rt)
library(mnormt)
dim(rt)
## [1] 1238 2
x=rmnorm(1238, mean = m1, varcov = v1)
dim(x)
## [1] 1238 2
plot(x[,2],x[,1], xlab="usjp.log", ylab="ukus.log",cex=0.8)
