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雷达卡
这里上传修改过的代码到论坛，同时上传压缩包。问这个问题的帖子应该还在R论坛吧。自己去搜索。
修改好的主程序代码，名字叫 mainCalculate.R 。
记得修改 setwd("E:/Mystudio/zhaotao011") # Set my working directory 这句代码，我有E盘这个文件夹，如果你没有也照样会出错，已经能运行，但是有一个警告，有缺失值。
不过不影响程序运行到最后，所以没有修改。
- #----------------------------------------------------------------------------
- # A demostration of R using
- #----------------------------------------------------------------------------
- setwd("E:/Mystudio/zhaotao011") # Set my working directory
- #----------------------------------------------------------------------------
- # Compile R script
- source("ma.R")
- source("ohlc.R")
- #----------------------------------------------------------------------------
- ### Chapter 1 ###
- library(quantmod) # Load the package
- getSymbols("AAPL") # Download daily prices of Apple stock from Yahoo
- dim(AAPL) # (dimension): See the size of the downloaded data.
- head(AAPL) # See the first 6 rows of the data
- tail(AAPL) # See the last 6 rows of the data
- chartSeries(AAPL,theme="white") # Plot the daily price and volume
- chartSeries(AAPL)#Not shown giving the same plot with black background.
- getSymbols("AAPL",from="2005-01-02", to="2010-12-31")
- head(AAPL)
- getSymbols("UNRATE",src="FRED")#Download unemployment rates from FRED.
- head(UNRATE)
- chartSeries(UNRATE,theme="white") # Plot monthly unemployment rates
- getSymbols("INTC",src="yahoo") # Download data from Google.
- head(INTC)
- getSymbols("^TNX") # Download CBOE 10-year Treasures Notes
- head(TNX)
- TNX<-na.fill(TNX,"extend")
- chartSeries(TNX,theme="white",TA=NULL) # Obtain plot without volume.
- library(fBasics) # Load package
- da=read.table('d-ibm-0110.txt',header=T) # Load text data with names.
- head(da) # See the first 6 rows
- dim(da) # Dimension of the data object "da".
- da <- read.table("d-vix0411.txt",header=T) # Load csv data with names.
- #
- library(quantmod)
- getSymbols("AAPL",from="2007-01-03",to="2011-12-02") #Specify period
- AAPL.rtn=diff(log(AAPL$AAPL.Adjusted)) # Compute log returns
- chartSeries(AAPL.rtn,theme="white")
- getSymbols("^TNX",from="2007-01-03",to="2011-12-02")
- TNX.rtn=diff(TNX$TNX.Adjusted) # Compute changes
- chartSeries(TNX.rtn,theme="white")
- getSymbols("DEXUSEU",src="FRED") #Obtain exchange rates from FRED
- head(DEXUSEU)
- tail(DEXUSEU)
- USEU.rtn=diff(log(DEXUSEU$DEXUSEU))
- chartSeries(DEXUSEU,theme="white")
- chartSeries(USEU.rtn,theme="white")
- #
- library(fBasics) # Load package
- da=read.table("d-mmm-0111.txt",header=T) # Load data
- # header=T means the first row of data file contains names.
- # deafult is no names.
- head(da) #Show the first 6 rows of data
- mmm=da[,2] # Obtain 3m simple returns
- basicStats(mmm) #Compute summary statistics
- mean(mmm)
- var(mmm)
- stdev(mmm) # standard deviation
- t.test(mmm) # Testing mean return = 0
- s3=skewness(mmm)
- T=length(mmm) # Sample size
- t3=s3/sqrt(6/T) # Skewness test
- pp=2*(1-pnorm(t3)) # Compute p-value
- s4=kurtosis(mmm)
- t4=s4/sqrt(24/T) # Kurtosis test
- normalTest(mmm,method='jb') # JB-test
- #
- library(fBasics)
- da=read.table("d-mmm-0111.txt",header=T) # Load data
- mmm=da[,2] # Locate 3M simple returns
- hist(mmm,nclass=30) # Histogram
- d1=density(mmm) # Obtain density estimate
- range(mmm) # Range of 3M returns
- x=seq(-.1,.1,.001) # Create a sequence of x with increment 0.001.
- y1=dnorm(x,mean(mmm),stdev(mmm))
- plot(d1$x,d1$y,xlab='rtn',ylab='density',type='l')
- lines(x,y1,lty=2)
- library(quantmod)
- getSymbols("AAPL",from="2011-01-03",to="2011-06-30")
- X=AAPL[,1:4] # Locate open, high, low, and close prices
- xx=cbind(as.numeric(X[,1]),as.numeric(X[,2]),as.numeric(X[,3]),as.numeric(X[,4]))
- #source("ohlc.R") # Compile the R script
- ohlc(xx,xl="days",yl="price",title="Apple Stock")
- #source("ma.R") # Compile R script
- getSymbols("AAPL",from="2010-01-02",to="2011-12-08")
- x1=as.numeric(AAPL$AAPL.Close) # Locate close price
- ma(x1,21)
- da=read.table("m-ibmsp-2611.txt",header=T)
- head(da)
- ibm=log(da$ibm+1) # Transform to log returns
- sp=log(da$sp+1)
- tdx=c(1:nrow(da))/12+1926 # Create time index
- par(mfcol=c(2,1))
- plot(tdx,ibm,xlab='year',ylab='lrtn',type='l')
- title(main='(a) IBM returns')
- plot(tdx,sp,xlab='year',ylab='lrtn',type='l') # X-axis first.
- title(main='(b) SP index')
- cor(ibm,sp) # Obtain sample correlation
- m1=lm(ibm~sp) # Fit the Market Model (linear model)
- summary(m1)
- plot(sp,ibm,cex=0.8) # Obtain scatter plot
- abline(0.008,.807) # Add the linear regression line
- #
- da=read.table("m-ibmsp-2611.txt",header=T) #Load data
- dim(da)
- ibm=log(da$ibm+1) # Compute log returns
- sp=log(da$sp+1)
- rt=cbind(ibm,sp) # Obtain bivariate returns
- m1=apply(rt,2,mean) # Obtain sample means
- v1=cov(rt) # Obtain sample covariance matrix
- m1
- v1
- library(mnormt) # Load package
- x=rmnorm(1029,mean=m1,varcov=v1) # Simulation
- dim(x)
- plot(x[,2],x[,1],xlab='sim-sp',ylab='sim-ibm',cex=0.8)
附件在这里，其实这个是那个作者论坛这本书里的代码，程序在 .tex 文本文件里。保存为 R 文件就可以。
不好意思，我下载这个文件夹的人的帖子时没仔细看，他的文件有里 .csv 文件，非常大。压缩后200多M，你们可以不下载。
这个程序已经可以运行，但是我最近很忙，忙很重要的代码。不方便论坛继续发帖修改程序读取他的数据演示一下。他的压缩文件太大，我无法上传。这里给论坛的这本书也有代码，复制我发的代码，保存他第一章的文件夹里，设定新的工作目录就可以运行。
An_Introduction_to_Analysis_of_Financial_Data_with_R 作者： Tsay
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