时间序列 R语言考试基本代码.docVIP

典型例题 HW2——5 HW3——3，4 HW4—— EXAM14,15——VAR library(quantmod) getSymbols(AAPL,from=2008-01-03,to=2015-01-28) dim(AAPL) head(AAPL) tail(AAPL) chartSeries(AAPL,theme=white) % Obtain time plot of closing price and trading volume da - read.csv(d-vix0411.csv,header=T)%有时候不用header参数，看head(da)的数据形式 da - read.table(d-vix0411.txt,header=T) AAPL.rtn=diff(log(AAPL$AAPL.Adjusted)) % Compute log returns unrate - as.numeric(UNRATE[,1]) % Use a regular vector, instead of an“xts”object library(fBasics) ts.plot(ibm,main=Monthly IBM simple returns: 1968-2015) % Time plot basicStats(ibm) apply(rtn,2,basicStats) ## This command says apply basicStats to every columns in rtn d4=density(ibm) plot(d4$x,d4$y,type=l,xlab=rtn,ylab=AAPL) ##density图 t.test(lnIBM) %% Test mean=0 vs mean .not. Zero也可以用basicStats命令去 计算 normalTest(lnIBM,method=’jb’) %testing normality of financial return series s3=skewness(lnIBM); T - length(lnIBM) tst - s3/sqrt(6/T) % test skewness pv - 2*pnorm(tst) %calculate p value k4 - kurtosis(lnIBM) tst - k4/sqrt(24/T) % test excess kurtosis mu - mean(sbux); v1 - var(sbux) %%prediction 或者可以用t-test的信息 lcl - mu-1.96*sqrt(v1) ucl - mu+1.96*sqrt(v1) c(lcl,ucl) correlation cor(sp,ibm) [1] 0.5785249 cor(sp,ibm,method=kendall) %random copy [1] 0.4172056 cor(sp,ibm,method=spearman) %rank correlation [1] 0.58267 cor(rank(ibm),rank(sp)) [1] 0.58267 x[1,] %show the first row of the data X[,4:5] %show the 4and5 columns of the data y=ts(x[,3],frequency=252,start=c(2004,1)) == Create a time-series object in R plot(y,type=l,xlab=year,ylab=rtn) par(mfcol=c(2,1)) == To put two plots on a single page hist(y,nclass=50)%直方图 tdx=(c(1:615)+11)/12+1959 %创建time plot 的横坐标 plot(tdx,xt,xlab=year,ylab=temp,type=l) plot(tdx[-1],zt,xlab=year,ylab=diff(temp),type=l) ##注意difference使得横坐标年份变化 int=cbind(x[300:914,4],y[,4]) == Line up the two TB rates acf(ibm) m1 - acf(ibm) name