library(dyn)
library(forecast)
data = read.csv("C:\\Documents and Settings\\Jaime Frade\\Desktop\\project\\4-17\\dataproj.csv", header=TRUE)
data1 = read.table("C:\\Documents and Settings\\Jaime Frade\\Desktop\\project\\4-17\\data7.txt", header=TRUE)
data1

attributes(data)

yr30_ts = ts(data$TCMNOMY30, start=c(2006, 4), frequency=365)
mon3LIB_ts = ts(data$EDM3, start=c(2006, 4), frequency=365)
mon3_ts = ts(data$TCMNOMM3, start=c(2006, 4), frequency=365)

at
LIBchange = ts(data1$change, start=c(2006, 4), frequency=365)
Spread = ts(data1$spread, start=c(2006, 4), frequency=365)

length(yr30_ts)
length(mon3LIB_ts)
length(mon3_ts)

par(mfrow=c(2,2))
plot.ts(yr30_ts, ylab="30 Year T-rate", main="Mar 06-Apr 08", col="red")
plot.ts(mon3LIB_ts, ylab="3 month LIBOR", main="Mar 06-Apr 08", col="red")
plot.ts(mon3_ts, ylab="3 month T-rate", main="Mar 06-Apr 08", col="red")

length(lag(mon3_ts,-1))


data = data.frame(mon3LIB_ts, yr30_ts, mon3_ts)

cor(data)

y=log(lag(mon3_ts,-2))

fit1 = dyn$lm(mon3LIB_ts~lag(mon3_ts,-7))
summary(fit1)
par(mfrow=c(2,2))
plot(fit1)

fit2 = dyn$lm(mon3LIB_ts~y)
summary(fit2)
par(mfrow=c(2,2))
plot(fit2)

fit3 = dyn$lm(LIBchange~Spread)
summary(fit3)
par(mfrow=c(2,2))
plot(fit3)



x = .011
y = sum(x*fit1$coef)
y
z = qt(0.975,260)
bm = sqrt(x)*z*0.3568/258
c(y-bm, y+bm)


x2 = .011
y2 = sum(x2*fit2$coef)
y2





par(mfrow=c(2,1))
plot(fit1$fitted.values, )
plot.ts(data2_ts)

par(mfrow=c(2,2))
plot(fit1)