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@WilsonMongwe WilsonMongwe/Training.R
Last active Oct 6, 2015

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#### Author: Wilson Mongwe
#### Date: 05/10/2015
#### Website: www.wilsonmongwe.co.za
#### Title: Training the nueral network for the jump test
#### This code tests fro the presence of jumps using nueral networks
#### Training the neural network #####
trainingdata=matrix(0,nrow=5000,ncol=9)
for(i in 1:5000)
{
mu=runif(1,-1,1)
s=runif(1,0.01,0.7)
lam=runif(1,1,252)/252
mu_jump=runif(1,-1,1)
s_jump=runif(1,0.01,0.5)
delta=1/252
TotalTime=252*5
u = runif(1,0,1)
if(u<=0.5)
{
data=simulateJump(mu,s,lam,mu_jump,s_jump,TotalTime,delta,FALSE,1)
X= data[,1]#X is already log form
jump=1
}
else
{
data=simulateGBM(mu,s,TotalTime,delta)
X= data[,1]#X is already log form
jump=0
}
FirstMoment= mean(diff(X)^1)
SecondMoment= mean((diff(X)-FirstMoment)^2)
Skewness=mean((diff(X)-FirstMoment)^3)/SecondMoment^(3/2)
Kurtosis = (3-mean((diff(X)-FirstMoment)^4)/SecondMoment^2)/10
FirthMoment= mean((diff(X)-FirstMoment)^5)
SixthMoment= mean((diff(X)-FirstMoment)^6)
SeventhMoment= mean((diff(X)-FirstMoment)^7)
EigthMoment= mean((diff(X)-FirstMoment)^8)
#Column bind the data into one variable
trainingdata[i,]= cbind(FirstMoment,SecondMoment,Skewness,Kurtosis,
FirthMoment,SixthMoment,SeventhMoment,EigthMoment,jump)
cat("Iteration Number:\t",i, "\n")
}
colnames(trainingdata) <- c("FirstMoment", "SecondMoment","Skewness","Kurtosis",
"FirthMoment", "SixthMoment","SeventhMoment","EigthMoment","jump")
library("neuralnet")
#derivatives of the error function as stopping criteria.
jumpTest<- neuralnet(jump~FirstMoment+SecondMoment+Skewness
+Kurtosis+FirthMoment+SixthMoment+SeventhMoment
+EigthMoment,trainingdata[1:3000,], hidden=c(10),
threshold=0.001,rep=1,stepmax=1e9)
plot(jumpTest)
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