Assignment no-: 6 BIS Lab

Assignments 1: Create a log of the return data for NIFTY INDEX data from 01 jan 2012 to 31 jan 2013.

Log return can be obtained using following formula

(Log S_t-Log S_t-1)/ Log S_t-1  or Log((S_t-S_t-1)/ S_t-1))

COMMANDS:

> niftydata<-read.csv(file.choose(),header=T)

> closing<-niftydata$Close

> local({pkg <- select.list(sort(.packages(all.available = TRUE)),graphics=TRUE)

+ if(nchar(pkg)) library(pkg, character.only=TRUE)})

‘tseries’ version: 0.10-30

‘tseries’ is a package for time series analysis and computational

finance.

See ‘library(help="tseries")’ for details.

> closing.ts<-ts(closing,frequency=252)

> lagtable <- cbind(closing.ts,z<-lag(closing.ts, k=-1),z1<-(closing.ts-lag(closing.ts, k=-1)))

> logreturn<-((log(closing.ts)-log(z))/log(z))

> logreturn

Time Series:

Start = c(1, 2)

End = c(2, 22)

Frequency = 252

[1] 3.239464e-03 -3.884187e-04 7.460649e-06 1.031566e-04 -1.790094e-04 -1.020756e-04 2.629635e-03 2.766672e-04 -7.219539e-04 8.448814e-04 1.910705e-04

[12] 2.235372e-03 -2.723447e-04 1.475328e-03 7.041325e-04 -5.460200e-05 1.869905e-03 7.045035e-04 1.047569e-03 -2.666119e-03 2.550488e-03 8.164967e-04

[23] 7.603225e-04 1.232348e-03 7.807907e-04 -5.770056e-04 7.185143e-04 9.547984e-04 -6.627921e-04 1.858701e-04 5.568074e-04 2.462872e-03 -2.099390e-04

[34] 8.866876e-04 8.895253e-04 -2.122643e-03 -4.659254e-04 -1.149537e-03 -3.216077e-03 2.064680e-03 2.098882e-04 -9.865220e-04 4.268778e-04 1.086513e-06

[45] -1.730561e-03 -1.287406e-03 -4.362502e-05 2.503809e-03 5.666613e-04 1.510141e-03 7.344260e-04 -1.787318e-03 -1.362292e-03 -1.341494e-03 3.945467e-04

[56] 1.976128e-03 -3.001079e-03 1.106098e-03 -2.095349e-03 1.320797e-03 -1.082815e-03 -3.583088e-04 2.605582e-03 4.911754e-04 8.865537e-04 -7.763192e-04

[67] -1.954136e-03 2.050752e-04 -3.735635e-04 1.112008e-03 -1.544616e-03 4.199823e-04 1.410639e-03 2.268949e-04 7.107020e-04 -9.115485e-04 -2.006700e-03

[78] 4.944683e-04 -4.627824e-04 -2.924186e-04 3.604002e-05 4.136487e-04 8.749252e-04 -2.003778e-04 -1.136619e-03 -2.310752e-03 6.271584e-04 -2.644486e-03

[89] -5.920671e-04 -2.150921e-04 -8.740499e-04 -5.045429e-04 8.361626e-04 -2.028488e-03 2.894189e-04 5.127588e-04 3.508262e-04 -1.097620e-03 -6.038190e-04

[100] 2.071895e-03 -2.390384e-05 1.549669e-03 1.047839e-04 -9.297326e-04 -6.308823e-04 -1.990929e-03 1.593334e-04 3.676528e-04 3.196962e-03 1.228327e-03

[111] 4.334883e-04 -3.300435e-04 1.425141e-03 1.269615e-04 -1.534822e-03 1.939456e-03 -1.715955e-03 9.131466e-04 3.826181e-04 1.011969e-03 -4.299203e-04

[122] -7.161795e-04 1.407172e-04 4.814369e-04 1.648873e-04 2.911816e-03 -6.630323e-06 2.064695e-04 3.216062e-04 5.429964e-04 -2.266406e-04 -9.200411e-04

[133] 1.542443e-03 -8.541758e-04 -1.571732e-03 -1.785871e-04 -6.722646e-04 -9.899153e-05 5.266673e-04 5.897855e-04 -8.404042e-04 -1.973141e-03 2.342661e-04

[144] -4.253547e-04 -1.536500e-03 1.314838e-03 2.273528e-03 6.544701e-04 2.565831e-04 -2.844336e-04 -2.695327e-04 1.487906e-03 1.189729e-03 2.837990e-05

[155] -3.289665e-04 -5.584902e-05 6.009196e-04 7.046999e-04 -3.770709e-04 7.271941e-05 1.180923e-03 -1.749869e-04 5.371437e-05 -6.170252e-04 -7.902596e-04

[166] -3.412252e-04 -1.026760e-03 5.995619e-04 -1.246938e-03 -1.054797e-04 4.490623e-04 -1.073482e-03 2.835242e-04 2.289030e-03 3.614632e-04 1.031874e-04

[177] 5.750264e-04 8.819401e-04 9.309863e-05 3.004835e-03 6.703951e-04 -2.056453e-04 -9.515204e-04 2.823943e-03 -4.387549e-04 8.771891e-05 -2.132743e-04

[188] -2.853809e-04 1.097066e-03 3.138052e-04 2.513622e-04 1.130621e-03 -8.135789e-04 -1.435064e-03 5.814561e-04 -1.067965e-03 1.139085e-03 -6.499572e-04

[199] 2.280491e-04 -8.009879e-04 2.507867e-04 1.188888e-03 -6.984126e-04 6.675458e-04 -5.217950e-04 2.821077e-04 -8.338676e-04 2.655438e-05 -1.391002e-03

[210] 4.503694e-04 5.212828e-04 1.074665e-03 1.318438e-04 4.087192e-04 7.185322e-04 -4.288652e-04 -1.061865e-03 -5.188074e-05 -3.413826e-04 -7.363699e-04

[221] -1.177061e-03 -5.512835e-05 3.121345e-06 8.964977e-04 2.668488e-04 -2.366583e-05 1.912506e-04 1.865662e-03 1.951756e-03 1.081009e-03 -1.745294e-04

[232] 3.586398e-04 2.198437e-04 5.918464e-04 -4.569753e-04 2.923626e-05 -1.969952e-04 -2.110634e-04 -7.163435e-04 5.522762e-04 -4.260227e-04 7.629091e-04

[243] 6.388874e-04 -2.565234e-04 -1.344742e-03 1.585997e-04 9.771520e-04 -6.943370e-04 7.484690e-04 -6.335935e-05 8.887682e-04 8.168833e-04 3.112892e-04

[254] 1.271069e-04 -5.312741e-04 2.550707e-04 -5.798537e-04 -5.490448e-05 -3.348281e-04 1.397952e-03 6.191517e-04 -1.042707e-03 7.130947e-04 4.782958e-04

[265] 3.383743e-04 -6.395637e-04 1.100716e-04 -6.648065e-04 1.050830e-03 2.834345e-06 -4.714611e-04 1.109914e-04 -3.988862e-04

> T<-252^0.5

> historicalvolatility<-sd(logreturn)*T

> historicalvolatility

[1] 0.01719952

Assignments 2: Do ACF plot and ADF.

Command:

> acf(logreturn)
> adf.test(logreturn)