An Investigation of the Structural Characteristics of the Indian IT
Sector and the Capital Goods Sector -- An Application of the R
Programming in Time Series Decomposition and Forecasting
Abstract
Time series analysis and forecasting of stock market prices has been a
very active area of research over the last two decades. Availability of
extremely fast and parallel architecture of computing and sophisticated
algorithms has made it possible to extract, store, process and analyze
high volume stock market time series data very efficiently. In this
paper, we have used time series data of the two sectors of the Indian
economy – Information Technology (IT) and Capital Goods (CG) for the
period January 2009 – April 2016 and have studied the relationships of
these two time series with the time series of DJIA indices, NIFTY
indices and the US Dollar to Indian Rupees exchange rate. We established
by graphical and statistical tests that while the IT sector of India has
a strong association with DJIA indices and the Dollar to Rupee exchange
rate, the Indian CG sector exhibits a strong association with the NIFTY
indices. We contend that these observations corroborate our hypotheses
that the Indian IT sector is strongly coupled with the world economy
whereas the CG sector of India is the reflection of India’s internal
economic growth. We also present several models of regression between
the time series which exhibit strong association among them. The
effectiveness of these models have been demonstrated by very low values
of their forecasting errors.