A Robust Analysis and Forecasting Framework for the Indian Mid Cap
Sector Using Times Series Decomposition Approach
- Jaydip Sen
Abstract
Prediction of stock prices using econometrics and machine learning based
approaches poses significant challenges to the research community since
the movement of stock prices are essentially random in its nature.
However, significant development and rapid evolution of sophisticated
and complex algorithms which are capable of analyzing large volume of
time series data, coupled with availability of high-performance hardware
and parallel computing architecture over the last decade, has made it
possible to efficiently process and effectively analyze voluminous stock
market time series data in an almost real-time environment. In this
paper, we propose a decomposition-based approach for time series
analysis of the Indian mid cap sector and also present a highly robust
and accurate prediction framework consisting of six forecasting methods
for predicting the future values of the time series. Extensive results
are presented on the performance of each forecasting method and the
reasons why a particular method has performed better than the others
have been critically analyzed.