Exploratory Analysis of Functional Principal Components to Observe the Absorption of Election Sentiments in the Indian Stock Market

Abhinav Keshri and Charu Sharma

MPRA Paper from University Library of Munich, Germany

Abstract: An election year is expected to be of high volatility and movement in the stock markets, reflecting the aspirations and expectations of the common people from the upcoming government. In this paper, we explore Functional Principal Component Analysis to show how a big event like the general elections affects the stock market in the country. We take the Indian general election years of 2009, 2014, and 2019 and demonstrate how the unique circumstances before the elections affect the absorption of election sentiments and how this method can be used to find and foresee the effect of other such events through a detailed analysis of eigenfunctions.

Keywords: PCA; FPCA; General elections effect; Functional Data Analysis (search for similar items in EconPapers)
JEL-codes: C02 G14 (search for similar items in EconPapers)
Date: 2020-07-01
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/122325/1/MPRA_paper_122325.pdf original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:122325

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().