Please use this identifier to cite or link to this item:
Author: Ιτσινές, Γεώργιος
Itsines, Georgios
Title: A note on predicting volatility.
Date Issued: 2014
Department: Διατμηματικό Πρόγραμμα Μεταπτυχιακών Σπουδών στην Οικονομική Επιστήμη
Supervisor: Παναγιωτίδης, Θεόδωρος
Panagiotidis, Theodoros
Abstract: This study presents the analytical examination of the information demand and its relationship with key elements of finance, like returns, trading volume and volatility. The research covers a sample of 29 of the largest stocks traded in the New York Stock Exchange (NYSE) and more specifically the constituents of the Dow Jones Industrial Average Index. The period of investigation is from January 2004 to December 2012. The data for the information demand variables (company name and ticker name), were downloaded from Google trends in a daily form, within the same time period. The analysis and the examination of the variables was made in two forms, first in a linear (Ordinary least squares and Quantile regression models) and second in a nonlinear estimation (GARCH, EGARCH and TGARCH).
Keywords: Volatility
Google trends
Information: Διπλωματική εργασία--Πανεπιστήμιο Μακεδονίας, Θεσσαλονίκη, 2014.
Appears in Collections:ΔΠΜΣ Οικονομική Επιστήμη (M)

Files in This Item:
File Description SizeFormat 
ItsinesGeorgiosMsc2014.pdf14.13 MBAdobe PDFView/Open

This item is licensed under a Creative Commons License Creative Commons