The Day of the Week and the Month of the Year Effects: Applications of Rolling Regressions in EVIEWS and MATLAB

Dossier / Travail , 2008 , 31 Pages , Note: 90.0%

Informatique - Informatique Appliquée à la Gestion

In this paper we examine the calendar anomalies in the stock market index of Athens. Specifically we examine the day of the week and the month of the year effects, where we expect negative or lower returns on Monday and the highest average returns on Friday for the day of the week effect and the higher average returns in January, concerning the January effect. For the period we examine we found insignificant returns on Monday, but significant positive and higher average returns on Friday. Also our results are consistent with the literature for the month of the year effect, where we find the highest average returns in January. Furthermore we estimate with ordinary least squares (OLS) and symmetric and asymmetric Generalized Autoregressive Conditional Heteroskedasticity (GARCH) rolling regressions and we conclude that the week day returns are not constant through the time period we examine but are changed. Specifically, while in the first half-period of the rolling regression there are negative returns on Mondays so we observe the day of the week effecting, in the last half-period of the rolling regression Friday presents the highest returns, but the lowest returns are reported on Tuesday and not on Monday, indicating a change shift in the pattern of the day of the week effect. Full programming routines of rolling regressions in EVIEWS and MATLAB software are described.

Inhaltsverzeichnis (Table of Contents)

• Introduction
• Methodology
  • The estimated model
  • Symmetric and Asymmetric Generalized Autoregressive Conditional Heteroskedasticity-GARCH
• Data
• Results

Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)

This study explores calendar anomalies in the Athens Stock Market Index, specifically focusing on the day of the week and month of the year effects. The paper aims to investigate whether there are consistent patterns in returns based on the day of the week and month of the year, and to assess the stability of these patterns over time.

• Day of the Week Effect
• Month of the Year Effect
• Rolling Regressions
• Generalized Autoregressive Conditional Heteroskedasticity (GARCH)
• Market Efficiency

Zusammenfassung der Kapitel (Chapter Summaries)

Introduction

This section provides an overview of previous research on calendar anomalies, particularly the day of the week and month of the year effects. The author summarizes findings from various studies, highlighting conflicting results and areas where further investigation is needed.

Methodology

This section outlines the models used to examine the day of the week and month of the year effects. Two theoretical models are presented, along with the rationale for using ordinary least squares (OLS) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models.

Data

The author describes the data used in the study, which includes daily and monthly data for the General Exchange Stock Market Index of Athens. The data period and source are specified.

Results

This section presents the results of the estimations using OLS and GARCH models. The author discusses the presence of ARCH effects and the need for GARCH models to address these issues. The results are summarized, highlighting the significant findings related to the Friday effect and the January effect.

Schlüsselwörter (Keywords)

The key concepts and themes explored in this paper include calendar anomalies, day of the week effect, month of the year effect, rolling regressions, GARCH models, market efficiency, Athens Stock Market Index, and the January effect.

• Note: 90.0%
• Auteur: Eleftherios Giovanis (Auteur)
• Année de publication: 2008
• Pages: 31
• N° de catalogue: V146637
• ISBN (ebook): 9783640575596
• ISBN (Livre): 9783640575763
• Langue: anglais
• mots-clé: stock returns, day of the week effect, month of the year effect, MATLAB, EVIEWS, rolling regressions