Thesis Defence – Nafiz Emir Eğilli (MSFE)

Thesis Defence – Nafiz Emir Eğilli (MSFE)

Asst. Prof. Dr. Emrah Ahi– Advisor

Date: 13.05.2025

Time: 16:30

Location: Özyeğin University Altunizade Campus - Classroom ALT 101

“From Headlines To Predictions: Using VADER To Construct a Sentiment-Based Market Index”

Asst. Prof. Dr. Emrah Ahi, Özyeğin University

Asst. Prof. Dr. Levent Güntay, Özyeğin University

Asst. Prof. Dr. Rıza Ergün Arsal, İstanbil Bilgi University

Abstract:

This thesis introduces a sentiment-based decision-support model that transforms daily financial news headlines into structured quantitative signals for investment analysis. The study focuses on 43 actively traded stocks, primarily listed on the S&P 500 index, using a two-year dataset of daily headlines collected from publicly available sources. Sentiment scores are generated through a custom framework based on the VADER lexicon and converted into time series. These scores are then evaluated in three main areas: assessing predictive power using Ordinary Least Squares (OLS) regression models, ranking assets for sentiment-driven portfolio strategies, and serving as explanatory variables in asset pricing models such as Capital Asset Pricing Model (CAPM) and Fama-French. Results show that the model provides both statistical and practical value, outperforming market benchmarks under basic portfolio construction methods.

Keywords: Sentiment Analysis, Financial Headlines, Quantitative Finance, OLS Regression, Portfolio Construction, Fama-French Model

Bio:       

Nafiz Emir Eğilli is a graduate student in the Financial Engineering and Risk Management MSc program at Özyeğin University. He is currently working in the financial technology sector, focusing on quantitative analysis and data-driven decision-support systems. This thesis aligns with his professional work, combining sentiment analysis with traditional financial modeling to develop innovative investment tools.