Public mood impacts stock price movement but not direction in turkiye
From Tweets to Trades: Analyzing the Influence of Public Mood over Stock Market Performance in Turkiye
Computation and Language
Summary
This study looks at whether the feelings expressed by people online in different topics relate to stock market changes in Turkey. The researchers found that while these moods don't predict whether the market goes up or down, they do relate to how big the price changes are. This connection is stronger when looking at longer time periods and varies depending on the topic of the posts and market events like elections. The study highlights that combining all moods without separating by topic can hide important details.
What this means in practice
- •For financial analysts: Incorporate domain-specific mood signals from social media to better assess the size of stock price movements in Turkish markets during varied market conditions.
- •For social media monitoring teams: Use fine-tuned language models to classify social media posts by topic for tracking public mood related to economic and financial communication.
Tested on one dataset.
Authors
Ece Elif Adak, Bertaç Şakir Şahin, Şaziye Betül Özateş
Abstract
Purpose: This study examines whether domain-specific public mood is associated with stock-market dynamics and whether these relationships vary across communication domains and market conditions. It distinguishes public mood from investor sentiment and investigates whether heterogeneous sources of public communication exhibit different relationships with market behaviour. Design: The study analyses 610,422 posts published by 176 curated X accounts between January 2022 and December 2023, covering Politics and Government, Economy and Finance, and Media and Society. Posts are classified using fine-tuned Turkish transformer models under three domain-specific and one pooled regime. Public mood measures are constructed at daily, weekly, and monthly frequencies and examined alongside BIST100 and BIST30 market measures using correlation, Granger causality, vector autoregression, and impulse response analyses across the full period and selected market conditions. Findings: Public mood is not associated with the direction of stock-market returns but is associated with the magnitude of price movements, particularly for Media and Society and pooled communication. These relationships become stronger at longer aggregation frequencies. Predictive relationships are concentrated in Economy and Finance communication, while their magnitude and direction vary across market conditions, particularly during the 2023 election period. The pooled measure largely reflects the most active communication domain. Originality: The study contributes to behavioral-finance research by incorporating communication - domain heterogeneity into the analysis of public mood and market dynamics. It also demonstrates how aggregating heterogeneous sources can obscure domain-specific relationships between public communication and financial markets.