Exploring the sentiment in Borsa Istanbul with deep learning

ATAK A.

Borsa Istanbul Review, cilt.23, 2023 (SSCI) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 23
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1016/j.bir.2023.12.010
  • Dergi Adı: Borsa Istanbul Review
  • Derginin Tarandığı İndeksler: Social Sciences Citation Index (SSCI), Scopus, EconLit, Directory of Open Access Journals
  • Anahtar Kelimeler: Asymmetric information, Emerging market, Endogeneity, Financial disclosure, FinBERT, FinRoBERTa, GMM, NLP, Sentiment, Tone
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

Sentiment analysis holds immense importance in finance and economics, addressing crucial issues such as principal–agent dynamics and information imbalances. The rise of natural language processing signifies a groundbreaking era in sentiment analysis, enabling the effective extraction of insights from textual data. Our research investigates the impact of qualitative financial data on firm valuation, utilizing sentiment extracted from annual financial disclosures, focusing on companies listed on the Borsa Istanbul Stock Exchange from 1998 to 2022. Employing a pre-trained transformer model, we develop sentiment indices and integrate textual data using a system-generalized method of moments. Our study aims to uncover how sentiment expressed in financial disclosures aids in mitigating challenges related to asymmetric information.