ANALYSIS OF CBRT MONETARY POLICY PRESS RELEASES BASED ON COSINE SIMILARITY, TOPIC MODELING, AND SENTIMENTAL TONE

Öz

This study examines the monetary policy press releases issued by the Central Bank of the Republic of Türkiye (CBRT) between 2006 and 2024 using text analysis methods In the study, cosine similarity, Latent Dirichlet Allocation (LDA) subject modeling and sentiment analysis were performed using natural language processing (NLP) techniques. The cosine similarity analysis measures the consistency of the content between releases, while the LDA method identifies the thematic structure and key topics of the announcements. Sentiment analysis reveals the positive, negative, and neutral tone of the texts. The findings indicate that the CBRT's communication strategy evolves based on economic conditions and aims to guide market expectations. This study contributes to the literature by evaluating the economic impact of the language used in central bank communications.

Anahtar Kelimeler

• CBRT
• Cosine Similarity
• Latent Dirichlet Allocation
• Sentiment Analysis
• Natural Language Processing (NLP)
• Central Bank Communication

TCMB PARA POLİTİKASI BASIN DUYURULARININ KOSİNÜS BENZERLİĞİ, KONU MODELLEMESİ VE DUYGU TONU TEMELİNDE ANALİZİ

Öz

Bu çalışma, Türkiye Cumhuriyet Merkez Bankası'nın (TCMB) 2006-2024 yılları arasında yayımladığı para politikası basın duyurularını metin analizi yöntemleriyle incelemektedir. Çalışmada doğal dil işleme (NLP) teknikleri kullanılarak kosinüs benzerliği, Gizli Dirichlet Tahsisi (LDA) konu modellemesi ve duygu analizleri yapılmıştır. Kosinüs benzerliği analizi, duyurular arasındaki içerik tutarlılığını ölçerken, LDA yöntemi ile duyuruların tematik yapısı ve temel konuları belirlenmiştir. Duygu analizi ise metinlerin pozitif, negatif ve nötr tonlarını ortaya koymuştur. Sonuçlar, TCMB'nin iletişim stratejisinin ekonomik koşullara bağlı olarak değiştiğini ve piyasa beklentilerini yönlendirme amacı taşıdığını göstermektedir. Çalışma, merkez bankası iletişiminde kullanılan dilin ekonomik etkilerini değerlendirmesi bakımından literatüre katkı sunmaktadır.

Anahtar Kelimeler

• TCMB
• Kosinüs Benzerliği
• Gizli Dirichlet Tahsisi
• Duygu Analizi
• Doğal Dil İşleme (NLP)
• Merkez Bankası İletişimi

Kaynakça

1. Akbıyık, A. & Coşkun, E. (2013). Eğitsel sosyal yazılımların kabul ve kullanımına yönelik bir model. Online Academic Journal of Information Technology. 4(13), 39-62.
2. Akça, Y. & Özer, G. (2012). Teknoloji kabul model’inin kurumsal kaynak planlaması uygulamalarında kullanılması. Business and Economics Research Journal, 3(2), 79-96.
3. Acosta M. & Meade E. (2015). Hanging on Every Word: Semantic Analysis of the FOMC's Postmeeting Statement. Board of Governors of the Federal Reserve System (U.S.), FEDS Notes 2015-09-30.
4. Amaya D. & Filbien J-Y. (2015). The Similarity of ECB’s Communication. Finance Research Letters, Volume 13.
5. Apel M. & Grimaldi M.B. (2012). The Information Content of Central Bank Minutes. Sveriges Riksbank Working Paper Series, No. 261.
6. Armelius H. & Bertsch C. & Hull I. & Zhang X. (2018). Spread the Word: International Spillovers from Central Bank Communication. Sveriges Riksbank Research Paper Series, No. 357.
7. Bholat D. & Hansen S. & Santos P. & Schonhardt-Bailey C. (2015). Text Mining for Central Banks. https://www.bankofengland.co.uk/ccbs/text-mining-for-central-banks, Erişim Tarihi: 20.02.2024.
8. Blei D.M. & Ng A.Y. & Jordan M.I. (2003), Latent Dirichlet Allocation. Journal of Machine Learning Research 3 (2003) 993-1022.

9. Blinder A.S. & Ehrmann M. & Fratzscher M. & Haan J.D. & Jansen D.J. (2008). Central bank Communication and Monetary Policy: A Survey of Theory and Evidence. European Central Bank Working Paper Series, No. 898.
10. Boyacıoğlu E.Z. & Türksever E. & Adıgüzel T. & Taş H. & Ulu B. (2023). Faiz Kararı ile İlgili Makro Ekonomi Gündemi ve Duygu Durumu İncelemesi: Twitter Analizi. İzmir İktisat Dergisi, Cilt 38, Sayı 3, Sayfa 862-883.
11. Bushman R.M. & Chen C.D. & Williams C.D. (2017). Informativeness and Timeliness of Text Similarity Measures for Predicting Banks' Tail Comovement. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2983315, Erişim Tarihi: 19.02.2024.
12. Chatchawan S. (2021). Effects of Central Bank Communication on Financial Markets: A Factor-Augmented Vector Autoregressive Approach. Journal of Business Administration, Vol. 44 No. 171.
13. Cormier B. & Manger M.S. (2018). The Evolution of World Bank Conditionality: A Quantitative Text Analysis. https://www.peio.me/wp-content/uploads/2020/01/PEIO13_paper_46.pdf, Erişim Tarihi: 20.02.2024.
14. Çelik Ş. & Erer D. & Erer E. & Güleç T.C. (2014). TCMB Para Politikası Kararlarındaki Değişimlerin ve TCMB, FED ve ECB Sözlü Yönlendirmelerin BIST 100 Oynaklığı Üzerindeki Etkisinin Analizi (2002-2014). https://dergipark.org.tr/tr/download/article-file/295304, Erişim Tarihi: 02.12.2024.
15. Egesdal, M. & Gill M., Rotemberg M. (2015). How Federal Reserve Discussions Respond To Increased Transparency, https://scholar.harvard.edu/files/mrotemberg/files/fed_text_oct2015.pdf, 20.02.2024.
16. Ehrmann M. & Talmi J. (2017). Starting From A Blank Page? Semantic Similarity in Central Bank Communication and Market Volatility. ECB Working Paper, No 2023.
17. Gonzales M. & Tadle R.C. (2022). Monetary Policy Press Releases: An International Comparison. BIS Working Papers, No 1023, https://www.bis.org/publ/work1023.pdf, Erişim Tarihi:20.02.2024.
18. Görgün, M.F. ve Demireli, E. (2024). Merkez Bankası Para Politikası Metinleri İçin Kosinüs Benzerlik Skorları: FED Basın Duyuruları Üzerine Ampirik Bir Analiz, Uluslararası Sosyal ve Ekonomik Çalışmalar Dergisi, 5(1), 58-77, DOI: 10.62001/gsijses.1491120.
19. Guo K.H. (2022). Testing and Validating the Cosine Similarity Measure for Textual Analysis. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4258463, Erişim Tarihi: 16.04.2024.
20. Gürkaynak R.S. & Sack B., Swanson E.T. (2005). The Response of Asset Prices to Monetary Policy Actions and Statements. International Journal of Central Banking, https://www.ijcb.org/journal/ijcb05q2a2.htm, 25.02.2024.
21. Hansen S. & McMahon M. (2016). Shocking Language: Understanding the Macroeconomic Effects of Central Bank Communication. Journal of International Economics, No 99.
22. Hansen S. & McMahon M. & Tong M. (2020). The Long-Run Information Effect of Central Bank Communication. European Central Bank Working Paper Series, No 2363.
23. Hernández-Murillo, R. & Shell H.G. (2014). Rising Complexity of the FOMC Statement. Economic Synopses, No. 23.
24. Jansen, D.J. & J. de Haan (2010). An Assessment of the Consistency of ECB Communication using Wordscores, DNB Working Paper, No. 259.
25. Jegadeesh N. & Wu D. (2015). Deciphering Fedspeak: The Information Content of FOMC Meetings. https://www.aeaweb.org/conference/2016/retrieve.php?pdfid=21466&tk=niAkBk3N, Erişim Tarihi: 27.02.2024.
26. Loughran T. & McDonald B. (2011). When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10-Ks. The Journal of Finance, Vol. LXVI No. 1.
27. Loughran T. & McDonald B. (2016). Textual Analysis in Accounting and Finance: A Survey. Journal of Accounting Research, Volume 54, Issue 4.
28. Lucca D.O. & Trebbi F. (2009). Measuring Central Bank Communication: An Automated Approach with Application to FOMC Statements. NBER Working Paper, No. 15367.
29. Masciandro D. & Romelli D. & Rubera G. (2022). Monetary Policy and Financial Markets: Evidence from Twitter Traffic. Bocconi University Working Paper, No. 160.
30. Nan H. & Zexi S. (2021). Uncertain Talking at Central Bank’s Press Conference: News or Noise? HKIMR Working Paper, No.04/2021, Hong Kong Institute for Monetary and Financial Research.
31. Narain N. & Sangani K. (2023). The Market Impact of Fed Communications: The Role of the Press Conference. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4354333, 20.02.2024.
32. Öztürk S. & Sankur B. & Güngör T. & Yılmaz M.B. (2014). Turkish Labeled Text Corpus. https://www.cmpe.boun.edu.tr/~gungort/papers/Turkce%20Etiketli%20Metin%20Derlemi.pdf, Erişim Tarihi: 03.12.2024.
33. Picault M. & Renault T. (2017). Words are Not All Created Equal: A New Measure of ECB Communication. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2980777, Erişim Tarihi: 27.02.2024.
34. Schmeling M. & Wagner C. (2023). Does Central Bank Tone Move Asset Prices? https://ssrn.com/abstract=2629978, Erişim Tarihi: 27.02.2024.
35. Tetlock P.C. (2007). Giving Content to Investor Sentiment: The Role of Media in the Stock Market. The Journal of Finance, Vol. 62 No. 3.
36. Tetlock P.C. (2014). Information Transmission in Finance. The Annual Review of Financial Economics, 2014.6.