Dergiler / Central Bank Review / 2021 / Cilt: 21 - Sayı: 4

Can central bank speeches predict financial market turbulence? Evidence from an adaptive NLP sentiment index analysis using XGBoost machine learning technique

Sayfa
143–150
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Using a combination of dictionaries which are either predefined or build based on historical speeches of the corpus we train an Extreme Gradient Boosting model that generates a sentiment index which signals turmoil with acceptable accuracy when passing a specific threshold.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Central Bank speeches usually function as aggregators of internal quantitative and qualitative analysis of the institutions regarding the macro economy, the monetary policy and the health of the financial systems.
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Temel Bulgular & Veri:Speeches usually function as a summary of the current status of a countries economic health, the undergoing trends and some future perspectives of the global economy.
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Sonuç & Katkı:Using a combination of dictionaries which are either predefined or build based on historical speeches of the corpus we train an Extreme Gradient Boosting model that generates a sentiment index which signals turmoil with acceptable accuracy when passing a specific threshold.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Alan Parametreleri

Özet

Central Bank speeches usually function as aggregators of internal quantitative and qualitative analysis of the institutions regarding the macro economy, the monetary policy and the health of the financial systems. Speeches usually function as a summary of the current status of a countries economic health, the undergoing trends and some future perspectives of the global economy. In this study departing from classical econometrics we employ natural language processing technologies in combination with machine learning techniques in order to filter out the most important signals in the corpus of speeches and translate into a sentiment index for forecasting the future financial markets behaviour. In our analysis, it is evident that central banker's expectations on economy tend to exhibit a predictive ability for financial markets turmoil. Using a combination of dictionaries which are either predefined or build based on historical speeches of the corpus we train an Extreme Gradient Boosting model that generates a sentiment index which signals turmoil with acceptable accuracy when passing a specific threshold.

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Bu Makaleye Atıf Yap

PETROPOULOS, A., SİAKOULİS, V. (2021). Can central bank speeches predict financial market turbulence? Evidence from an adaptive NLP sentiment index analysis using XGBoost machine learning technique. Central Bank Review, Cilt: 21 - Sayı: 4, 143–150. https://ajindex.com/articles/415023

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Kaynakça (3)

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  3. Deep Learning. MIT press. Hubert, Paul, Fabien, Labondance, February 17, 2017. Central Bank Sentiment and Policy Expectations. Bank of England Working. Paper No. 648. Kahveci, Eyup, Odabas¸, Aysun, 2016. Central banks' communication strategy and content analysis of monetary policy statements: the case of Fed, ECB and CBRT. In: Procedia-Social and Behavioral Sciences, 235, pp. 618e629. Maqsood, H., Mehmood, I., Maqsood, M., Yassood, Y., February 2020. A local and global event sentiment based efficient stock exchange forecasting using deep learning. Int. J. Inf. Manag. 50, 432e451. Masawi, Becksndale, Bhattacharya, Sukanto, Terry, Boulter, 2018. Does the information content of central bank speeches impact on the level of exchange rate? A comparative study of Canadian and Australian Central Bank communications. Rev. Pac. Basin Financ. Mark. P