Can central bank speeches predict financial market turbulence? Evidence from an adaptive NLP sentiment index analysis using XGBoost machine learning technique von Petropoulos, Anastasios, Siakoulis, Vasilis

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Re-constructing the interbank links using machine learning techniques. An application to the Greek interbank market von Petropoulos, Anastasios, Siakoulis, Vasilis, Lazaris, Panagiotis, Chatzis, Sotirios

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Predicting bank insolvencies using machine learning techniques von Petropoulos, Anastasios, Siakoulis, Vasilis, Stavroulakis, Evangelos, Vlachogiannakis, Nikolaos E.

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A stacked generalization system for automated FOREX portfolio trading von Petropoulos, Anastasios, Chatzis, Sotirios P., Siakoulis, Vasilis, Vlachogiannakis, Nikos

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Towards an early warning system for sovereign defaults leveraging on machine learning methodologies von Petropoulos, Anastasios, Siakoulis, Vasilis, Stavroulakis, Evangelos

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Sentiments Extracted from News and Stock Market Reactions in Vietnam von Vu, Loan Thi, Pham, Dong Ngoc, Kieu, Hang Thu, Pham, Thuy Thi Thanh

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“Decoding” Policy Perspectives: Structural Topic Modeling of European Central Bankers’ Speeches von Warin, Thierry, Stojkov, Aleksandar

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Assessing Machine Learning Techniques for Predicting Banking Crises in India von Puli, Sreenivasulu, Thota, Nagaraju, Subrahmanyam, A. C. V.

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A machine learning approach for micro-credit scoring von Ampountolas, Apostolos, Nde, Titus Nyarko, Date, Paresh, Constantinescu, Corina

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Estimating the BIS capital adequacy ratio for Korean banks using machine learning: Predicting by variable selection using random forest algorithms von Park, Jaewon, Shin, Minsoo, Heo, Wookjae

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Approaching European Supervisory Risk Assessment with SupTech: A Proposal of an Early Warning System von Guerra, Pedro, Castelli, Mauro, Côrte-Real, Nadine

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