Search Results - subject_exact:"Early warning system"

Deep hybrid CNN-LSTM-GRU model for a financial risk early warning system

Muhammad Ali Chohan; Li, Teng; Abrar, Mohammad; … - 2026

Financial risk early warning systems are essential for proactive risk management in volatile markets, particularly for emerging economies such as China. This study develops a hybrid deep learning model integrating Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM), and Gated...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015611314

Predicting bank distress in Europe : using machine learning and a novel definition of distress

Malikkidou, Despo; Strohbach, Wolfgang - 2025

This paper develops an early warning system for predicting distress for large European banks. Using a novel definition of distress derived from banks' headroom above regulatory requirements, we investigate the performance of three machine learning techniques against the traditional logistic...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015185208

Risk detection through LLMs : an EU banking case study in monitoring media with AI

Sehanovic, Vedad; Bacca, Lorenz; Dietz, Charles - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015670428

Early warning system for currency crises using long short-term memory and gated recurrent unit neural networks

Barthélémy, Sylvain; Gautier, Virginie; Rondeau, Fabien - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015108370

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Early warning system for currency crises using long short-term memory and gated recurrent unit neural networks

Barthélémy, Sylvain; Rondeau, Fabien; Gautier, Virginie - 2023

Book / Working Paper

Convolutional neural networks to signal currency crises : from the Asian financial crisis to the Covid crisis

Barthélémy, Sylvain; Gautier, Virginie; Rondeau, Fabien - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014578446

Smog, not lights : tracking Bolivia's 2024-2026 recession from space

Hernani-Limarino, Werner; Eid, Ahmed - 2026

Nighttime lights are the standard satellite proxy for economic activity, but they fail to detect recessions. On a 2020-2024 panel of nine Bolivian departments, VIIRS lights match the sign of PIB growth 78 percent of the time during expansions but only 39 percent during contractions - worse than...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015654701

Early warning and alluvial risk perception of Peruvian business intelligent owners systems

Ramirez-Asis, Edwin; Villegas-Ramirez, Giovani; … - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015394853

Toward a Standard for Landslide Data : Bridging Gaps in Landslide Susceptibility Modeling and Early Warning Systems

Niyokwiringirwa, Priscilla; Gall, Tjark; Jha, Abhas K. - 2026

Landslides claim more than 4,000 lives annually and lead to approximately US$20 billion in economic losses. However, landslide hazard, risk assessment, and early warning systems remain constrained by fragmented, inconsistent, and incomplete data. This study addresses the global data gap by...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015613912

Subsidiarity ex ante and ex post : from the early warning system to the court of justice of the European Union

Huysmans, Martijn; Brink, Ton van den; Van Gruisen, Philippe - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014540174

Interpretable multi-model framework for early warning of SME loan delinquency

Akhmetova, Ardak; Shayakhmetova, Assem; Abdurakhmanov, … - 2026

The rapid expansion of small and medium enterprise (SME) lending has intensified the need for accurate and interpretable credit risk forecasting. Financial institutions must anticipate potential business loan delinquency to maintain portfolio stability and meet regulatory standards. This study...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015614113

The credit gap as a real-time early warning indicator of financial imbalances : a South African perspective

Msiska, Wongani; Sikhosana, Ayanda; Vermeulen, Cobus - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015615329

Hybrid early warning system : Integration of Z-score and machine learning for predicting financial performance of IRB in Indonesia

Mawardi, Imron; Estetiono, Andi; Widiastuti, Tika; … - 2026

Purpose This study aims to develop a hybrid Early Warning System (EWS) that integrates the traditional Z-score method with machine learning algorithms to accurately predict the financial performance and potential failure of IRB in Indonesia. Design/methodology/approach The study employs a data...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015639534

Warning signal and broker’s misconduct in financial markets

Tedde, Mariachiara - 2026 - Prima edizione

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015641816

Energy price crisis and crash early warning system

Yokuş, Turgut; Ay, Ahmet; Yokuş, Nihal - 2026

Over the past fifty years, numerous energy price crises and energy price crashes have occurred worldwide, defined as cases exceeding two standard deviations (large increases or decreases) from the mean of the Energy Market Pressure Index, which is constructed from energy prices and U.S....

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015670552

Machine learning for predicting bank stability : evidence from the Middle East & North Africa region

Farag, Karim; Ibeh, Lawrence; Mutai, Noah Cheruiyot - 2026

Artificial intelligence (AI) has become a contentious topic in the financial services sector, especially regarding its capacity to provide more accurate bank risk predictions than the traditional econometric models. However, limited research has so far been conducted in the MENA countries. In...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015664816

Hunger hotspots : FAO-WFP early warnings on acute food insecurity : June to November 2026 outlook

2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015677753

Public-data causal multiscale wavelet spillover learning for stock index volatility forecasting and risk early warning

Liu, Hengyan; Shen, Yisu; Jiang, Aiping - 2026

Accurate volatility forecasting and timely risk early warning are foundational requirements of financial risk management: Value-at-Risk estimates, portfolio risk limits, derivative hedging ratios, and stress-test scenario calibrations all depend on forward-looking volatility signals that remain...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015676659

Beyond volatility : a leakage-safe residual-stress signal for drawdown risk monitoring

Liu, Ting - 2026

Monitoring equity drawdown risk requires real-time indicators that can be implemented without look-ahead bias and that may add information beyond standard volatility measures. This study develops a leakage-safe residual-stress indicator from cross-sectional PCA reconstruction errors in U.S....

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016059391

A composite indicator of systemic risk related to the Italian financial cycle

Moller, Luca - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016061396

Learning from hospital financial distress associated with negative cash reserves

Shanmugam, Ramalingam; Mileski, Michael; Beauvais, Bradley - 2026

This study introduces a multivariate distance-based framework for analyzing hospital liquidity stress using three financial indicators: cash reserves, days with negative cash, and accounts receivable. Using Definitive Healthcare data from 2020-2025, the study applies principal component analysis...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016061377

Monitoring food price volatility in Ukraine : implications for social protection and ensuring the right to food

Borodina, Olena - 2026

This paper explores the applicability of the Food and Agriculture Organization's Global Information and Early Warning System (GIEWS) indicator of price anomalies for monitoring food price volatility in Ukraine, particularly amidst the challenges posed by the ongoing war. Recognizing the...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016064692

Early warning systems in Indonesian Islamic banks : a comparison of Islamic commercial and rural banks

Mawardi, Imron; Al Mustofa, Muhammad Ubaidillah; … - 2023

The study examines the stability of Indonesian Islamic Commercial Bank (ICB) and Islamic Rural Bank (IRB) by employing a Markov Switching Dynamic model of two regimes, stable (tranquil) and unstable (crisis). This study utilizes monthly data between December 2007 and April 2022. Findings show...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014500626

Predicting bank distress in Europe: Using machine learning and a novel definition of distress

Malikkidou, Despo; Strohbach, Wolfgang - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015199522

Forecasting volatility spillovers across Chinese financial industries : an out-of-sample framework using a novel matrix autoregressive model

Liu, Chengcheng; Fang, Tong - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015636670

Valuing Disaster Prevention : Desert Locust Monitoring and Control

Gantois, Joséphine; Missirian, Anouch; Linnros, Evelina; … - 2026

Monitoring systems for disaster prevention are costly, and measuring benefits is difficult when monitoring effort is endogenous. We provide the first causal estimate of one such system's impact using three decades of desert locust monitoring data. We document conflict-induced interruptions to...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015653979

Identifying macrofinancial risk regimes in Malta

Gatt, William; Vella, Sarah - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015596026

Time sensitive and oversampling learning for systemic crisis forecasting

De Nicolò, Francesco; La Rocca, Marianna; Marrone, Antonio - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015101836

Preferences for Warning Signal Quality : Experimental Evidence

Ugarov, Alexander; Gaduh, Arya; McGee, Peter - 2026

We use a laboratory experiment to study preferences over false-positive and false-negative rates of warning signals for an adverse event with a known prior. We find that subjects decrease their demand with signal quality, but less than predicted by our theory. There is asymmetric...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015626321

Mapping the knowledge domain of corporate financial distress prediction

Gurmeet Singh; Singla, Ravi - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015674944

New forecasting methods for an old problem : predicting 147 years of systemic financial crises

Plessis, Emile du; Fritsche, Ulrich - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015373950

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New forecasting methods for an old problem : predicting 147 years of systemic financial crises

Plessis, Emile du; Fritsche, Ulrich - 2022

Book / Working Paper

Developing an early warning system with machine learning and post-crisis information

Baek, Yaein - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016076764

Valuing the economic impact of river floods and early flood warning for households in Bangladesh

Zayed, Stephanie; Morrison, Laura T. R.; Lapidus, Daniel; … - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015330771

Understanding and predicting systemic corporate distress : a machine-learning approach

Hacibedel, Burcu; Qu, Ritong - 2023

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014489149

Tailored microprudential recommendations for bank profit retention using a risk tolerance framework

Jakubik, Petr; Moinescu, Bogdan Gabriel - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015333018

Early Warning Systems for identifying financial instability

Allaj, Erindi; Sanfelici, Simona - 2023

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014465353

Exploring corporate capital structure and overleveraging in the pharmaceutical industry

Issa, Samar; Issa, Hussein - 2025

This paper applies an empirical model of corporate capital structure, optimal debt, and overleveraging to estimate overleveraging measured as the difference between actual and optimal debt. Estimated using a sample of the twenty largest pharmaceutical firms, covering the time span from 2000 to...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015333730

Catalysing business engagement in early warning systems

2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015329002

Development of early warning systems in Croatian companies

Kereta, Josip; Plećaš, Mihael; Gogolja, Janko - 2023

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014490969

Early warning system for preventing bank distress in Brazil

Barboza, Flavio Luiz de Moraes; Barbosa, Jorge Henrique … - 2023

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014306887

Technical development of countercyclical capital buffer implementation in Mongolia's banking sector

Oyungerel, Enkhbaatar; Erdenebileg, Urangoo - 2025

This paper attempts to develop a framework for implementing the Countercyclical Capital Buffer (CCyB) in Mongolia's banking sector by identifying early warning indicators of systemic risk and examining the impact of capital adequacy on bank lending. Using quarterly data from 2000 to 2024, the...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015423905

Can we better predict financial crisis? : The role of Laplacian-energy-like measure

Zhao, Xian; Huang, Chuangxia; Yang, Xiaoguang; Cao, Jie; … - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015470795

Identifying macrofinancial risk regimes in Malta

Gatt, William; Vella, Sarah - 2025

The withdrawal of public sector intervention from Malta's housing market commenced in the early 1990s, while financial markets were liberalised in 1994. These developments were likely behind the significant expansion in credit and house price appreciation experienced over the past two decades,...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015450380

The future of conflict early warning : new technologies and policy impact : workshop proceedings

2025

The workshop "The Future of Conflict Early Warning: New Technologies and Policy Impact" explored advancements in AI, data analytics, and their applications in conflict prevention. Key conclusions include the need for collaboration between policymakers and researchers to develop practical tools...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015453041

Empowering financial supervision : a suptech experiment using machine learning in an early warning system

Alonso, Andrés; Azqueta-Gavaldón, Andrés; Carbó, … - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015409631

The impact of temperature and precipitation on wheat production in Türkiye

Demirhan, Aslıhan Atabek; Bayraktar, Saide Simin - 2025

It is now a well-known fact that climate is changing globally at an unprecedented rate and agriculture is one of the most vulnerable sectors to this change. Considered as a significant threat for food security, climate change and its impact on agricultural practices are among the most prominent...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015410490

Early warning of bubbles in the agricultural commodity market : evidence from LPPLS confidence indicators

Xu, Hai-Chuan; Tan, Yu-Zhen; Fan, Han-Xiao; Zhou, Wei-Xing - 2025

This study leverages the Log-Periodic Power Law Singularity (LPPLS) confidence indicator to effectively identify bubbles in agricultural commodity markets. We analyze five major grain price indices reported by the International Grains Council (IGC) from January 2000 to April 2023, successfully...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015437814

Predicting retail customers' distress in the finance industry : an early warning system approach

Beltman, Jaap; Machado, Marcos R.; Osterrieder, Joerg R. - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015441218

Real-time monitoring procedures for early detection of bubbles

Whitehouse, E. J.; Harvey, David I.; Leybourne, Stephen … - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015441644

Warning on crypto assets

2025

In November 2024, the value of certain crypto-assets has significantly and suddenly increased, hitting new records. This reflects an intensifying interest in relation to crypto-assets and confirms their highly volatile nature. ESMA is cautioning investors against being caught up in this hype....

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015428066

An analytical approach to credit risk assessment using machine learning models

Machado, Marcos R.; Chen, Daniel Tianfu; Osterrieder, … - 2025

This study presents a novel Early Warning System for monitoring the credit risk of commercial customers at a large international bank headquartered in the Netherlands. Traditional early warning methods often rely on backward-looking indicators such as probability of default or loss given...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015506690