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Incorporating financial development indicators into early warning systems
Journal of Economic Asymmetries. 2023. Vol. 27. Article e00284.
Ponomarenko A. A., Татаринцев С. А.
We set up an early warning system for financial crises based on the Random Forrest approach. We use a novel set of predictors that comprises financial development indicators in addition to conventional imbalances measures. The evaluation of the model is conducted using a three-step procedure (i.e. training, validation and testing sub-samples). The results indicate that combining financial imbalances and financial development indicators helps to improve the out-of-sample accuracy of the early warning system.
Barut A., Proskuryakova L. N., Yakutkina V. et al., Renewable Energy 2026 Vol. 267 Article 125736
The global demand for rare earth metals (REM) has exceeded the global supply, exacerbating the deficit of these resources for wind turbines, solar panels, electric vehicles, and nuclear reactors. The largest REM exporting and importing countries have the power to influence energy transition in their own countries and around the world. This study analyzes the ...
Added: April 8, 2026
Shchepeleva M., Финансы: теория и практика 2025 Т. 29 № 4 С. 146–162
This research is devoted to the analysis of financial crises. We examine different classifications of crises, methods of forecasting, approaches to building systems of early warning indicators. To better understand the potential for predicting financial crises, we conduct our own empirical research, comparing Logit model and random forest to predict currency crises in developing countries. ...
Added: February 12, 2026
Vasilyeva R., Shakib M., Sohag K. et al., Emerging Markets Review 2023 No. 57 Article 101059
We investigate if financial development (FD) can reduce the export concentration in regional context, corroborating the role of the World Trade Organization (WTO) membership, sanctions and investment potential. Given the considerable heterogeneity in data across regions and over time, we apply the Method of Moments Quantile Regression (MMQR) to analyze panel time-series data from 2009 to 2019. Our finding ...
Added: December 26, 2025
Тушнолобова М. О., Экономическая социология 2025
Bruce Carruthers’ book “The Economy of Promises: Trust, Power, and Credit in America” is devoted to a historical and sociological analysis of the evolution of credit relations in the United States. The key question that the author answers is how did creditors decide whom to trust in different periods of U. S. history? The author ...
Added: November 18, 2025
Soldatova A., Финансы, деньги, инвестиции 2023 № 4 С. 9–15
The price of gold is the most important economic indicator. Expectations of rising inflation and higher key rates from central banks are driving investor interest in gold around the world. Given the increasing number of factors influencing the dynamics of the gold rate in the world, forecasting gold prices requires new methods and modern technological ...
Added: July 8, 2025
Shchepeleva M., Procedia Computer Science 2024 Vol. 242 P. 51–56
We test the predictive performance of different ensemble methods for forecasting systemic risk in Russia for the period 2008-2024. In contrast to the existing research on machine learning ensemble techniques, we find that conventional random forest works better for the Russian data. Based on this model, we additionally conduct variable importance analysis. We identify that ...
Added: June 17, 2025
What is the relationship between biodiversity and the frequency of financial crises? Global evidence
Stolbov M., Shchepeleva M., Parfenov D., Economics Letters 2025 Vol. 250 Article 112259
The paper studies the relationship between the state of world’s biodiversity proxied by the Living Planet Index and the frequency of financial crises, conditional on global economic growth and the total number of biodiversity-related environmental policy instruments, during 1970–2018. We find that the increased frequency of banking crises as well as triple crises, i.e. simultaneously ...
Added: June 17, 2025
Grigoryev L. M., Россия в глобальной политике 2025 Т. 23 № 2 С. 170–188
The period preceding the reforms of the 1990s, the activities of the leaders and participants of the processes should be discussed “according to the bylinas of that time”, and not according to memories and later adjustments to a given or even known result. This does not exclude a contemporary assessment of past events. But we ...
Added: May 16, 2025
Forecasting Stadium Attendance Using Machine Learning Models: A Case of the National Football League
Пан Ю., Wang F., Studia Sportiva 2024 Vol. 18 No. 2 P. 147–164
Added: May 16, 2025
Tikhomirova A., Journal of Economic Sociology 2025 Vol. 26 No. 1 P. 154–180
Consumption is a focal element of modern society. Dynamic by nature, it reflects diverse societal changes facilitated by a variety of external factors, including cri- ses. Consumption practices in times of crisis have drawn considerable scholarly attention and are reflected in the vast amount of research that requires systemati- zation and generalization.
Given the significance of ...
Added: January 31, 2025
Afanasev V., Финансы и бизнес 2024 Vol. 20 No. 3 P. 71–88
The conventional approach to default prediction implies using financial ratios as predictors. This paper provides evidence for improvement in the quality of default prediction for auto repair firms if non-financial data is included in the models. The study uses a sample of more than 200 firms, which defaulted in 2018–2023 and 10 healthy peers samples ...
Added: October 2, 2024
Stolbov M., Shchepeleva M., Environmental and Sustainability Indicators 2024 Vol. 22 Article 100389
The paper studies the relationships among the composite indicators of environmental performance, financial development, systemic risk and economic uncertainty for a balanced panel of 57 countries during 2010–2020. The analysis builds on panel local projections by Jord´ a (2005). In addition to the whole panel, this technique also applies to two sub-panels obtained via the ...
Added: May 22, 2024
Ignatenko V., Surkov A., Sergei Koltcov, PeerJ Computer Science 2024 Vol. 10 Article e1775
The random forest algorithm is one of the most popular and commonly used algorithms
for classification and regression tasks. It combines the output of multiple decision trees
to form a single result. Random forest algorithms demonstrate the highest accuracy on
tabular data compared to other algorithms in various applications. However, random
forests and, more precisely, decision trees, are usually ...
Added: February 16, 2024
Bukina T. V., Kashin D., Экономический журнал Высшей школы экономики 2024 Т. 28 № 1 С. 81–107
The paper reveals the forecasts for regional inflation based on the regions of the Privolzhskiy Federal District (PFD). The purpose of the study is to determine the model that most accurately predicts regional inflation. The paper compares the tools of machine learning – support vector machines, gradient boosting, and random forest – with econometric models ...
Added: February 13, 2024
Dungey M., Hurn S., Shi S. et al., Econometrics 2019 P. 1–20
Crises in the banking and sovereign debt sectors give rise to heightened financial fragility.
Of particular concern is the development of self-fulfilling feedback loops where crisis conditions in
one sector are transmitted to the other sector and back again. We use time-varying tests of Granger
causality to demonstrate how empirical evidence of connectivity between the banking and sovereign
sectors ...
Added: November 10, 2023
Lee H., Chernikov S., Nagy S. et al., Social Sciences 2022
Added: September 27, 2023
Umar Z., Riaz Y., Shahab Y. et al., Pacific-Basin Finance Journal 2023 Vol. 80 Article 102056
This paper explores the connectedness between the returns and volatilities of the conventional and Islamic bond markets. We use the level, slope, and curvature of the US yield curve and estimate the connectedness of these factors with the Dow Jones Islamic indices (of 3 to 10 years of maturity) as well as the minimum connectedness portfolio. The ...
Added: June 22, 2023
Ponomarenko A. A., Emerging Markets Review 2013 Vol. 15 P. 92–106
Added: March 28, 2023
Дерюгина Е. Б., Ponomarenko A. A., Рожкова А. М., Economic Analysis and Policy 2020 Vol. 67 P. 221–238
Added: March 28, 2023
Nikitin M., Урошевич Б., Деньги и кредит 2022 Т. 81 № 4 С. 3–33
The crisis of the euro zone in 2010–2012 brought several important questions to the fore, including the question of the proper level of financial integration and the optimal exchange rate arrangements between countries that are part of tightly knit financial networks. Using a simple Diamond–Dybvig style theoretical model, we show that the effects of increased ...
Added: February 12, 2023
Deryugina E., Maria Guseva, Alexey Ponomarenko, , in: Risk Assessment and Financial Regulation in Emerging Markets' Banking: Trends and Prospects.: Springer, 2021. P. 277–286.
We analyse the ability of credit gap measures to predict banking crises by estimating the usefulness measure conditionally on policymaker's preferences. The results show that the signals based on the credit gap indicators are most useful when the policymaker’s preferences regarding Type I and Type II errors are approximately equal. However, according to the current ...
Added: January 31, 2023
Stolbov M., Shchepeleva M., Risks 2022 Vol. 10 No. 12
This paper seeks to identify the most important global drivers of credit-to-GDP gaps for 35 countries. The analysis is performed on a country-by-country basis for the sub-periods 2000Q1:2007Q2, 2007Q3:2013Q4, and 2014Q1:2021Q1 and is based on two state-of-the-art methods for variable selection in the time series framework: the one covariate at a time multiple testing (OCMT) ...
Added: January 5, 2023